identifier
stringlengths 7
18
| space
stringclasses 4
values | uid
stringlengths 1
6
| arch_str
stringlengths 1
32
| input
stringlengths 8.51k
461k
| target_metric
stringclasses 1
value | val_accuracy
float64 0
95.1
| flops
float64 31.1M
14.7B
| params
float64 227k
50M
| metadata
stringlengths 0
1.46k
| metainformation
stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|
NASBench101_245750
|
NASBench101
|
245750
|
94c86ebaf6bb0d7231d823db1d98ba8e
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_986[FLOAT, 128x3x3x3]
%onnx::Conv_987[FLOAT, 128]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x1x1]
%onnx::Conv_998[FLOAT, 128x128x1x1]
%onnx::Conv_1001[FLOAT, 128x128x1x1]
%onnx::Conv_1004[FLOAT, 128x128x1x1]
%onnx::Conv_1007[FLOAT, 128x128x1x1]
%onnx::Conv_1010[FLOAT, 128x128x1x1]
%onnx::Conv_1013[FLOAT, 128x128x1x1]
%onnx::Conv_1016[FLOAT, 128x128x1x1]
%onnx::Conv_1019[FLOAT, 128x128x1x1]
%onnx::Conv_1022[FLOAT, 128x128x1x1]
%onnx::Conv_1025[FLOAT, 128x128x1x1]
%onnx::Conv_1028[FLOAT, 128x128x1x1]
%onnx::Conv_1031[FLOAT, 128x128x1x1]
%onnx::Conv_1034[FLOAT, 128x128x1x1]
%onnx::Conv_1037[FLOAT, 128x128x1x1]
%onnx::Conv_1040[FLOAT, 128x128x1x1]
%onnx::Conv_1043[FLOAT, 128x128x1x1]
%onnx::Conv_1046[FLOAT, 128x128x1x1]
%onnx::Conv_1049[FLOAT, 128x128x1x1]
%onnx::Conv_1052[FLOAT, 256x128x1x1]
%onnx::Conv_1053[FLOAT, 256]
%onnx::Conv_1055[FLOAT, 256x256x1x1]
%onnx::Conv_1058[FLOAT, 256x256x1x1]
%onnx::Conv_1061[FLOAT, 256x128x1x1]
%onnx::Conv_1064[FLOAT, 256x256x1x1]
%onnx::Conv_1067[FLOAT, 256x128x1x1]
%onnx::Conv_1070[FLOAT, 256x256x1x1]
%onnx::Conv_1073[FLOAT, 256x256x1x1]
%onnx::Conv_1076[FLOAT, 256x256x1x1]
%onnx::Conv_1079[FLOAT, 256x256x1x1]
%onnx::Conv_1082[FLOAT, 256x256x1x1]
%onnx::Conv_1085[FLOAT, 256x256x1x1]
%onnx::Conv_1088[FLOAT, 256x256x1x1]
%onnx::Conv_1091[FLOAT, 256x256x1x1]
%onnx::Conv_1094[FLOAT, 256x256x1x1]
%onnx::Conv_1097[FLOAT, 256x256x1x1]
%onnx::Conv_1100[FLOAT, 256x256x1x1]
%onnx::Conv_1103[FLOAT, 256x256x1x1]
%onnx::Conv_1106[FLOAT, 256x256x1x1]
%onnx::Conv_1109[FLOAT, 256x256x1x1]
%onnx::Conv_1112[FLOAT, 256x256x1x1]
%onnx::Conv_1115[FLOAT, 512x256x1x1]
%onnx::Conv_1116[FLOAT, 512]
%onnx::Conv_1118[FLOAT, 512x512x1x1]
%onnx::Conv_1121[FLOAT, 512x512x1x1]
%onnx::Conv_1124[FLOAT, 512x256x1x1]
%onnx::Conv_1127[FLOAT, 512x512x1x1]
%onnx::Conv_1130[FLOAT, 512x256x1x1]
%onnx::Conv_1133[FLOAT, 512x512x1x1]
%onnx::Conv_1136[FLOAT, 512x512x1x1]
%onnx::Conv_1139[FLOAT, 512x512x1x1]
%onnx::Conv_1142[FLOAT, 512x512x1x1]
%onnx::Conv_1145[FLOAT, 512x512x1x1]
%onnx::Conv_1148[FLOAT, 512x512x1x1]
%onnx::Conv_1151[FLOAT, 512x512x1x1]
%onnx::Conv_1154[FLOAT, 512x512x1x1]
%onnx::Conv_1157[FLOAT, 512x512x1x1]
%onnx::Conv_1160[FLOAT, 512x512x1x1]
%onnx::Conv_1163[FLOAT, 512x512x1x1]
%onnx::Conv_1166[FLOAT, 512x512x1x1]
%onnx::Conv_1169[FLOAT, 512x512x1x1]
%onnx::Conv_1172[FLOAT, 512x512x1x1]
%onnx::Conv_1175[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1176 = Identity(%onnx::Conv_1116)
%onnx::Conv_1173 = Identity(%onnx::Conv_1116)
%onnx::Conv_1170 = Identity(%onnx::Conv_1116)
%onnx::Conv_1167 = Identity(%onnx::Conv_1116)
%onnx::Conv_1164 = Identity(%onnx::Conv_1116)
%onnx::Conv_1161 = Identity(%onnx::Conv_1116)
%onnx::Conv_1158 = Identity(%onnx::Conv_1116)
%onnx::Conv_1155 = Identity(%onnx::Conv_1116)
%onnx::Conv_1152 = Identity(%onnx::Conv_1116)
%onnx::Conv_1149 = Identity(%onnx::Conv_1116)
%onnx::Conv_1146 = Identity(%onnx::Conv_1116)
%onnx::Conv_1143 = Identity(%onnx::Conv_1116)
%onnx::Conv_1140 = Identity(%onnx::Conv_1116)
%onnx::Conv_1137 = Identity(%onnx::Conv_1116)
%onnx::Conv_1134 = Identity(%onnx::Conv_1116)
%onnx::Conv_1131 = Identity(%onnx::Conv_1116)
%onnx::Conv_1128 = Identity(%onnx::Conv_1116)
%onnx::Conv_1125 = Identity(%onnx::Conv_1116)
%onnx::Conv_1122 = Identity(%onnx::Conv_1116)
%onnx::Conv_1119 = Identity(%onnx::Conv_1116)
%onnx::Conv_1113 = Identity(%onnx::Conv_1053)
%onnx::Conv_1110 = Identity(%onnx::Conv_1053)
%onnx::Conv_1107 = Identity(%onnx::Conv_1053)
%onnx::Conv_1104 = Identity(%onnx::Conv_1053)
%onnx::Conv_1101 = Identity(%onnx::Conv_1053)
%onnx::Conv_1098 = Identity(%onnx::Conv_1053)
%onnx::Conv_1095 = Identity(%onnx::Conv_1053)
%onnx::Conv_1092 = Identity(%onnx::Conv_1053)
%onnx::Conv_1089 = Identity(%onnx::Conv_1053)
%onnx::Conv_1086 = Identity(%onnx::Conv_1053)
%onnx::Conv_1083 = Identity(%onnx::Conv_1053)
%onnx::Conv_1080 = Identity(%onnx::Conv_1053)
%onnx::Conv_1077 = Identity(%onnx::Conv_1053)
%onnx::Conv_1074 = Identity(%onnx::Conv_1053)
%onnx::Conv_1071 = Identity(%onnx::Conv_1053)
%onnx::Conv_1068 = Identity(%onnx::Conv_1053)
%onnx::Conv_1065 = Identity(%onnx::Conv_1053)
%onnx::Conv_1062 = Identity(%onnx::Conv_1053)
%onnx::Conv_1059 = Identity(%onnx::Conv_1053)
%onnx::Conv_1056 = Identity(%onnx::Conv_1053)
%onnx::Conv_1050 = Identity(%onnx::Conv_987)
%onnx::Conv_1047 = Identity(%onnx::Conv_987)
%onnx::Conv_1044 = Identity(%onnx::Conv_987)
%onnx::Conv_1041 = Identity(%onnx::Conv_987)
%onnx::Conv_1038 = Identity(%onnx::Conv_987)
%onnx::Conv_1035 = Identity(%onnx::Conv_987)
%onnx::Conv_1032 = Identity(%onnx::Conv_987)
%onnx::Conv_1029 = Identity(%onnx::Conv_987)
%onnx::Conv_1026 = Identity(%onnx::Conv_987)
%onnx::Conv_1023 = Identity(%onnx::Conv_987)
%onnx::Conv_1020 = Identity(%onnx::Conv_987)
%onnx::Conv_1017 = Identity(%onnx::Conv_987)
%onnx::Conv_1014 = Identity(%onnx::Conv_987)
%onnx::Conv_1011 = Identity(%onnx::Conv_987)
%onnx::Conv_1008 = Identity(%onnx::Conv_987)
%onnx::Conv_1005 = Identity(%onnx::Conv_987)
%onnx::Conv_1002 = Identity(%onnx::Conv_987)
%onnx::Conv_999 = Identity(%onnx::Conv_987)
%onnx::Conv_996 = Identity(%onnx::Conv_987)
%onnx::Conv_993 = Identity(%onnx::Conv_987)
%onnx::Conv_990 = Identity(%onnx::Conv_987)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_986, %onnx::Conv_987)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_7_output_0 = Add(%/layers.1/Add_6_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_7_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_7_output_0 = Add(%/layers.2/Add_6_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_7_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_7_output_0 = Add(%/layers.3/Add_6_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_7_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_7_output_0 = Add(%/layers.5/Add_6_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_7_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_7_output_0 = Add(%/layers.6/Add_6_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_7_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_7_output_0 = Add(%/layers.7/Add_6_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_7_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_7_output_0 = Add(%/layers.9/Add_6_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_7_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_7_output_0 = Add(%/layers.10/Add_6_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_7_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1169, %onnx::Conv_1170)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1172, %onnx::Conv_1173)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_7_output_0 = Add(%/layers.11/Add_6_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_7_output_0, %onnx::Conv_1175, %onnx::Conv_1176)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%984 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %984
}
|
val_accuracy
| 87.60016
| 2,059,937,792
| 6,780,298
|
{'zcp_epe_nas': 98.00862038251148, 'zcp_fisher': 40.17920684814453, 'zcp_flops': 32959004672.0, 'zcp_grad_norm': 153.7720184326172, 'zcp_grasp': -31.1533203125, 'zcp_jacov': -16.051129540136294, 'zcp_l2_norm': 1438.436767578125, 'zcp_nwot': 237.82970757830375, 'zcp_params': 6780298.0, 'zcp_plain': -0.016512613743543, 'zcp_snip': 1100.2493896484375, 'zcp_synflow': 136.8182007516169, 'zcp_zen': 106.63469696044922, 'zcp_val_accuracy': 0.9173678159713741}
| |
NASBench101_244631
|
NASBench101
|
244631
|
9412ff6996f2dcaea98dafce65de1ebe
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_668[FLOAT, 128x3x3x3]
%onnx::Conv_669[FLOAT, 128]
%onnx::Conv_671[FLOAT, 43x128x1x1]
%onnx::Conv_672[FLOAT, 43]
%onnx::Conv_674[FLOAT, 43x43x3x3]
%onnx::Conv_677[FLOAT, 42x128x1x1]
%onnx::Conv_678[FLOAT, 42]
%onnx::Conv_680[FLOAT, 42x42x1x1]
%onnx::Conv_683[FLOAT, 43x128x1x1]
%onnx::Conv_686[FLOAT, 43x43x3x3]
%onnx::Conv_689[FLOAT, 42x128x1x1]
%onnx::Conv_692[FLOAT, 42x42x1x1]
%onnx::Conv_695[FLOAT, 43x128x1x1]
%onnx::Conv_698[FLOAT, 43x43x3x3]
%onnx::Conv_701[FLOAT, 42x128x1x1]
%onnx::Conv_704[FLOAT, 42x42x1x1]
%onnx::Conv_707[FLOAT, 86x128x1x1]
%onnx::Conv_708[FLOAT, 86]
%onnx::Conv_710[FLOAT, 85x85x3x3]
%onnx::Conv_711[FLOAT, 85]
%onnx::Conv_713[FLOAT, 85x128x1x1]
%onnx::Conv_716[FLOAT, 85x85x1x1]
%onnx::Conv_719[FLOAT, 86x256x1x1]
%onnx::Conv_722[FLOAT, 85x85x3x3]
%onnx::Conv_725[FLOAT, 85x256x1x1]
%onnx::Conv_728[FLOAT, 85x85x1x1]
%onnx::Conv_731[FLOAT, 86x256x1x1]
%onnx::Conv_734[FLOAT, 85x85x3x3]
%onnx::Conv_737[FLOAT, 85x256x1x1]
%onnx::Conv_740[FLOAT, 85x85x1x1]
%onnx::Conv_743[FLOAT, 171x256x1x1]
%onnx::Conv_744[FLOAT, 171]
%onnx::Conv_746[FLOAT, 171x171x3x3]
%onnx::Conv_749[FLOAT, 170x256x1x1]
%onnx::Conv_750[FLOAT, 170]
%onnx::Conv_752[FLOAT, 170x170x1x1]
%onnx::Conv_755[FLOAT, 171x512x1x1]
%onnx::Conv_758[FLOAT, 171x171x3x3]
%onnx::Conv_761[FLOAT, 170x512x1x1]
%onnx::Conv_764[FLOAT, 170x170x1x1]
%onnx::Conv_767[FLOAT, 171x512x1x1]
%onnx::Conv_770[FLOAT, 171x171x3x3]
%onnx::Conv_773[FLOAT, 170x512x1x1]
%onnx::Conv_776[FLOAT, 170x170x1x1]
) {
%onnx::Conv_777 = Identity(%onnx::Conv_750)
%onnx::Conv_774 = Identity(%onnx::Conv_750)
%onnx::Conv_771 = Identity(%onnx::Conv_744)
%onnx::Conv_768 = Identity(%onnx::Conv_744)
%onnx::Conv_765 = Identity(%onnx::Conv_750)
%onnx::Conv_762 = Identity(%onnx::Conv_750)
%onnx::Conv_759 = Identity(%onnx::Conv_744)
%onnx::Conv_756 = Identity(%onnx::Conv_744)
%onnx::Conv_753 = Identity(%onnx::Conv_750)
%onnx::Conv_747 = Identity(%onnx::Conv_744)
%onnx::Conv_741 = Identity(%onnx::Conv_711)
%onnx::Conv_738 = Identity(%onnx::Conv_711)
%onnx::Conv_735 = Identity(%onnx::Conv_711)
%onnx::Conv_732 = Identity(%onnx::Conv_708)
%onnx::Conv_729 = Identity(%onnx::Conv_711)
%onnx::Conv_726 = Identity(%onnx::Conv_711)
%onnx::Conv_723 = Identity(%onnx::Conv_711)
%onnx::Conv_720 = Identity(%onnx::Conv_708)
%onnx::Conv_717 = Identity(%onnx::Conv_711)
%onnx::Conv_714 = Identity(%onnx::Conv_711)
%onnx::Conv_705 = Identity(%onnx::Conv_678)
%onnx::Conv_702 = Identity(%onnx::Conv_678)
%onnx::Conv_699 = Identity(%onnx::Conv_672)
%onnx::Conv_696 = Identity(%onnx::Conv_672)
%onnx::Conv_693 = Identity(%onnx::Conv_678)
%onnx::Conv_690 = Identity(%onnx::Conv_678)
%onnx::Conv_687 = Identity(%onnx::Conv_672)
%onnx::Conv_684 = Identity(%onnx::Conv_672)
%onnx::Conv_681 = Identity(%onnx::Conv_678)
%onnx::Conv_675 = Identity(%onnx::Conv_672)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_668, %onnx::Conv_669)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_1_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Slice_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_1_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Slice_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_1_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Slice_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%666 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %666
}
|
val_accuracy
| 89.813703
| 530,417,536
| 1,742,732
|
{'zcp_epe_nas': 140.46577647468862, 'zcp_fisher': 3.8035237789154053, 'zcp_flops': 8486680576.0, 'zcp_grad_norm': 40.45942306518555, 'zcp_grasp': -1.967727661132812, 'zcp_jacov': -16.04735336416637, 'zcp_l2_norm': 639.4888305664062, 'zcp_nwot': 212.43646390352532, 'zcp_params': 1742732.0, 'zcp_plain': 0.07371529936790401, 'zcp_snip': 204.68154907226562, 'zcp_synflow': 59.960542383920526, 'zcp_zen': 62.42807388305664, 'zcp_val_accuracy': 0.911858975887298}
| |
NASBench101_75877
|
NASBench101
|
75877
|
2dfc8987eca08e25bba5342e76c52168
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_833[FLOAT, 128x3x3x3]
%onnx::Conv_834[FLOAT, 128]
%onnx::Conv_836[FLOAT, 64x128x1x1]
%onnx::Conv_837[FLOAT, 64]
%onnx::Conv_839[FLOAT, 64x64x3x3]
%onnx::Conv_842[FLOAT, 64x128x1x1]
%onnx::Conv_845[FLOAT, 64x128x1x1]
%onnx::Conv_848[FLOAT, 64x64x1x1]
%onnx::Conv_851[FLOAT, 64x64x1x1]
%onnx::Conv_854[FLOAT, 64x128x1x1]
%onnx::Conv_857[FLOAT, 64x64x3x3]
%onnx::Conv_860[FLOAT, 64x128x1x1]
%onnx::Conv_863[FLOAT, 64x128x1x1]
%onnx::Conv_866[FLOAT, 64x64x1x1]
%onnx::Conv_869[FLOAT, 64x64x1x1]
%onnx::Conv_872[FLOAT, 64x128x1x1]
%onnx::Conv_875[FLOAT, 64x64x3x3]
%onnx::Conv_878[FLOAT, 64x128x1x1]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_884[FLOAT, 64x64x1x1]
%onnx::Conv_887[FLOAT, 64x64x1x1]
%onnx::Conv_890[FLOAT, 128x128x1x1]
%onnx::Conv_893[FLOAT, 128x128x3x3]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%onnx::Conv_899[FLOAT, 128x128x1x1]
%onnx::Conv_902[FLOAT, 128x128x1x1]
%onnx::Conv_905[FLOAT, 128x128x1x1]
%onnx::Conv_908[FLOAT, 128x256x1x1]
%onnx::Conv_911[FLOAT, 128x128x3x3]
%onnx::Conv_914[FLOAT, 128x256x1x1]
%onnx::Conv_917[FLOAT, 128x256x1x1]
%onnx::Conv_920[FLOAT, 128x128x1x1]
%onnx::Conv_923[FLOAT, 128x128x1x1]
%onnx::Conv_926[FLOAT, 128x256x1x1]
%onnx::Conv_929[FLOAT, 128x128x3x3]
%onnx::Conv_932[FLOAT, 128x256x1x1]
%onnx::Conv_935[FLOAT, 128x256x1x1]
%onnx::Conv_938[FLOAT, 128x128x1x1]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 256x256x1x1]
%onnx::Conv_945[FLOAT, 256]
%onnx::Conv_947[FLOAT, 256x256x3x3]
%onnx::Conv_950[FLOAT, 256x256x1x1]
%onnx::Conv_953[FLOAT, 256x256x1x1]
%onnx::Conv_956[FLOAT, 256x256x1x1]
%onnx::Conv_959[FLOAT, 256x256x1x1]
%onnx::Conv_962[FLOAT, 256x512x1x1]
%onnx::Conv_965[FLOAT, 256x256x3x3]
%onnx::Conv_968[FLOAT, 256x512x1x1]
%onnx::Conv_971[FLOAT, 256x512x1x1]
%onnx::Conv_974[FLOAT, 256x256x1x1]
%onnx::Conv_977[FLOAT, 256x256x1x1]
%onnx::Conv_980[FLOAT, 256x512x1x1]
%onnx::Conv_983[FLOAT, 256x256x3x3]
%onnx::Conv_986[FLOAT, 256x512x1x1]
%onnx::Conv_989[FLOAT, 256x512x1x1]
%onnx::Conv_992[FLOAT, 256x256x1x1]
%onnx::Conv_995[FLOAT, 256x256x1x1]
) {
%onnx::Conv_996 = Identity(%onnx::Conv_945)
%onnx::Conv_993 = Identity(%onnx::Conv_945)
%onnx::Conv_990 = Identity(%onnx::Conv_945)
%onnx::Conv_987 = Identity(%onnx::Conv_945)
%onnx::Conv_984 = Identity(%onnx::Conv_945)
%onnx::Conv_981 = Identity(%onnx::Conv_945)
%onnx::Conv_978 = Identity(%onnx::Conv_945)
%onnx::Conv_975 = Identity(%onnx::Conv_945)
%onnx::Conv_972 = Identity(%onnx::Conv_945)
%onnx::Conv_969 = Identity(%onnx::Conv_945)
%onnx::Conv_966 = Identity(%onnx::Conv_945)
%onnx::Conv_963 = Identity(%onnx::Conv_945)
%onnx::Conv_960 = Identity(%onnx::Conv_945)
%onnx::Conv_957 = Identity(%onnx::Conv_945)
%onnx::Conv_954 = Identity(%onnx::Conv_945)
%onnx::Conv_951 = Identity(%onnx::Conv_945)
%onnx::Conv_948 = Identity(%onnx::Conv_945)
%onnx::Conv_942 = Identity(%onnx::Conv_834)
%onnx::Conv_939 = Identity(%onnx::Conv_834)
%onnx::Conv_936 = Identity(%onnx::Conv_834)
%onnx::Conv_933 = Identity(%onnx::Conv_834)
%onnx::Conv_930 = Identity(%onnx::Conv_834)
%onnx::Conv_927 = Identity(%onnx::Conv_834)
%onnx::Conv_924 = Identity(%onnx::Conv_834)
%onnx::Conv_921 = Identity(%onnx::Conv_834)
%onnx::Conv_918 = Identity(%onnx::Conv_834)
%onnx::Conv_915 = Identity(%onnx::Conv_834)
%onnx::Conv_912 = Identity(%onnx::Conv_834)
%onnx::Conv_909 = Identity(%onnx::Conv_834)
%onnx::Conv_906 = Identity(%onnx::Conv_834)
%onnx::Conv_903 = Identity(%onnx::Conv_834)
%onnx::Conv_900 = Identity(%onnx::Conv_834)
%onnx::Conv_897 = Identity(%onnx::Conv_834)
%onnx::Conv_894 = Identity(%onnx::Conv_834)
%onnx::Conv_891 = Identity(%onnx::Conv_834)
%onnx::Conv_888 = Identity(%onnx::Conv_837)
%onnx::Conv_885 = Identity(%onnx::Conv_837)
%onnx::Conv_882 = Identity(%onnx::Conv_837)
%onnx::Conv_879 = Identity(%onnx::Conv_837)
%onnx::Conv_876 = Identity(%onnx::Conv_837)
%onnx::Conv_873 = Identity(%onnx::Conv_837)
%onnx::Conv_870 = Identity(%onnx::Conv_837)
%onnx::Conv_867 = Identity(%onnx::Conv_837)
%onnx::Conv_864 = Identity(%onnx::Conv_837)
%onnx::Conv_861 = Identity(%onnx::Conv_837)
%onnx::Conv_858 = Identity(%onnx::Conv_837)
%onnx::Conv_855 = Identity(%onnx::Conv_837)
%onnx::Conv_852 = Identity(%onnx::Conv_837)
%onnx::Conv_849 = Identity(%onnx::Conv_837)
%onnx::Conv_846 = Identity(%onnx::Conv_837)
%onnx::Conv_843 = Identity(%onnx::Conv_837)
%onnx::Conv_840 = Identity(%onnx::Conv_837)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_833, %onnx::Conv_834)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%831 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %831
}
|
val_accuracy
| 93.289262
| 1,257,777,152
| 4,166,026
|
{'zcp_epe_nas': 99.09750167733556, 'zcp_fisher': 23.170482635498047, 'zcp_flops': 20124434432.0, 'zcp_grad_norm': 91.72470092773438, 'zcp_grasp': -0.7666015625, 'zcp_jacov': -16.058918543009767, 'zcp_l2_norm': 1040.1199951171875, 'zcp_nwot': 224.82613125938914, 'zcp_params': 4166026.0, 'zcp_plain': 0.006914854981005, 'zcp_snip': 530.2466430664062, 'zcp_synflow': 107.88259954263619, 'zcp_zen': 89.94918060302734, 'zcp_val_accuracy': 0.8866186141967771}
| |
NASBench101_201436
|
NASBench101
|
201436
|
79f54e6a53a122f85431a63006a8f3ad
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_977[FLOAT, 128x3x3x3]
%onnx::Conv_978[FLOAT, 128]
%onnx::Conv_980[FLOAT, 64x128x1x1]
%onnx::Conv_981[FLOAT, 64]
%onnx::Conv_983[FLOAT, 64x64x1x1]
%onnx::Conv_986[FLOAT, 64x128x1x1]
%onnx::Conv_989[FLOAT, 64x128x1x1]
%onnx::Conv_992[FLOAT, 64x64x3x3]
%onnx::Conv_995[FLOAT, 64x64x1x1]
%onnx::Conv_998[FLOAT, 64x64x1x1]
%onnx::Conv_1001[FLOAT, 64x128x1x1]
%onnx::Conv_1004[FLOAT, 64x64x1x1]
%onnx::Conv_1007[FLOAT, 64x128x1x1]
%onnx::Conv_1010[FLOAT, 64x128x1x1]
%onnx::Conv_1013[FLOAT, 64x64x3x3]
%onnx::Conv_1016[FLOAT, 64x64x1x1]
%onnx::Conv_1019[FLOAT, 64x64x1x1]
%onnx::Conv_1022[FLOAT, 64x128x1x1]
%onnx::Conv_1025[FLOAT, 64x64x1x1]
%onnx::Conv_1028[FLOAT, 64x128x1x1]
%onnx::Conv_1031[FLOAT, 64x128x1x1]
%onnx::Conv_1034[FLOAT, 64x64x3x3]
%onnx::Conv_1037[FLOAT, 64x64x1x1]
%onnx::Conv_1040[FLOAT, 64x64x1x1]
%onnx::Conv_1043[FLOAT, 128x128x1x1]
%onnx::Conv_1046[FLOAT, 128x128x1x1]
%onnx::Conv_1049[FLOAT, 128x128x1x1]
%onnx::Conv_1052[FLOAT, 128x128x1x1]
%onnx::Conv_1055[FLOAT, 128x128x3x3]
%onnx::Conv_1058[FLOAT, 128x128x1x1]
%onnx::Conv_1061[FLOAT, 128x128x1x1]
%onnx::Conv_1064[FLOAT, 128x256x1x1]
%onnx::Conv_1067[FLOAT, 128x128x1x1]
%onnx::Conv_1070[FLOAT, 128x256x1x1]
%onnx::Conv_1073[FLOAT, 128x256x1x1]
%onnx::Conv_1076[FLOAT, 128x128x3x3]
%onnx::Conv_1079[FLOAT, 128x128x1x1]
%onnx::Conv_1082[FLOAT, 128x128x1x1]
%onnx::Conv_1085[FLOAT, 128x256x1x1]
%onnx::Conv_1088[FLOAT, 128x128x1x1]
%onnx::Conv_1091[FLOAT, 128x256x1x1]
%onnx::Conv_1094[FLOAT, 128x256x1x1]
%onnx::Conv_1097[FLOAT, 128x128x3x3]
%onnx::Conv_1100[FLOAT, 128x128x1x1]
%onnx::Conv_1103[FLOAT, 128x128x1x1]
%onnx::Conv_1106[FLOAT, 256x256x1x1]
%onnx::Conv_1107[FLOAT, 256]
%onnx::Conv_1109[FLOAT, 256x256x1x1]
%onnx::Conv_1112[FLOAT, 256x256x1x1]
%onnx::Conv_1115[FLOAT, 256x256x1x1]
%onnx::Conv_1118[FLOAT, 256x256x3x3]
%onnx::Conv_1121[FLOAT, 256x256x1x1]
%onnx::Conv_1124[FLOAT, 256x256x1x1]
%onnx::Conv_1127[FLOAT, 256x512x1x1]
%onnx::Conv_1130[FLOAT, 256x256x1x1]
%onnx::Conv_1133[FLOAT, 256x512x1x1]
%onnx::Conv_1136[FLOAT, 256x512x1x1]
%onnx::Conv_1139[FLOAT, 256x256x3x3]
%onnx::Conv_1142[FLOAT, 256x256x1x1]
%onnx::Conv_1145[FLOAT, 256x256x1x1]
%onnx::Conv_1148[FLOAT, 256x512x1x1]
%onnx::Conv_1151[FLOAT, 256x256x1x1]
%onnx::Conv_1154[FLOAT, 256x512x1x1]
%onnx::Conv_1157[FLOAT, 256x512x1x1]
%onnx::Conv_1160[FLOAT, 256x256x3x3]
%onnx::Conv_1163[FLOAT, 256x256x1x1]
%onnx::Conv_1166[FLOAT, 256x256x1x1]
) {
%onnx::Conv_1167 = Identity(%onnx::Conv_1107)
%onnx::Conv_1164 = Identity(%onnx::Conv_1107)
%onnx::Conv_1161 = Identity(%onnx::Conv_1107)
%onnx::Conv_1158 = Identity(%onnx::Conv_1107)
%onnx::Conv_1155 = Identity(%onnx::Conv_1107)
%onnx::Conv_1152 = Identity(%onnx::Conv_1107)
%onnx::Conv_1149 = Identity(%onnx::Conv_1107)
%onnx::Conv_1146 = Identity(%onnx::Conv_1107)
%onnx::Conv_1143 = Identity(%onnx::Conv_1107)
%onnx::Conv_1140 = Identity(%onnx::Conv_1107)
%onnx::Conv_1137 = Identity(%onnx::Conv_1107)
%onnx::Conv_1134 = Identity(%onnx::Conv_1107)
%onnx::Conv_1131 = Identity(%onnx::Conv_1107)
%onnx::Conv_1128 = Identity(%onnx::Conv_1107)
%onnx::Conv_1125 = Identity(%onnx::Conv_1107)
%onnx::Conv_1122 = Identity(%onnx::Conv_1107)
%onnx::Conv_1119 = Identity(%onnx::Conv_1107)
%onnx::Conv_1116 = Identity(%onnx::Conv_1107)
%onnx::Conv_1113 = Identity(%onnx::Conv_1107)
%onnx::Conv_1110 = Identity(%onnx::Conv_1107)
%onnx::Conv_1104 = Identity(%onnx::Conv_978)
%onnx::Conv_1101 = Identity(%onnx::Conv_978)
%onnx::Conv_1098 = Identity(%onnx::Conv_978)
%onnx::Conv_1095 = Identity(%onnx::Conv_978)
%onnx::Conv_1092 = Identity(%onnx::Conv_978)
%onnx::Conv_1089 = Identity(%onnx::Conv_978)
%onnx::Conv_1086 = Identity(%onnx::Conv_978)
%onnx::Conv_1083 = Identity(%onnx::Conv_978)
%onnx::Conv_1080 = Identity(%onnx::Conv_978)
%onnx::Conv_1077 = Identity(%onnx::Conv_978)
%onnx::Conv_1074 = Identity(%onnx::Conv_978)
%onnx::Conv_1071 = Identity(%onnx::Conv_978)
%onnx::Conv_1068 = Identity(%onnx::Conv_978)
%onnx::Conv_1065 = Identity(%onnx::Conv_978)
%onnx::Conv_1062 = Identity(%onnx::Conv_978)
%onnx::Conv_1059 = Identity(%onnx::Conv_978)
%onnx::Conv_1056 = Identity(%onnx::Conv_978)
%onnx::Conv_1053 = Identity(%onnx::Conv_978)
%onnx::Conv_1050 = Identity(%onnx::Conv_978)
%onnx::Conv_1047 = Identity(%onnx::Conv_978)
%onnx::Conv_1044 = Identity(%onnx::Conv_978)
%onnx::Conv_1041 = Identity(%onnx::Conv_981)
%onnx::Conv_1038 = Identity(%onnx::Conv_981)
%onnx::Conv_1035 = Identity(%onnx::Conv_981)
%onnx::Conv_1032 = Identity(%onnx::Conv_981)
%onnx::Conv_1029 = Identity(%onnx::Conv_981)
%onnx::Conv_1026 = Identity(%onnx::Conv_981)
%onnx::Conv_1023 = Identity(%onnx::Conv_981)
%onnx::Conv_1020 = Identity(%onnx::Conv_981)
%onnx::Conv_1017 = Identity(%onnx::Conv_981)
%onnx::Conv_1014 = Identity(%onnx::Conv_981)
%onnx::Conv_1011 = Identity(%onnx::Conv_981)
%onnx::Conv_1008 = Identity(%onnx::Conv_981)
%onnx::Conv_1005 = Identity(%onnx::Conv_981)
%onnx::Conv_1002 = Identity(%onnx::Conv_981)
%onnx::Conv_999 = Identity(%onnx::Conv_981)
%onnx::Conv_996 = Identity(%onnx::Conv_981)
%onnx::Conv_993 = Identity(%onnx::Conv_981)
%onnx::Conv_990 = Identity(%onnx::Conv_981)
%onnx::Conv_987 = Identity(%onnx::Conv_981)
%onnx::Conv_984 = Identity(%onnx::Conv_981)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_977, %onnx::Conv_978)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%975 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %975
}
|
val_accuracy
| 88.661861
| 1,336,027,136
| 4,426,762
|
{'zcp_epe_nas': 105.18975826262655, 'zcp_fisher': 22.09173011779785, 'zcp_flops': 21376434176.0, 'zcp_grad_norm': 115.48481750488281, 'zcp_grasp': -7.7611083984375, 'zcp_jacov': -16.052745569690842, 'zcp_l2_norm': 1190.5875244140625, 'zcp_nwot': 226.80931747943953, 'zcp_params': 4426762.0, 'zcp_plain': 0.030306912958621004, 'zcp_snip': 670.6607666015625, 'zcp_synflow': 106.99330157978977, 'zcp_zen': 99.76847839355469, 'zcp_val_accuracy': 0.9232772588729851}
| |
NASBench101_19674
|
NASBench101
|
19674
|
0be644d9a247d26464cd74d4238c430b
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_806[FLOAT, 128x3x3x3]
%onnx::Conv_807[FLOAT, 128]
%onnx::Conv_809[FLOAT, 43x128x1x1]
%onnx::Conv_810[FLOAT, 43]
%onnx::Conv_812[FLOAT, 43x43x3x3]
%onnx::Conv_815[FLOAT, 43x43x1x1]
%onnx::Conv_818[FLOAT, 43x43x3x3]
%onnx::Conv_821[FLOAT, 42x42x3x3]
%onnx::Conv_822[FLOAT, 42]
%onnx::Conv_824[FLOAT, 43x128x1x1]
%onnx::Conv_827[FLOAT, 43x43x3x3]
%onnx::Conv_830[FLOAT, 43x43x1x1]
%onnx::Conv_833[FLOAT, 43x43x3x3]
%onnx::Conv_836[FLOAT, 42x42x3x3]
%onnx::Conv_839[FLOAT, 43x128x1x1]
%onnx::Conv_842[FLOAT, 43x43x3x3]
%onnx::Conv_845[FLOAT, 43x43x1x1]
%onnx::Conv_848[FLOAT, 43x43x3x3]
%onnx::Conv_851[FLOAT, 42x42x3x3]
%onnx::Conv_854[FLOAT, 86x128x1x1]
%onnx::Conv_855[FLOAT, 86]
%onnx::Conv_857[FLOAT, 86x86x3x3]
%onnx::Conv_860[FLOAT, 85x85x1x1]
%onnx::Conv_861[FLOAT, 85]
%onnx::Conv_863[FLOAT, 85x85x3x3]
%onnx::Conv_866[FLOAT, 85x85x3x3]
%onnx::Conv_869[FLOAT, 86x256x1x1]
%onnx::Conv_872[FLOAT, 86x86x3x3]
%onnx::Conv_875[FLOAT, 85x85x1x1]
%onnx::Conv_878[FLOAT, 85x85x3x3]
%onnx::Conv_881[FLOAT, 85x85x3x3]
%onnx::Conv_884[FLOAT, 86x256x1x1]
%onnx::Conv_887[FLOAT, 86x86x3x3]
%onnx::Conv_890[FLOAT, 85x85x1x1]
%onnx::Conv_893[FLOAT, 85x85x3x3]
%onnx::Conv_896[FLOAT, 85x85x3x3]
%onnx::Conv_899[FLOAT, 171x256x1x1]
%onnx::Conv_900[FLOAT, 171]
%onnx::Conv_902[FLOAT, 171x171x3x3]
%onnx::Conv_905[FLOAT, 171x171x1x1]
%onnx::Conv_908[FLOAT, 171x171x3x3]
%onnx::Conv_911[FLOAT, 170x170x3x3]
%onnx::Conv_912[FLOAT, 170]
%onnx::Conv_914[FLOAT, 171x512x1x1]
%onnx::Conv_917[FLOAT, 171x171x3x3]
%onnx::Conv_920[FLOAT, 171x171x1x1]
%onnx::Conv_923[FLOAT, 171x171x3x3]
%onnx::Conv_926[FLOAT, 170x170x3x3]
%onnx::Conv_929[FLOAT, 171x512x1x1]
%onnx::Conv_932[FLOAT, 171x171x3x3]
%onnx::Conv_935[FLOAT, 171x171x1x1]
%onnx::Conv_938[FLOAT, 171x171x3x3]
%onnx::Conv_941[FLOAT, 170x170x3x3]
) {
%onnx::Conv_942 = Identity(%onnx::Conv_912)
%onnx::Conv_939 = Identity(%onnx::Conv_900)
%onnx::Conv_936 = Identity(%onnx::Conv_900)
%onnx::Conv_933 = Identity(%onnx::Conv_900)
%onnx::Conv_930 = Identity(%onnx::Conv_900)
%onnx::Conv_927 = Identity(%onnx::Conv_912)
%onnx::Conv_924 = Identity(%onnx::Conv_900)
%onnx::Conv_921 = Identity(%onnx::Conv_900)
%onnx::Conv_918 = Identity(%onnx::Conv_900)
%onnx::Conv_915 = Identity(%onnx::Conv_900)
%onnx::Conv_909 = Identity(%onnx::Conv_900)
%onnx::Conv_906 = Identity(%onnx::Conv_900)
%onnx::Conv_903 = Identity(%onnx::Conv_900)
%onnx::Conv_897 = Identity(%onnx::Conv_861)
%onnx::Conv_894 = Identity(%onnx::Conv_861)
%onnx::Conv_891 = Identity(%onnx::Conv_861)
%onnx::Conv_888 = Identity(%onnx::Conv_855)
%onnx::Conv_885 = Identity(%onnx::Conv_855)
%onnx::Conv_882 = Identity(%onnx::Conv_861)
%onnx::Conv_879 = Identity(%onnx::Conv_861)
%onnx::Conv_876 = Identity(%onnx::Conv_861)
%onnx::Conv_873 = Identity(%onnx::Conv_855)
%onnx::Conv_870 = Identity(%onnx::Conv_855)
%onnx::Conv_867 = Identity(%onnx::Conv_861)
%onnx::Conv_864 = Identity(%onnx::Conv_861)
%onnx::Conv_858 = Identity(%onnx::Conv_855)
%onnx::Conv_852 = Identity(%onnx::Conv_822)
%onnx::Conv_849 = Identity(%onnx::Conv_810)
%onnx::Conv_846 = Identity(%onnx::Conv_810)
%onnx::Conv_843 = Identity(%onnx::Conv_810)
%onnx::Conv_840 = Identity(%onnx::Conv_810)
%onnx::Conv_837 = Identity(%onnx::Conv_822)
%onnx::Conv_834 = Identity(%onnx::Conv_810)
%onnx::Conv_831 = Identity(%onnx::Conv_810)
%onnx::Conv_828 = Identity(%onnx::Conv_810)
%onnx::Conv_825 = Identity(%onnx::Conv_810)
%onnx::Conv_819 = Identity(%onnx::Conv_810)
%onnx::Conv_816 = Identity(%onnx::Conv_810)
%onnx::Conv_813 = Identity(%onnx::Conv_810)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_806, %onnx::Conv_807)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_6_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_7_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Slice_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_6_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_7_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Slice_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_6_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_7_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Slice_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_1_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_7_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_1_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_7_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_1_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_7_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_6_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_7_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Slice_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_6_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_7_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Slice_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_6_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_7_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Slice_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%804 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %804
}
|
val_accuracy
| 89.89383
| 1,047,049,344
| 3,519,819
|
{'zcp_epe_nas': 101.62611728412048, 'zcp_fisher': 748.2284545898438, 'zcp_flops': 16752789504.0, 'zcp_grad_norm': 501.62890625, 'zcp_grasp': 16.7265625, 'zcp_jacov': -16.05121009523765, 'zcp_l2_norm': 688.6827392578125, 'zcp_nwot': 215.54870108672677, 'zcp_params': 3519819.0, 'zcp_plain': 0.000296290963888, 'zcp_snip': 2222.546875, 'zcp_synflow': 141.39567705218536, 'zcp_zen': 88.56440734863281, 'zcp_val_accuracy': 0.9396033883094781}
| |
NASBench101_7803
|
NASBench101
|
7803
|
04b672c9253a1514c12b6542e0b0620f
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_887[FLOAT, 128x3x3x3]
%onnx::Conv_888[FLOAT, 128]
%onnx::Conv_890[FLOAT, 64x128x1x1]
%onnx::Conv_891[FLOAT, 64]
%onnx::Conv_893[FLOAT, 64x64x1x1]
%onnx::Conv_896[FLOAT, 64x128x1x1]
%onnx::Conv_899[FLOAT, 64x64x3x3]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x64x3x3]
%onnx::Conv_908[FLOAT, 64x128x1x1]
%onnx::Conv_911[FLOAT, 64x64x1x1]
%onnx::Conv_914[FLOAT, 64x128x1x1]
%onnx::Conv_917[FLOAT, 64x64x3x3]
%onnx::Conv_920[FLOAT, 64x64x3x3]
%onnx::Conv_923[FLOAT, 64x64x3x3]
%onnx::Conv_926[FLOAT, 64x128x1x1]
%onnx::Conv_929[FLOAT, 64x64x1x1]
%onnx::Conv_932[FLOAT, 64x128x1x1]
%onnx::Conv_935[FLOAT, 64x64x3x3]
%onnx::Conv_938[FLOAT, 64x64x3x3]
%onnx::Conv_941[FLOAT, 64x64x3x3]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%onnx::Conv_953[FLOAT, 128x128x3x3]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x128x3x3]
%onnx::Conv_962[FLOAT, 128x256x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x256x1x1]
%onnx::Conv_971[FLOAT, 128x128x3x3]
%onnx::Conv_974[FLOAT, 128x128x3x3]
%onnx::Conv_977[FLOAT, 128x128x3x3]
%onnx::Conv_980[FLOAT, 128x256x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x256x1x1]
%onnx::Conv_989[FLOAT, 128x128x3x3]
%onnx::Conv_992[FLOAT, 128x128x3x3]
%onnx::Conv_995[FLOAT, 128x128x3x3]
%onnx::Conv_998[FLOAT, 256x256x1x1]
%onnx::Conv_999[FLOAT, 256]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 256x256x1x1]
%onnx::Conv_1007[FLOAT, 256x256x3x3]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x256x3x3]
%onnx::Conv_1016[FLOAT, 256x512x1x1]
%onnx::Conv_1019[FLOAT, 256x256x1x1]
%onnx::Conv_1022[FLOAT, 256x512x1x1]
%onnx::Conv_1025[FLOAT, 256x256x3x3]
%onnx::Conv_1028[FLOAT, 256x256x3x3]
%onnx::Conv_1031[FLOAT, 256x256x3x3]
%onnx::Conv_1034[FLOAT, 256x512x1x1]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 256x512x1x1]
%onnx::Conv_1043[FLOAT, 256x256x3x3]
%onnx::Conv_1046[FLOAT, 256x256x3x3]
%onnx::Conv_1049[FLOAT, 256x256x3x3]
) {
%onnx::Conv_1050 = Identity(%onnx::Conv_999)
%onnx::Conv_1047 = Identity(%onnx::Conv_999)
%onnx::Conv_1044 = Identity(%onnx::Conv_999)
%onnx::Conv_1041 = Identity(%onnx::Conv_999)
%onnx::Conv_1038 = Identity(%onnx::Conv_999)
%onnx::Conv_1035 = Identity(%onnx::Conv_999)
%onnx::Conv_1032 = Identity(%onnx::Conv_999)
%onnx::Conv_1029 = Identity(%onnx::Conv_999)
%onnx::Conv_1026 = Identity(%onnx::Conv_999)
%onnx::Conv_1023 = Identity(%onnx::Conv_999)
%onnx::Conv_1020 = Identity(%onnx::Conv_999)
%onnx::Conv_1017 = Identity(%onnx::Conv_999)
%onnx::Conv_1014 = Identity(%onnx::Conv_999)
%onnx::Conv_1011 = Identity(%onnx::Conv_999)
%onnx::Conv_1008 = Identity(%onnx::Conv_999)
%onnx::Conv_1005 = Identity(%onnx::Conv_999)
%onnx::Conv_1002 = Identity(%onnx::Conv_999)
%onnx::Conv_996 = Identity(%onnx::Conv_888)
%onnx::Conv_993 = Identity(%onnx::Conv_888)
%onnx::Conv_990 = Identity(%onnx::Conv_888)
%onnx::Conv_987 = Identity(%onnx::Conv_888)
%onnx::Conv_984 = Identity(%onnx::Conv_888)
%onnx::Conv_981 = Identity(%onnx::Conv_888)
%onnx::Conv_978 = Identity(%onnx::Conv_888)
%onnx::Conv_975 = Identity(%onnx::Conv_888)
%onnx::Conv_972 = Identity(%onnx::Conv_888)
%onnx::Conv_969 = Identity(%onnx::Conv_888)
%onnx::Conv_966 = Identity(%onnx::Conv_888)
%onnx::Conv_963 = Identity(%onnx::Conv_888)
%onnx::Conv_960 = Identity(%onnx::Conv_888)
%onnx::Conv_957 = Identity(%onnx::Conv_888)
%onnx::Conv_954 = Identity(%onnx::Conv_888)
%onnx::Conv_951 = Identity(%onnx::Conv_888)
%onnx::Conv_948 = Identity(%onnx::Conv_888)
%onnx::Conv_945 = Identity(%onnx::Conv_888)
%onnx::Conv_942 = Identity(%onnx::Conv_891)
%onnx::Conv_939 = Identity(%onnx::Conv_891)
%onnx::Conv_936 = Identity(%onnx::Conv_891)
%onnx::Conv_933 = Identity(%onnx::Conv_891)
%onnx::Conv_930 = Identity(%onnx::Conv_891)
%onnx::Conv_927 = Identity(%onnx::Conv_891)
%onnx::Conv_924 = Identity(%onnx::Conv_891)
%onnx::Conv_921 = Identity(%onnx::Conv_891)
%onnx::Conv_918 = Identity(%onnx::Conv_891)
%onnx::Conv_915 = Identity(%onnx::Conv_891)
%onnx::Conv_912 = Identity(%onnx::Conv_891)
%onnx::Conv_909 = Identity(%onnx::Conv_891)
%onnx::Conv_906 = Identity(%onnx::Conv_891)
%onnx::Conv_903 = Identity(%onnx::Conv_891)
%onnx::Conv_900 = Identity(%onnx::Conv_891)
%onnx::Conv_897 = Identity(%onnx::Conv_891)
%onnx::Conv_894 = Identity(%onnx::Conv_891)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_887, %onnx::Conv_888)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%885 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %885
}
|
val_accuracy
| 91.676682
| 2,407,016,448
| 8,118,666
|
{'zcp_epe_nas': 104.60400632236203, 'zcp_fisher': 212.70118713378906, 'zcp_flops': 38512263168.0, 'zcp_grad_norm': 288.38653564453125, 'zcp_grasp': -237.8779296875, 'zcp_jacov': -16.056630566852327, 'zcp_l2_norm': 994.1347045898438, 'zcp_nwot': 224.41150824290324, 'zcp_params': 8118666.0, 'zcp_plain': 0.173381149768829, 'zcp_snip': 1664.157470703125, 'zcp_synflow': 149.88942450886506, 'zcp_zen': 108.27470397949219, 'zcp_val_accuracy': 0.9054487347602841}
| |
NASBench101_339633
|
NASBench101
|
339633
|
cd5e9bb0aa3da92c60ba2fbdb0a0e291
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_812[FLOAT, 128x3x3x3]
%onnx::Conv_813[FLOAT, 128]
%onnx::Conv_815[FLOAT, 43x128x1x1]
%onnx::Conv_816[FLOAT, 43]
%onnx::Conv_818[FLOAT, 43x43x3x3]
%onnx::Conv_821[FLOAT, 42x42x3x3]
%onnx::Conv_822[FLOAT, 42]
%onnx::Conv_824[FLOAT, 42x128x1x1]
%onnx::Conv_827[FLOAT, 42x42x1x1]
%onnx::Conv_830[FLOAT, 43x128x1x1]
%onnx::Conv_833[FLOAT, 43x43x3x3]
%onnx::Conv_836[FLOAT, 42x42x3x3]
%onnx::Conv_839[FLOAT, 42x128x1x1]
%onnx::Conv_842[FLOAT, 42x42x1x1]
%onnx::Conv_845[FLOAT, 43x128x1x1]
%onnx::Conv_848[FLOAT, 43x43x3x3]
%onnx::Conv_851[FLOAT, 42x42x3x3]
%onnx::Conv_854[FLOAT, 42x128x1x1]
%onnx::Conv_857[FLOAT, 42x42x1x1]
%onnx::Conv_860[FLOAT, 86x128x1x1]
%onnx::Conv_861[FLOAT, 86]
%onnx::Conv_863[FLOAT, 86x86x3x3]
%onnx::Conv_866[FLOAT, 85x85x3x3]
%onnx::Conv_867[FLOAT, 85]
%onnx::Conv_869[FLOAT, 85x128x1x1]
%onnx::Conv_872[FLOAT, 85x85x1x1]
%onnx::Conv_875[FLOAT, 86x256x1x1]
%onnx::Conv_878[FLOAT, 86x86x3x3]
%onnx::Conv_881[FLOAT, 85x85x3x3]
%onnx::Conv_884[FLOAT, 85x256x1x1]
%onnx::Conv_887[FLOAT, 85x85x1x1]
%onnx::Conv_890[FLOAT, 86x256x1x1]
%onnx::Conv_893[FLOAT, 86x86x3x3]
%onnx::Conv_896[FLOAT, 85x85x3x3]
%onnx::Conv_899[FLOAT, 85x256x1x1]
%onnx::Conv_902[FLOAT, 85x85x1x1]
%onnx::Conv_905[FLOAT, 171x256x1x1]
%onnx::Conv_906[FLOAT, 171]
%onnx::Conv_908[FLOAT, 171x171x3x3]
%onnx::Conv_911[FLOAT, 170x170x3x3]
%onnx::Conv_912[FLOAT, 170]
%onnx::Conv_914[FLOAT, 170x256x1x1]
%onnx::Conv_917[FLOAT, 170x170x1x1]
%onnx::Conv_920[FLOAT, 171x512x1x1]
%onnx::Conv_923[FLOAT, 171x171x3x3]
%onnx::Conv_926[FLOAT, 170x170x3x3]
%onnx::Conv_929[FLOAT, 170x512x1x1]
%onnx::Conv_932[FLOAT, 170x170x1x1]
%onnx::Conv_935[FLOAT, 171x512x1x1]
%onnx::Conv_938[FLOAT, 171x171x3x3]
%onnx::Conv_941[FLOAT, 170x170x3x3]
%onnx::Conv_944[FLOAT, 170x512x1x1]
%onnx::Conv_947[FLOAT, 170x170x1x1]
) {
%onnx::Conv_948 = Identity(%onnx::Conv_912)
%onnx::Conv_945 = Identity(%onnx::Conv_912)
%onnx::Conv_942 = Identity(%onnx::Conv_912)
%onnx::Conv_939 = Identity(%onnx::Conv_906)
%onnx::Conv_936 = Identity(%onnx::Conv_906)
%onnx::Conv_933 = Identity(%onnx::Conv_912)
%onnx::Conv_930 = Identity(%onnx::Conv_912)
%onnx::Conv_927 = Identity(%onnx::Conv_912)
%onnx::Conv_924 = Identity(%onnx::Conv_906)
%onnx::Conv_921 = Identity(%onnx::Conv_906)
%onnx::Conv_918 = Identity(%onnx::Conv_912)
%onnx::Conv_915 = Identity(%onnx::Conv_912)
%onnx::Conv_909 = Identity(%onnx::Conv_906)
%onnx::Conv_903 = Identity(%onnx::Conv_867)
%onnx::Conv_900 = Identity(%onnx::Conv_867)
%onnx::Conv_897 = Identity(%onnx::Conv_867)
%onnx::Conv_894 = Identity(%onnx::Conv_861)
%onnx::Conv_891 = Identity(%onnx::Conv_861)
%onnx::Conv_888 = Identity(%onnx::Conv_867)
%onnx::Conv_885 = Identity(%onnx::Conv_867)
%onnx::Conv_882 = Identity(%onnx::Conv_867)
%onnx::Conv_879 = Identity(%onnx::Conv_861)
%onnx::Conv_876 = Identity(%onnx::Conv_861)
%onnx::Conv_873 = Identity(%onnx::Conv_867)
%onnx::Conv_870 = Identity(%onnx::Conv_867)
%onnx::Conv_864 = Identity(%onnx::Conv_861)
%onnx::Conv_858 = Identity(%onnx::Conv_822)
%onnx::Conv_855 = Identity(%onnx::Conv_822)
%onnx::Conv_852 = Identity(%onnx::Conv_822)
%onnx::Conv_849 = Identity(%onnx::Conv_816)
%onnx::Conv_846 = Identity(%onnx::Conv_816)
%onnx::Conv_843 = Identity(%onnx::Conv_822)
%onnx::Conv_840 = Identity(%onnx::Conv_822)
%onnx::Conv_837 = Identity(%onnx::Conv_822)
%onnx::Conv_834 = Identity(%onnx::Conv_816)
%onnx::Conv_831 = Identity(%onnx::Conv_816)
%onnx::Conv_828 = Identity(%onnx::Conv_822)
%onnx::Conv_825 = Identity(%onnx::Conv_822)
%onnx::Conv_819 = Identity(%onnx::Conv_816)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_812, %onnx::Conv_813)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_1_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_5_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_6_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_1_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_5_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_6_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_1_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_5_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_6_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_1_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Slice_output_0)
%/layers.5/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_1_output_0 = Slice(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_6_output_0, %/layers.5/Constant_7_output_0, %/layers.5/Constant_5_output_0, %/layers.5/Constant_8_output_0)
%/layers.5/Constant_9_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/Slice_1_output_0, %/layers.5/Constant_9_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_10_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_1_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Slice_output_0)
%/layers.6/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_1_output_0 = Slice(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_6_output_0, %/layers.6/Constant_7_output_0, %/layers.6/Constant_5_output_0, %/layers.6/Constant_8_output_0)
%/layers.6/Constant_9_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/Slice_1_output_0, %/layers.6/Constant_9_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_10_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_1_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Slice_output_0)
%/layers.7/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_1_output_0 = Slice(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_6_output_0, %/layers.7/Constant_7_output_0, %/layers.7/Constant_5_output_0, %/layers.7/Constant_8_output_0)
%/layers.7/Constant_9_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/Slice_1_output_0, %/layers.7/Constant_9_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_10_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_1_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_5_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_6_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_1_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_5_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_6_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_1_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_5_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_6_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%810 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %810
}
|
val_accuracy
| 90.614986
| 831,902,080
| 2,772,140
|
{'zcp_epe_nas': 90.18757024972379, 'zcp_fisher': 8.127219200134277, 'zcp_flops': 13310433280.0, 'zcp_grad_norm': 57.80967712402344, 'zcp_grasp': 0.688995361328125, 'zcp_jacov': -16.06168621696979, 'zcp_l2_norm': 761.1338500976562, 'zcp_nwot': 215.49853197558488, 'zcp_params': 2772140.0, 'zcp_plain': -0.0040116603486230005, 'zcp_snip': 300.481201171875, 'zcp_synflow': 109.5320478618118, 'zcp_zen': 81.589111328125, 'zcp_val_accuracy': 0.9229767918586731}
| |
NASBench101_231808
|
NASBench101
|
231808
|
8c5d017bd056146d922f8b540cda277c
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_572[FLOAT, 128x3x3x3]
%onnx::Conv_573[FLOAT, 128]
%onnx::Conv_575[FLOAT, 32x128x1x1]
%onnx::Conv_576[FLOAT, 32]
%onnx::Conv_578[FLOAT, 32x32x1x1]
%onnx::Conv_581[FLOAT, 32x32x1x1]
%onnx::Conv_584[FLOAT, 32x128x1x1]
%onnx::Conv_587[FLOAT, 32x32x1x1]
%onnx::Conv_590[FLOAT, 32x32x1x1]
%onnx::Conv_593[FLOAT, 32x128x1x1]
%onnx::Conv_596[FLOAT, 32x32x1x1]
%onnx::Conv_599[FLOAT, 32x32x1x1]
%onnx::Conv_602[FLOAT, 64x128x1x1]
%onnx::Conv_603[FLOAT, 64]
%onnx::Conv_605[FLOAT, 64x64x1x1]
%onnx::Conv_608[FLOAT, 64x64x1x1]
%onnx::Conv_611[FLOAT, 64x256x1x1]
%onnx::Conv_614[FLOAT, 64x64x1x1]
%onnx::Conv_617[FLOAT, 64x64x1x1]
%onnx::Conv_620[FLOAT, 64x256x1x1]
%onnx::Conv_623[FLOAT, 64x64x1x1]
%onnx::Conv_626[FLOAT, 64x64x1x1]
%onnx::Conv_629[FLOAT, 128x256x1x1]
%onnx::Conv_632[FLOAT, 128x128x1x1]
%onnx::Conv_635[FLOAT, 128x128x1x1]
%onnx::Conv_638[FLOAT, 128x512x1x1]
%onnx::Conv_641[FLOAT, 128x128x1x1]
%onnx::Conv_644[FLOAT, 128x128x1x1]
%onnx::Conv_647[FLOAT, 128x512x1x1]
%onnx::Conv_650[FLOAT, 128x128x1x1]
%onnx::Conv_653[FLOAT, 128x128x1x1]
) {
%onnx::Conv_654 = Identity(%onnx::Conv_573)
%onnx::Conv_651 = Identity(%onnx::Conv_573)
%onnx::Conv_648 = Identity(%onnx::Conv_573)
%onnx::Conv_645 = Identity(%onnx::Conv_573)
%onnx::Conv_642 = Identity(%onnx::Conv_573)
%onnx::Conv_639 = Identity(%onnx::Conv_573)
%onnx::Conv_636 = Identity(%onnx::Conv_573)
%onnx::Conv_633 = Identity(%onnx::Conv_573)
%onnx::Conv_630 = Identity(%onnx::Conv_573)
%onnx::Conv_627 = Identity(%onnx::Conv_603)
%onnx::Conv_624 = Identity(%onnx::Conv_603)
%onnx::Conv_621 = Identity(%onnx::Conv_603)
%onnx::Conv_618 = Identity(%onnx::Conv_603)
%onnx::Conv_615 = Identity(%onnx::Conv_603)
%onnx::Conv_612 = Identity(%onnx::Conv_603)
%onnx::Conv_609 = Identity(%onnx::Conv_603)
%onnx::Conv_606 = Identity(%onnx::Conv_603)
%onnx::Conv_600 = Identity(%onnx::Conv_576)
%onnx::Conv_597 = Identity(%onnx::Conv_576)
%onnx::Conv_594 = Identity(%onnx::Conv_576)
%onnx::Conv_591 = Identity(%onnx::Conv_576)
%onnx::Conv_588 = Identity(%onnx::Conv_576)
%onnx::Conv_585 = Identity(%onnx::Conv_576)
%onnx::Conv_582 = Identity(%onnx::Conv_576)
%onnx::Conv_579 = Identity(%onnx::Conv_576)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_572, %onnx::Conv_573)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_575, %onnx::Conv_576)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_578, %onnx::Conv_579)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_581, %onnx::Conv_582)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_584, %onnx::Conv_585)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_587, %onnx::Conv_588)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_590, %onnx::Conv_591)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_593, %onnx::Conv_594)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_596, %onnx::Conv_597)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_599, %onnx::Conv_600)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_602, %onnx::Conv_603)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_605, %onnx::Conv_606)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_608, %onnx::Conv_609)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_611, %onnx::Conv_612)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_614, %onnx::Conv_615)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_617, %onnx::Conv_618)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_620, %onnx::Conv_621)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_623, %onnx::Conv_624)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_626, %onnx::Conv_627)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_629, %onnx::Conv_630)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_632, %onnx::Conv_633)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_635, %onnx::Conv_636)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_638, %onnx::Conv_639)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_641, %onnx::Conv_642)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_644, %onnx::Conv_645)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_647, %onnx::Conv_648)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_650, %onnx::Conv_651)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_653, %onnx::Conv_654)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%570 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %570
}
|
val_accuracy
| 85.687101
| 117,123,072
| 358,986
|
{'zcp_epe_nas': 69.9521353768917, 'zcp_fisher': 8.762478828430176, 'zcp_flops': 1873969152.0, 'zcp_grad_norm': 67.53434753417969, 'zcp_grasp': 5.0125732421875, 'zcp_jacov': -16.051293763428827, 'zcp_l2_norm': 410.1748046875, 'zcp_nwot': 205.11385837412053, 'zcp_params': 358986.0, 'zcp_plain': 0.053829606622457005, 'zcp_snip': 215.72669982910156, 'zcp_synflow': 67.52926436800124, 'zcp_zen': 37.370391845703125, 'zcp_val_accuracy': 0.916766822338104}
| |
NASBench101_420323
|
NASBench101
|
420323
|
fdfffd48f14fff1464952c3ad92ba166
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_968[FLOAT, 128x3x3x3]
%onnx::Conv_969[FLOAT, 128]
%onnx::Conv_971[FLOAT, 64x128x1x1]
%onnx::Conv_972[FLOAT, 64]
%onnx::Conv_974[FLOAT, 64x64x1x1]
%onnx::Conv_977[FLOAT, 64x128x1x1]
%onnx::Conv_980[FLOAT, 64x64x1x1]
%onnx::Conv_983[FLOAT, 64x64x3x3]
%onnx::Conv_986[FLOAT, 64x64x1x1]
%onnx::Conv_989[FLOAT, 64x64x1x1]
%onnx::Conv_992[FLOAT, 64x128x1x1]
%onnx::Conv_995[FLOAT, 64x64x1x1]
%onnx::Conv_998[FLOAT, 64x128x1x1]
%onnx::Conv_1001[FLOAT, 64x64x1x1]
%onnx::Conv_1004[FLOAT, 64x64x3x3]
%onnx::Conv_1007[FLOAT, 64x64x1x1]
%onnx::Conv_1010[FLOAT, 64x64x1x1]
%onnx::Conv_1013[FLOAT, 64x128x1x1]
%onnx::Conv_1016[FLOAT, 64x64x1x1]
%onnx::Conv_1019[FLOAT, 64x128x1x1]
%onnx::Conv_1022[FLOAT, 64x64x1x1]
%onnx::Conv_1025[FLOAT, 64x64x3x3]
%onnx::Conv_1028[FLOAT, 64x64x1x1]
%onnx::Conv_1031[FLOAT, 64x64x1x1]
%onnx::Conv_1034[FLOAT, 128x128x1x1]
%onnx::Conv_1037[FLOAT, 128x128x1x1]
%onnx::Conv_1040[FLOAT, 128x128x1x1]
%onnx::Conv_1043[FLOAT, 128x128x1x1]
%onnx::Conv_1046[FLOAT, 128x128x3x3]
%onnx::Conv_1049[FLOAT, 128x128x1x1]
%onnx::Conv_1052[FLOAT, 128x128x1x1]
%onnx::Conv_1055[FLOAT, 128x256x1x1]
%onnx::Conv_1058[FLOAT, 128x128x1x1]
%onnx::Conv_1061[FLOAT, 128x256x1x1]
%onnx::Conv_1064[FLOAT, 128x128x1x1]
%onnx::Conv_1067[FLOAT, 128x128x3x3]
%onnx::Conv_1070[FLOAT, 128x128x1x1]
%onnx::Conv_1073[FLOAT, 128x128x1x1]
%onnx::Conv_1076[FLOAT, 128x256x1x1]
%onnx::Conv_1079[FLOAT, 128x128x1x1]
%onnx::Conv_1082[FLOAT, 128x256x1x1]
%onnx::Conv_1085[FLOAT, 128x128x1x1]
%onnx::Conv_1088[FLOAT, 128x128x3x3]
%onnx::Conv_1091[FLOAT, 128x128x1x1]
%onnx::Conv_1094[FLOAT, 128x128x1x1]
%onnx::Conv_1097[FLOAT, 256x256x1x1]
%onnx::Conv_1098[FLOAT, 256]
%onnx::Conv_1100[FLOAT, 256x256x1x1]
%onnx::Conv_1103[FLOAT, 256x256x1x1]
%onnx::Conv_1106[FLOAT, 256x256x1x1]
%onnx::Conv_1109[FLOAT, 256x256x3x3]
%onnx::Conv_1112[FLOAT, 256x256x1x1]
%onnx::Conv_1115[FLOAT, 256x256x1x1]
%onnx::Conv_1118[FLOAT, 256x512x1x1]
%onnx::Conv_1121[FLOAT, 256x256x1x1]
%onnx::Conv_1124[FLOAT, 256x512x1x1]
%onnx::Conv_1127[FLOAT, 256x256x1x1]
%onnx::Conv_1130[FLOAT, 256x256x3x3]
%onnx::Conv_1133[FLOAT, 256x256x1x1]
%onnx::Conv_1136[FLOAT, 256x256x1x1]
%onnx::Conv_1139[FLOAT, 256x512x1x1]
%onnx::Conv_1142[FLOAT, 256x256x1x1]
%onnx::Conv_1145[FLOAT, 256x512x1x1]
%onnx::Conv_1148[FLOAT, 256x256x1x1]
%onnx::Conv_1151[FLOAT, 256x256x3x3]
%onnx::Conv_1154[FLOAT, 256x256x1x1]
%onnx::Conv_1157[FLOAT, 256x256x1x1]
) {
%onnx::Conv_1158 = Identity(%onnx::Conv_1098)
%onnx::Conv_1155 = Identity(%onnx::Conv_1098)
%onnx::Conv_1152 = Identity(%onnx::Conv_1098)
%onnx::Conv_1149 = Identity(%onnx::Conv_1098)
%onnx::Conv_1146 = Identity(%onnx::Conv_1098)
%onnx::Conv_1143 = Identity(%onnx::Conv_1098)
%onnx::Conv_1140 = Identity(%onnx::Conv_1098)
%onnx::Conv_1137 = Identity(%onnx::Conv_1098)
%onnx::Conv_1134 = Identity(%onnx::Conv_1098)
%onnx::Conv_1131 = Identity(%onnx::Conv_1098)
%onnx::Conv_1128 = Identity(%onnx::Conv_1098)
%onnx::Conv_1125 = Identity(%onnx::Conv_1098)
%onnx::Conv_1122 = Identity(%onnx::Conv_1098)
%onnx::Conv_1119 = Identity(%onnx::Conv_1098)
%onnx::Conv_1116 = Identity(%onnx::Conv_1098)
%onnx::Conv_1113 = Identity(%onnx::Conv_1098)
%onnx::Conv_1110 = Identity(%onnx::Conv_1098)
%onnx::Conv_1107 = Identity(%onnx::Conv_1098)
%onnx::Conv_1104 = Identity(%onnx::Conv_1098)
%onnx::Conv_1101 = Identity(%onnx::Conv_1098)
%onnx::Conv_1095 = Identity(%onnx::Conv_969)
%onnx::Conv_1092 = Identity(%onnx::Conv_969)
%onnx::Conv_1089 = Identity(%onnx::Conv_969)
%onnx::Conv_1086 = Identity(%onnx::Conv_969)
%onnx::Conv_1083 = Identity(%onnx::Conv_969)
%onnx::Conv_1080 = Identity(%onnx::Conv_969)
%onnx::Conv_1077 = Identity(%onnx::Conv_969)
%onnx::Conv_1074 = Identity(%onnx::Conv_969)
%onnx::Conv_1071 = Identity(%onnx::Conv_969)
%onnx::Conv_1068 = Identity(%onnx::Conv_969)
%onnx::Conv_1065 = Identity(%onnx::Conv_969)
%onnx::Conv_1062 = Identity(%onnx::Conv_969)
%onnx::Conv_1059 = Identity(%onnx::Conv_969)
%onnx::Conv_1056 = Identity(%onnx::Conv_969)
%onnx::Conv_1053 = Identity(%onnx::Conv_969)
%onnx::Conv_1050 = Identity(%onnx::Conv_969)
%onnx::Conv_1047 = Identity(%onnx::Conv_969)
%onnx::Conv_1044 = Identity(%onnx::Conv_969)
%onnx::Conv_1041 = Identity(%onnx::Conv_969)
%onnx::Conv_1038 = Identity(%onnx::Conv_969)
%onnx::Conv_1035 = Identity(%onnx::Conv_969)
%onnx::Conv_1032 = Identity(%onnx::Conv_972)
%onnx::Conv_1029 = Identity(%onnx::Conv_972)
%onnx::Conv_1026 = Identity(%onnx::Conv_972)
%onnx::Conv_1023 = Identity(%onnx::Conv_972)
%onnx::Conv_1020 = Identity(%onnx::Conv_972)
%onnx::Conv_1017 = Identity(%onnx::Conv_972)
%onnx::Conv_1014 = Identity(%onnx::Conv_972)
%onnx::Conv_1011 = Identity(%onnx::Conv_972)
%onnx::Conv_1008 = Identity(%onnx::Conv_972)
%onnx::Conv_1005 = Identity(%onnx::Conv_972)
%onnx::Conv_1002 = Identity(%onnx::Conv_972)
%onnx::Conv_999 = Identity(%onnx::Conv_972)
%onnx::Conv_996 = Identity(%onnx::Conv_972)
%onnx::Conv_993 = Identity(%onnx::Conv_972)
%onnx::Conv_990 = Identity(%onnx::Conv_972)
%onnx::Conv_987 = Identity(%onnx::Conv_972)
%onnx::Conv_984 = Identity(%onnx::Conv_972)
%onnx::Conv_981 = Identity(%onnx::Conv_972)
%onnx::Conv_978 = Identity(%onnx::Conv_972)
%onnx::Conv_975 = Identity(%onnx::Conv_972)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_968, %onnx::Conv_969)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%966 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %966
}
|
val_accuracy
| 91.125804
| 1,277,306,880
| 4,250,634
|
{'zcp_epe_nas': 119.75200155898683, 'zcp_fisher': 299.7142028808594, 'zcp_flops': 20436910080.0, 'zcp_grad_norm': 363.4896545410156, 'zcp_grasp': 5089.76953125, 'zcp_jacov': -16.054561711161284, 'zcp_l2_norm': 1144.484619140625, 'zcp_nwot': 227.27956981572044, 'zcp_params': 4250634.0, 'zcp_plain': 0.06800544261932301, 'zcp_snip': 1872.3472900390625, 'zcp_synflow': 153.89527815163683, 'zcp_zen': 95.00923156738281, 'zcp_val_accuracy': 0.8939303159713741}
| |
NASBench101_414868
|
NASBench101
|
414868
|
fab3cb009c08807465b1ece6f23f120d
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_725[FLOAT, 128x3x3x3]
%onnx::Conv_726[FLOAT, 128]
%onnx::Conv_728[FLOAT, 64x128x1x1]
%onnx::Conv_729[FLOAT, 64]
%onnx::Conv_731[FLOAT, 64x64x3x3]
%onnx::Conv_734[FLOAT, 64x64x3x3]
%onnx::Conv_737[FLOAT, 64x128x1x1]
%onnx::Conv_740[FLOAT, 64x64x3x3]
%onnx::Conv_743[FLOAT, 64x128x1x1]
%onnx::Conv_746[FLOAT, 64x64x3x3]
%onnx::Conv_749[FLOAT, 64x64x3x3]
%onnx::Conv_752[FLOAT, 64x128x1x1]
%onnx::Conv_755[FLOAT, 64x64x3x3]
%onnx::Conv_758[FLOAT, 64x128x1x1]
%onnx::Conv_761[FLOAT, 64x64x3x3]
%onnx::Conv_764[FLOAT, 64x64x3x3]
%onnx::Conv_767[FLOAT, 64x128x1x1]
%onnx::Conv_770[FLOAT, 64x64x3x3]
%onnx::Conv_773[FLOAT, 128x128x1x1]
%onnx::Conv_776[FLOAT, 128x128x3x3]
%onnx::Conv_779[FLOAT, 128x128x3x3]
%onnx::Conv_782[FLOAT, 128x128x1x1]
%onnx::Conv_785[FLOAT, 128x128x3x3]
%onnx::Conv_788[FLOAT, 128x256x1x1]
%onnx::Conv_791[FLOAT, 128x128x3x3]
%onnx::Conv_794[FLOAT, 128x128x3x3]
%onnx::Conv_797[FLOAT, 128x256x1x1]
%onnx::Conv_800[FLOAT, 128x128x3x3]
%onnx::Conv_803[FLOAT, 128x256x1x1]
%onnx::Conv_806[FLOAT, 128x128x3x3]
%onnx::Conv_809[FLOAT, 128x128x3x3]
%onnx::Conv_812[FLOAT, 128x256x1x1]
%onnx::Conv_815[FLOAT, 128x128x3x3]
%onnx::Conv_818[FLOAT, 256x256x1x1]
%onnx::Conv_819[FLOAT, 256]
%onnx::Conv_821[FLOAT, 256x256x3x3]
%onnx::Conv_824[FLOAT, 256x256x3x3]
%onnx::Conv_827[FLOAT, 256x256x1x1]
%onnx::Conv_830[FLOAT, 256x256x3x3]
%onnx::Conv_833[FLOAT, 256x512x1x1]
%onnx::Conv_836[FLOAT, 256x256x3x3]
%onnx::Conv_839[FLOAT, 256x256x3x3]
%onnx::Conv_842[FLOAT, 256x512x1x1]
%onnx::Conv_845[FLOAT, 256x256x3x3]
%onnx::Conv_848[FLOAT, 256x512x1x1]
%onnx::Conv_851[FLOAT, 256x256x3x3]
%onnx::Conv_854[FLOAT, 256x256x3x3]
%onnx::Conv_857[FLOAT, 256x512x1x1]
%onnx::Conv_860[FLOAT, 256x256x3x3]
) {
%onnx::Conv_861 = Identity(%onnx::Conv_819)
%onnx::Conv_858 = Identity(%onnx::Conv_819)
%onnx::Conv_855 = Identity(%onnx::Conv_819)
%onnx::Conv_852 = Identity(%onnx::Conv_819)
%onnx::Conv_849 = Identity(%onnx::Conv_819)
%onnx::Conv_846 = Identity(%onnx::Conv_819)
%onnx::Conv_843 = Identity(%onnx::Conv_819)
%onnx::Conv_840 = Identity(%onnx::Conv_819)
%onnx::Conv_837 = Identity(%onnx::Conv_819)
%onnx::Conv_834 = Identity(%onnx::Conv_819)
%onnx::Conv_831 = Identity(%onnx::Conv_819)
%onnx::Conv_828 = Identity(%onnx::Conv_819)
%onnx::Conv_825 = Identity(%onnx::Conv_819)
%onnx::Conv_822 = Identity(%onnx::Conv_819)
%onnx::Conv_816 = Identity(%onnx::Conv_726)
%onnx::Conv_813 = Identity(%onnx::Conv_726)
%onnx::Conv_810 = Identity(%onnx::Conv_726)
%onnx::Conv_807 = Identity(%onnx::Conv_726)
%onnx::Conv_804 = Identity(%onnx::Conv_726)
%onnx::Conv_801 = Identity(%onnx::Conv_726)
%onnx::Conv_798 = Identity(%onnx::Conv_726)
%onnx::Conv_795 = Identity(%onnx::Conv_726)
%onnx::Conv_792 = Identity(%onnx::Conv_726)
%onnx::Conv_789 = Identity(%onnx::Conv_726)
%onnx::Conv_786 = Identity(%onnx::Conv_726)
%onnx::Conv_783 = Identity(%onnx::Conv_726)
%onnx::Conv_780 = Identity(%onnx::Conv_726)
%onnx::Conv_777 = Identity(%onnx::Conv_726)
%onnx::Conv_774 = Identity(%onnx::Conv_726)
%onnx::Conv_771 = Identity(%onnx::Conv_729)
%onnx::Conv_768 = Identity(%onnx::Conv_729)
%onnx::Conv_765 = Identity(%onnx::Conv_729)
%onnx::Conv_762 = Identity(%onnx::Conv_729)
%onnx::Conv_759 = Identity(%onnx::Conv_729)
%onnx::Conv_756 = Identity(%onnx::Conv_729)
%onnx::Conv_753 = Identity(%onnx::Conv_729)
%onnx::Conv_750 = Identity(%onnx::Conv_729)
%onnx::Conv_747 = Identity(%onnx::Conv_729)
%onnx::Conv_744 = Identity(%onnx::Conv_729)
%onnx::Conv_741 = Identity(%onnx::Conv_729)
%onnx::Conv_738 = Identity(%onnx::Conv_729)
%onnx::Conv_735 = Identity(%onnx::Conv_729)
%onnx::Conv_732 = Identity(%onnx::Conv_729)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_725, %onnx::Conv_726)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%723 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %723
}
|
val_accuracy
| 93.379408
| 2,328,766,464
| 7,857,930
|
{'zcp_epe_nas': 91.52145089181838, 'zcp_fisher': 24.48984718322754, 'zcp_flops': 37260263424.0, 'zcp_grad_norm': 98.47154998779297, 'zcp_grasp': 1.3702392578125, 'zcp_jacov': -16.04279032746293, 'zcp_l2_norm': 844.8289794921875, 'zcp_nwot': 221.23983603567555, 'zcp_params': 7857930.0, 'zcp_plain': 0.00559096969664, 'zcp_snip': 586.2754516601562, 'zcp_synflow': 126.90273039009045, 'zcp_zen': 94.42655944824219, 'zcp_val_accuracy': 0.8488581776618951}
| |
NASBench101_266928
|
NASBench101
|
266928
|
a1a336151bb7095f71e9f242e104ec6f
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_821[FLOAT, 128x3x3x3]
%onnx::Conv_822[FLOAT, 128]
%onnx::Conv_824[FLOAT, 43x128x1x1]
%onnx::Conv_825[FLOAT, 43]
%onnx::Conv_827[FLOAT, 43x43x3x3]
%onnx::Conv_830[FLOAT, 43x43x3x3]
%onnx::Conv_833[FLOAT, 43x43x1x1]
%onnx::Conv_836[FLOAT, 42x42x3x3]
%onnx::Conv_837[FLOAT, 42]
%onnx::Conv_839[FLOAT, 43x128x1x1]
%onnx::Conv_842[FLOAT, 43x43x3x3]
%onnx::Conv_845[FLOAT, 43x43x3x3]
%onnx::Conv_848[FLOAT, 43x43x1x1]
%onnx::Conv_851[FLOAT, 42x42x3x3]
%onnx::Conv_854[FLOAT, 43x128x1x1]
%onnx::Conv_857[FLOAT, 43x43x3x3]
%onnx::Conv_860[FLOAT, 43x43x3x3]
%onnx::Conv_863[FLOAT, 43x43x1x1]
%onnx::Conv_866[FLOAT, 42x42x3x3]
%onnx::Conv_869[FLOAT, 86x128x1x1]
%onnx::Conv_870[FLOAT, 86]
%onnx::Conv_872[FLOAT, 86x86x3x3]
%onnx::Conv_875[FLOAT, 85x85x3x3]
%onnx::Conv_876[FLOAT, 85]
%onnx::Conv_878[FLOAT, 85x85x1x1]
%onnx::Conv_881[FLOAT, 85x85x3x3]
%onnx::Conv_884[FLOAT, 86x256x1x1]
%onnx::Conv_887[FLOAT, 86x86x3x3]
%onnx::Conv_890[FLOAT, 85x85x3x3]
%onnx::Conv_893[FLOAT, 85x85x1x1]
%onnx::Conv_896[FLOAT, 85x85x3x3]
%onnx::Conv_899[FLOAT, 86x256x1x1]
%onnx::Conv_902[FLOAT, 86x86x3x3]
%onnx::Conv_905[FLOAT, 85x85x3x3]
%onnx::Conv_908[FLOAT, 85x85x1x1]
%onnx::Conv_911[FLOAT, 85x85x3x3]
%onnx::Conv_914[FLOAT, 171x256x1x1]
%onnx::Conv_915[FLOAT, 171]
%onnx::Conv_917[FLOAT, 171x171x3x3]
%onnx::Conv_920[FLOAT, 171x171x3x3]
%onnx::Conv_923[FLOAT, 171x171x1x1]
%onnx::Conv_926[FLOAT, 170x170x3x3]
%onnx::Conv_927[FLOAT, 170]
%onnx::Conv_929[FLOAT, 171x512x1x1]
%onnx::Conv_932[FLOAT, 171x171x3x3]
%onnx::Conv_935[FLOAT, 171x171x3x3]
%onnx::Conv_938[FLOAT, 171x171x1x1]
%onnx::Conv_941[FLOAT, 170x170x3x3]
%onnx::Conv_944[FLOAT, 171x512x1x1]
%onnx::Conv_947[FLOAT, 171x171x3x3]
%onnx::Conv_950[FLOAT, 171x171x3x3]
%onnx::Conv_953[FLOAT, 171x171x1x1]
%onnx::Conv_956[FLOAT, 170x170x3x3]
) {
%onnx::Conv_957 = Identity(%onnx::Conv_927)
%onnx::Conv_954 = Identity(%onnx::Conv_915)
%onnx::Conv_951 = Identity(%onnx::Conv_915)
%onnx::Conv_948 = Identity(%onnx::Conv_915)
%onnx::Conv_945 = Identity(%onnx::Conv_915)
%onnx::Conv_942 = Identity(%onnx::Conv_927)
%onnx::Conv_939 = Identity(%onnx::Conv_915)
%onnx::Conv_936 = Identity(%onnx::Conv_915)
%onnx::Conv_933 = Identity(%onnx::Conv_915)
%onnx::Conv_930 = Identity(%onnx::Conv_915)
%onnx::Conv_924 = Identity(%onnx::Conv_915)
%onnx::Conv_921 = Identity(%onnx::Conv_915)
%onnx::Conv_918 = Identity(%onnx::Conv_915)
%onnx::Conv_912 = Identity(%onnx::Conv_876)
%onnx::Conv_909 = Identity(%onnx::Conv_876)
%onnx::Conv_906 = Identity(%onnx::Conv_876)
%onnx::Conv_903 = Identity(%onnx::Conv_870)
%onnx::Conv_900 = Identity(%onnx::Conv_870)
%onnx::Conv_897 = Identity(%onnx::Conv_876)
%onnx::Conv_894 = Identity(%onnx::Conv_876)
%onnx::Conv_891 = Identity(%onnx::Conv_876)
%onnx::Conv_888 = Identity(%onnx::Conv_870)
%onnx::Conv_885 = Identity(%onnx::Conv_870)
%onnx::Conv_882 = Identity(%onnx::Conv_876)
%onnx::Conv_879 = Identity(%onnx::Conv_876)
%onnx::Conv_873 = Identity(%onnx::Conv_870)
%onnx::Conv_867 = Identity(%onnx::Conv_837)
%onnx::Conv_864 = Identity(%onnx::Conv_825)
%onnx::Conv_861 = Identity(%onnx::Conv_825)
%onnx::Conv_858 = Identity(%onnx::Conv_825)
%onnx::Conv_855 = Identity(%onnx::Conv_825)
%onnx::Conv_852 = Identity(%onnx::Conv_837)
%onnx::Conv_849 = Identity(%onnx::Conv_825)
%onnx::Conv_846 = Identity(%onnx::Conv_825)
%onnx::Conv_843 = Identity(%onnx::Conv_825)
%onnx::Conv_840 = Identity(%onnx::Conv_825)
%onnx::Conv_834 = Identity(%onnx::Conv_825)
%onnx::Conv_831 = Identity(%onnx::Conv_825)
%onnx::Conv_828 = Identity(%onnx::Conv_825)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_821, %onnx::Conv_822)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_6_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_7_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Slice_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_6_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_7_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Slice_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_6_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_7_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Slice_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_1_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_1_output_0 = Slice(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_8_output_0, %/layers.5/Constant_9_output_0, %/layers.5/Constant_7_output_0, %/layers.5/Constant_10_output_0)
%/layers.5/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/Slice_1_output_0, %/layers.5/Constant_11_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_1_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_1_output_0 = Slice(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_8_output_0, %/layers.6/Constant_9_output_0, %/layers.6/Constant_7_output_0, %/layers.6/Constant_10_output_0)
%/layers.6/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/Slice_1_output_0, %/layers.6/Constant_11_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_1_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_1_output_0 = Slice(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_8_output_0, %/layers.7/Constant_9_output_0, %/layers.7/Constant_7_output_0, %/layers.7/Constant_10_output_0)
%/layers.7/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/Slice_1_output_0, %/layers.7/Constant_11_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_6_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_7_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Slice_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_6_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_7_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Slice_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_6_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_7_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Slice_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%819 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %819
}
|
val_accuracy
| 91.646636
| 1,047,049,344
| 3,519,819
|
{'zcp_epe_nas': 121.74971774414294, 'zcp_fisher': 119.45992279052734, 'zcp_flops': 16752789504.0, 'zcp_grad_norm': 202.7003631591797, 'zcp_grasp': 186.4677734375, 'zcp_jacov': -16.060601009476265, 'zcp_l2_norm': 688.088623046875, 'zcp_nwot': 215.3972099428479, 'zcp_params': 3519819.0, 'zcp_plain': -0.014833213761448001, 'zcp_snip': 951.1583251953125, 'zcp_synflow': 122.23207065953372, 'zcp_zen': 87.23699951171875, 'zcp_val_accuracy': 0.8958333134651181}
| |
NASBench101_296168
|
NASBench101
|
296168
|
b349bc7242595b860771f17a93911520
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_752[FLOAT, 128x3x3x3]
%onnx::Conv_753[FLOAT, 128]
%onnx::Conv_755[FLOAT, 128x128x1x1]
%onnx::Conv_758[FLOAT, 128x128x1x1]
%onnx::Conv_761[FLOAT, 128x128x1x1]
%onnx::Conv_764[FLOAT, 128x128x3x3]
%onnx::Conv_767[FLOAT, 128x128x1x1]
%onnx::Conv_770[FLOAT, 128x128x1x1]
%onnx::Conv_773[FLOAT, 128x128x1x1]
%onnx::Conv_776[FLOAT, 128x128x1x1]
%onnx::Conv_779[FLOAT, 128x128x3x3]
%onnx::Conv_782[FLOAT, 128x128x1x1]
%onnx::Conv_785[FLOAT, 128x128x1x1]
%onnx::Conv_788[FLOAT, 128x128x1x1]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 128x128x3x3]
%onnx::Conv_797[FLOAT, 128x128x1x1]
%onnx::Conv_800[FLOAT, 256x128x1x1]
%onnx::Conv_801[FLOAT, 256]
%onnx::Conv_803[FLOAT, 256x256x1x1]
%onnx::Conv_806[FLOAT, 256x128x1x1]
%onnx::Conv_809[FLOAT, 256x256x3x3]
%onnx::Conv_812[FLOAT, 256x256x1x1]
%onnx::Conv_815[FLOAT, 256x256x1x1]
%onnx::Conv_818[FLOAT, 256x256x1x1]
%onnx::Conv_821[FLOAT, 256x256x1x1]
%onnx::Conv_824[FLOAT, 256x256x3x3]
%onnx::Conv_827[FLOAT, 256x256x1x1]
%onnx::Conv_830[FLOAT, 256x256x1x1]
%onnx::Conv_833[FLOAT, 256x256x1x1]
%onnx::Conv_836[FLOAT, 256x256x1x1]
%onnx::Conv_839[FLOAT, 256x256x3x3]
%onnx::Conv_842[FLOAT, 256x256x1x1]
%onnx::Conv_845[FLOAT, 512x256x1x1]
%onnx::Conv_846[FLOAT, 512]
%onnx::Conv_848[FLOAT, 512x512x1x1]
%onnx::Conv_851[FLOAT, 512x256x1x1]
%onnx::Conv_854[FLOAT, 512x512x3x3]
%onnx::Conv_857[FLOAT, 512x512x1x1]
%onnx::Conv_860[FLOAT, 512x512x1x1]
%onnx::Conv_863[FLOAT, 512x512x1x1]
%onnx::Conv_866[FLOAT, 512x512x1x1]
%onnx::Conv_869[FLOAT, 512x512x3x3]
%onnx::Conv_872[FLOAT, 512x512x1x1]
%onnx::Conv_875[FLOAT, 512x512x1x1]
%onnx::Conv_878[FLOAT, 512x512x1x1]
%onnx::Conv_881[FLOAT, 512x512x1x1]
%onnx::Conv_884[FLOAT, 512x512x3x3]
%onnx::Conv_887[FLOAT, 512x512x1x1]
) {
%onnx::Conv_888 = Identity(%onnx::Conv_846)
%onnx::Conv_885 = Identity(%onnx::Conv_846)
%onnx::Conv_882 = Identity(%onnx::Conv_846)
%onnx::Conv_879 = Identity(%onnx::Conv_846)
%onnx::Conv_876 = Identity(%onnx::Conv_846)
%onnx::Conv_873 = Identity(%onnx::Conv_846)
%onnx::Conv_870 = Identity(%onnx::Conv_846)
%onnx::Conv_867 = Identity(%onnx::Conv_846)
%onnx::Conv_864 = Identity(%onnx::Conv_846)
%onnx::Conv_861 = Identity(%onnx::Conv_846)
%onnx::Conv_858 = Identity(%onnx::Conv_846)
%onnx::Conv_855 = Identity(%onnx::Conv_846)
%onnx::Conv_852 = Identity(%onnx::Conv_846)
%onnx::Conv_849 = Identity(%onnx::Conv_846)
%onnx::Conv_843 = Identity(%onnx::Conv_801)
%onnx::Conv_840 = Identity(%onnx::Conv_801)
%onnx::Conv_837 = Identity(%onnx::Conv_801)
%onnx::Conv_834 = Identity(%onnx::Conv_801)
%onnx::Conv_831 = Identity(%onnx::Conv_801)
%onnx::Conv_828 = Identity(%onnx::Conv_801)
%onnx::Conv_825 = Identity(%onnx::Conv_801)
%onnx::Conv_822 = Identity(%onnx::Conv_801)
%onnx::Conv_819 = Identity(%onnx::Conv_801)
%onnx::Conv_816 = Identity(%onnx::Conv_801)
%onnx::Conv_813 = Identity(%onnx::Conv_801)
%onnx::Conv_810 = Identity(%onnx::Conv_801)
%onnx::Conv_807 = Identity(%onnx::Conv_801)
%onnx::Conv_804 = Identity(%onnx::Conv_801)
%onnx::Conv_798 = Identity(%onnx::Conv_753)
%onnx::Conv_795 = Identity(%onnx::Conv_753)
%onnx::Conv_792 = Identity(%onnx::Conv_753)
%onnx::Conv_789 = Identity(%onnx::Conv_753)
%onnx::Conv_786 = Identity(%onnx::Conv_753)
%onnx::Conv_783 = Identity(%onnx::Conv_753)
%onnx::Conv_780 = Identity(%onnx::Conv_753)
%onnx::Conv_777 = Identity(%onnx::Conv_753)
%onnx::Conv_774 = Identity(%onnx::Conv_753)
%onnx::Conv_771 = Identity(%onnx::Conv_753)
%onnx::Conv_768 = Identity(%onnx::Conv_753)
%onnx::Conv_765 = Identity(%onnx::Conv_753)
%onnx::Conv_762 = Identity(%onnx::Conv_753)
%onnx::Conv_759 = Identity(%onnx::Conv_753)
%onnx::Conv_756 = Identity(%onnx::Conv_753)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_752, %onnx::Conv_753)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%750 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %750
}
|
val_accuracy
| 89.953929
| 3,894,421,504
| 13,126,538
|
{'zcp_epe_nas': 119.30637240372623, 'zcp_fisher': 211.54812622070312, 'zcp_flops': 62310744064.0, 'zcp_grad_norm': 212.96682739257812, 'zcp_grasp': 6.322265625, 'zcp_jacov': -16.05571953368823, 'zcp_l2_norm': 1030.806640625, 'zcp_nwot': 231.64153905636073, 'zcp_params': 13126538.0, 'zcp_plain': 0.05682165548205301, 'zcp_snip': 1672.8245849609375, 'zcp_synflow': 126.23909541613362, 'zcp_zen': 91.24940490722656, 'zcp_val_accuracy': 0.9427083134651181}
| |
NASBench101_190237
|
NASBench101
|
190237
|
730af82308ea5bbda6685469e898e7ae
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_554[FLOAT, 128x3x3x3]
%onnx::Conv_555[FLOAT, 128]
%onnx::Conv_557[FLOAT, 64x128x1x1]
%onnx::Conv_558[FLOAT, 64]
%onnx::Conv_560[FLOAT, 64x64x3x3]
%onnx::Conv_563[FLOAT, 64x64x1x1]
%onnx::Conv_566[FLOAT, 64x128x1x1]
%onnx::Conv_569[FLOAT, 64x64x3x3]
%onnx::Conv_572[FLOAT, 64x64x1x1]
%onnx::Conv_575[FLOAT, 64x128x1x1]
%onnx::Conv_578[FLOAT, 64x64x3x3]
%onnx::Conv_581[FLOAT, 64x64x1x1]
%onnx::Conv_584[FLOAT, 128x128x1x1]
%onnx::Conv_587[FLOAT, 128x128x3x3]
%onnx::Conv_590[FLOAT, 128x128x1x1]
%onnx::Conv_593[FLOAT, 128x256x1x1]
%onnx::Conv_596[FLOAT, 128x128x3x3]
%onnx::Conv_599[FLOAT, 128x128x1x1]
%onnx::Conv_602[FLOAT, 128x256x1x1]
%onnx::Conv_605[FLOAT, 128x128x3x3]
%onnx::Conv_608[FLOAT, 128x128x1x1]
%onnx::Conv_611[FLOAT, 256x256x1x1]
%onnx::Conv_612[FLOAT, 256]
%onnx::Conv_614[FLOAT, 256x256x3x3]
%onnx::Conv_617[FLOAT, 256x256x1x1]
%onnx::Conv_620[FLOAT, 256x512x1x1]
%onnx::Conv_623[FLOAT, 256x256x3x3]
%onnx::Conv_626[FLOAT, 256x256x1x1]
%onnx::Conv_629[FLOAT, 256x512x1x1]
%onnx::Conv_632[FLOAT, 256x256x3x3]
%onnx::Conv_635[FLOAT, 256x256x1x1]
) {
%onnx::Conv_636 = Identity(%onnx::Conv_612)
%onnx::Conv_633 = Identity(%onnx::Conv_612)
%onnx::Conv_630 = Identity(%onnx::Conv_612)
%onnx::Conv_627 = Identity(%onnx::Conv_612)
%onnx::Conv_624 = Identity(%onnx::Conv_612)
%onnx::Conv_621 = Identity(%onnx::Conv_612)
%onnx::Conv_618 = Identity(%onnx::Conv_612)
%onnx::Conv_615 = Identity(%onnx::Conv_612)
%onnx::Conv_609 = Identity(%onnx::Conv_555)
%onnx::Conv_606 = Identity(%onnx::Conv_555)
%onnx::Conv_603 = Identity(%onnx::Conv_555)
%onnx::Conv_600 = Identity(%onnx::Conv_555)
%onnx::Conv_597 = Identity(%onnx::Conv_555)
%onnx::Conv_594 = Identity(%onnx::Conv_555)
%onnx::Conv_591 = Identity(%onnx::Conv_555)
%onnx::Conv_588 = Identity(%onnx::Conv_555)
%onnx::Conv_585 = Identity(%onnx::Conv_555)
%onnx::Conv_582 = Identity(%onnx::Conv_558)
%onnx::Conv_579 = Identity(%onnx::Conv_558)
%onnx::Conv_576 = Identity(%onnx::Conv_558)
%onnx::Conv_573 = Identity(%onnx::Conv_558)
%onnx::Conv_570 = Identity(%onnx::Conv_558)
%onnx::Conv_567 = Identity(%onnx::Conv_558)
%onnx::Conv_564 = Identity(%onnx::Conv_558)
%onnx::Conv_561 = Identity(%onnx::Conv_558)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_554, %onnx::Conv_555)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_557, %onnx::Conv_558)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_560, %onnx::Conv_561)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_563, %onnx::Conv_564)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_566, %onnx::Conv_567)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_569, %onnx::Conv_570)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_572, %onnx::Conv_573)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_575, %onnx::Conv_576)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_578, %onnx::Conv_579)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_581, %onnx::Conv_582)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_584, %onnx::Conv_585)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_587, %onnx::Conv_588)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_590, %onnx::Conv_591)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_593, %onnx::Conv_594)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_596, %onnx::Conv_597)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_599, %onnx::Conv_600)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_602, %onnx::Conv_603)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_605, %onnx::Conv_606)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_608, %onnx::Conv_609)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_611, %onnx::Conv_612)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_614, %onnx::Conv_615)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_617, %onnx::Conv_618)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_620, %onnx::Conv_621)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_623, %onnx::Conv_624)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_626, %onnx::Conv_627)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_629, %onnx::Conv_630)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_632, %onnx::Conv_633)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_635, %onnx::Conv_636)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%552 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %552
}
|
val_accuracy
| 88.711941
| 905,586,688
| 3,031,562
|
{'zcp_epe_nas': 111.00228556718278, 'zcp_fisher': 25.86653709411621, 'zcp_flops': 14489387008.0, 'zcp_grad_norm': 78.69331359863281, 'zcp_grasp': -5.31817626953125, 'zcp_jacov': -16.04520910643869, 'zcp_l2_norm': 497.6888732910156, 'zcp_nwot': 213.82951337986006, 'zcp_params': 3031562.0, 'zcp_plain': 0.08617752790451001, 'zcp_snip': 494.02996826171875, 'zcp_synflow': 96.57471971999233, 'zcp_zen': 59.797855377197266, 'zcp_val_accuracy': 0.919471144676208}
| |
NASBench101_104654
|
NASBench101
|
104654
|
3f49f1da001141d6671c2c5614c2e403
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_653[FLOAT, 128x3x3x3]
%onnx::Conv_654[FLOAT, 128]
%onnx::Conv_656[FLOAT, 64x128x1x1]
%onnx::Conv_657[FLOAT, 64]
%onnx::Conv_659[FLOAT, 64x64x1x1]
%onnx::Conv_662[FLOAT, 64x128x1x1]
%onnx::Conv_665[FLOAT, 64x64x1x1]
%onnx::Conv_668[FLOAT, 64x128x1x1]
%onnx::Conv_671[FLOAT, 64x64x1x1]
%onnx::Conv_674[FLOAT, 64x128x1x1]
%onnx::Conv_677[FLOAT, 64x64x1x1]
%onnx::Conv_680[FLOAT, 64x128x1x1]
%onnx::Conv_683[FLOAT, 64x64x1x1]
%onnx::Conv_686[FLOAT, 64x128x1x1]
%onnx::Conv_689[FLOAT, 64x64x1x1]
%onnx::Conv_692[FLOAT, 128x128x1x1]
%onnx::Conv_695[FLOAT, 128x128x1x1]
%onnx::Conv_698[FLOAT, 128x128x1x1]
%onnx::Conv_701[FLOAT, 128x128x1x1]
%onnx::Conv_704[FLOAT, 128x256x1x1]
%onnx::Conv_707[FLOAT, 128x128x1x1]
%onnx::Conv_710[FLOAT, 128x256x1x1]
%onnx::Conv_713[FLOAT, 128x128x1x1]
%onnx::Conv_716[FLOAT, 128x256x1x1]
%onnx::Conv_719[FLOAT, 128x128x1x1]
%onnx::Conv_722[FLOAT, 128x256x1x1]
%onnx::Conv_725[FLOAT, 128x128x1x1]
%onnx::Conv_728[FLOAT, 256x256x1x1]
%onnx::Conv_729[FLOAT, 256]
%onnx::Conv_731[FLOAT, 256x256x1x1]
%onnx::Conv_734[FLOAT, 256x256x1x1]
%onnx::Conv_737[FLOAT, 256x256x1x1]
%onnx::Conv_740[FLOAT, 256x512x1x1]
%onnx::Conv_743[FLOAT, 256x256x1x1]
%onnx::Conv_746[FLOAT, 256x512x1x1]
%onnx::Conv_749[FLOAT, 256x256x1x1]
%onnx::Conv_752[FLOAT, 256x512x1x1]
%onnx::Conv_755[FLOAT, 256x256x1x1]
%onnx::Conv_758[FLOAT, 256x512x1x1]
%onnx::Conv_761[FLOAT, 256x256x1x1]
) {
%onnx::Conv_762 = Identity(%onnx::Conv_729)
%onnx::Conv_759 = Identity(%onnx::Conv_729)
%onnx::Conv_756 = Identity(%onnx::Conv_729)
%onnx::Conv_753 = Identity(%onnx::Conv_729)
%onnx::Conv_750 = Identity(%onnx::Conv_729)
%onnx::Conv_747 = Identity(%onnx::Conv_729)
%onnx::Conv_744 = Identity(%onnx::Conv_729)
%onnx::Conv_741 = Identity(%onnx::Conv_729)
%onnx::Conv_738 = Identity(%onnx::Conv_729)
%onnx::Conv_735 = Identity(%onnx::Conv_729)
%onnx::Conv_732 = Identity(%onnx::Conv_729)
%onnx::Conv_726 = Identity(%onnx::Conv_654)
%onnx::Conv_723 = Identity(%onnx::Conv_654)
%onnx::Conv_720 = Identity(%onnx::Conv_654)
%onnx::Conv_717 = Identity(%onnx::Conv_654)
%onnx::Conv_714 = Identity(%onnx::Conv_654)
%onnx::Conv_711 = Identity(%onnx::Conv_654)
%onnx::Conv_708 = Identity(%onnx::Conv_654)
%onnx::Conv_705 = Identity(%onnx::Conv_654)
%onnx::Conv_702 = Identity(%onnx::Conv_654)
%onnx::Conv_699 = Identity(%onnx::Conv_654)
%onnx::Conv_696 = Identity(%onnx::Conv_654)
%onnx::Conv_693 = Identity(%onnx::Conv_654)
%onnx::Conv_690 = Identity(%onnx::Conv_657)
%onnx::Conv_687 = Identity(%onnx::Conv_657)
%onnx::Conv_684 = Identity(%onnx::Conv_657)
%onnx::Conv_681 = Identity(%onnx::Conv_657)
%onnx::Conv_678 = Identity(%onnx::Conv_657)
%onnx::Conv_675 = Identity(%onnx::Conv_657)
%onnx::Conv_672 = Identity(%onnx::Conv_657)
%onnx::Conv_669 = Identity(%onnx::Conv_657)
%onnx::Conv_666 = Identity(%onnx::Conv_657)
%onnx::Conv_663 = Identity(%onnx::Conv_657)
%onnx::Conv_660 = Identity(%onnx::Conv_657)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_653, %onnx::Conv_654)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_656, %onnx::Conv_657)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_659, %onnx::Conv_660)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_662, %onnx::Conv_663)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%651 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %651
}
|
val_accuracy
| 89.573318
| 438,577,152
| 1,404,042
|
{'zcp_epe_nas': 97.1761582233028, 'zcp_fisher': 8.577780723571777, 'zcp_flops': 7017234432.0, 'zcp_grad_norm': 61.40545654296875, 'zcp_grasp': -1.5892333984375, 'zcp_jacov': -16.062316166685534, 'zcp_l2_norm': 695.2295532226562, 'zcp_nwot': 218.28324459971648, 'zcp_params': 1404042.0, 'zcp_plain': 0.057310171425342005, 'zcp_snip': 318.0677490234375, 'zcp_synflow': 76.24105357106862, 'zcp_zen': 59.933204650878906, 'zcp_val_accuracy': 0.9198718070983881}
| |
NASBench101_421423
|
NASBench101
|
421423
|
fea76f4cbd8e9c8cf96f4c49282eef69
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_743[FLOAT, 128x3x3x3]
%onnx::Conv_744[FLOAT, 128]
%onnx::Conv_746[FLOAT, 64x128x1x1]
%onnx::Conv_747[FLOAT, 64]
%onnx::Conv_749[FLOAT, 64x64x1x1]
%onnx::Conv_752[FLOAT, 64x128x1x1]
%onnx::Conv_755[FLOAT, 64x64x1x1]
%onnx::Conv_758[FLOAT, 128x128x1x1]
%onnx::Conv_761[FLOAT, 64x128x1x1]
%onnx::Conv_764[FLOAT, 64x64x1x1]
%onnx::Conv_767[FLOAT, 64x128x1x1]
%onnx::Conv_770[FLOAT, 64x64x1x1]
%onnx::Conv_773[FLOAT, 128x128x1x1]
%onnx::Conv_776[FLOAT, 64x128x1x1]
%onnx::Conv_779[FLOAT, 64x64x1x1]
%onnx::Conv_782[FLOAT, 64x128x1x1]
%onnx::Conv_785[FLOAT, 64x64x1x1]
%onnx::Conv_788[FLOAT, 128x128x1x1]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 128x128x1x1]
%onnx::Conv_797[FLOAT, 128x128x1x1]
%onnx::Conv_800[FLOAT, 128x128x1x1]
%onnx::Conv_803[FLOAT, 256x128x1x1]
%onnx::Conv_804[FLOAT, 256]
%onnx::Conv_806[FLOAT, 128x256x1x1]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x256x1x1]
%onnx::Conv_815[FLOAT, 128x128x1x1]
%onnx::Conv_818[FLOAT, 256x256x1x1]
%onnx::Conv_821[FLOAT, 128x256x1x1]
%onnx::Conv_824[FLOAT, 128x128x1x1]
%onnx::Conv_827[FLOAT, 128x256x1x1]
%onnx::Conv_830[FLOAT, 128x128x1x1]
%onnx::Conv_833[FLOAT, 256x256x1x1]
%onnx::Conv_836[FLOAT, 256x256x1x1]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x256x1x1]
%onnx::Conv_845[FLOAT, 256x256x1x1]
%onnx::Conv_848[FLOAT, 512x256x1x1]
%onnx::Conv_849[FLOAT, 512]
%onnx::Conv_851[FLOAT, 256x512x1x1]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_857[FLOAT, 256x512x1x1]
%onnx::Conv_860[FLOAT, 256x256x1x1]
%onnx::Conv_863[FLOAT, 512x512x1x1]
%onnx::Conv_866[FLOAT, 256x512x1x1]
%onnx::Conv_869[FLOAT, 256x256x1x1]
%onnx::Conv_872[FLOAT, 256x512x1x1]
%onnx::Conv_875[FLOAT, 256x256x1x1]
%onnx::Conv_878[FLOAT, 512x512x1x1]
) {
%onnx::Conv_879 = Identity(%onnx::Conv_849)
%onnx::Conv_876 = Identity(%onnx::Conv_804)
%onnx::Conv_873 = Identity(%onnx::Conv_804)
%onnx::Conv_870 = Identity(%onnx::Conv_804)
%onnx::Conv_867 = Identity(%onnx::Conv_804)
%onnx::Conv_864 = Identity(%onnx::Conv_849)
%onnx::Conv_861 = Identity(%onnx::Conv_804)
%onnx::Conv_858 = Identity(%onnx::Conv_804)
%onnx::Conv_855 = Identity(%onnx::Conv_804)
%onnx::Conv_852 = Identity(%onnx::Conv_804)
%onnx::Conv_846 = Identity(%onnx::Conv_804)
%onnx::Conv_843 = Identity(%onnx::Conv_804)
%onnx::Conv_840 = Identity(%onnx::Conv_804)
%onnx::Conv_837 = Identity(%onnx::Conv_804)
%onnx::Conv_834 = Identity(%onnx::Conv_804)
%onnx::Conv_831 = Identity(%onnx::Conv_744)
%onnx::Conv_828 = Identity(%onnx::Conv_744)
%onnx::Conv_825 = Identity(%onnx::Conv_744)
%onnx::Conv_822 = Identity(%onnx::Conv_744)
%onnx::Conv_819 = Identity(%onnx::Conv_804)
%onnx::Conv_816 = Identity(%onnx::Conv_744)
%onnx::Conv_813 = Identity(%onnx::Conv_744)
%onnx::Conv_810 = Identity(%onnx::Conv_744)
%onnx::Conv_807 = Identity(%onnx::Conv_744)
%onnx::Conv_801 = Identity(%onnx::Conv_744)
%onnx::Conv_798 = Identity(%onnx::Conv_744)
%onnx::Conv_795 = Identity(%onnx::Conv_744)
%onnx::Conv_792 = Identity(%onnx::Conv_744)
%onnx::Conv_789 = Identity(%onnx::Conv_744)
%onnx::Conv_786 = Identity(%onnx::Conv_747)
%onnx::Conv_783 = Identity(%onnx::Conv_747)
%onnx::Conv_780 = Identity(%onnx::Conv_747)
%onnx::Conv_777 = Identity(%onnx::Conv_747)
%onnx::Conv_774 = Identity(%onnx::Conv_744)
%onnx::Conv_771 = Identity(%onnx::Conv_747)
%onnx::Conv_768 = Identity(%onnx::Conv_747)
%onnx::Conv_765 = Identity(%onnx::Conv_747)
%onnx::Conv_762 = Identity(%onnx::Conv_747)
%onnx::Conv_759 = Identity(%onnx::Conv_744)
%onnx::Conv_756 = Identity(%onnx::Conv_747)
%onnx::Conv_753 = Identity(%onnx::Conv_747)
%onnx::Conv_750 = Identity(%onnx::Conv_747)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_743, %onnx::Conv_744)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_4_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_4_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_4_output_0)
%741 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %741
}
|
val_accuracy
| 90.014023
| 712,517,632
| 2,277,770
|
{'zcp_epe_nas': 93.04355055305368, 'zcp_fisher': 3.448273181915283, 'zcp_flops': 11400282112.0, 'zcp_grad_norm': 42.87882614135742, 'zcp_grasp': -1.938720703125, 'zcp_jacov': -16.064177366397978, 'zcp_l2_norm': 890.4979858398438, 'zcp_nwot': 224.50437033155754, 'zcp_params': 2277770.0, 'zcp_plain': 0.032628551125526005, 'zcp_snip': 269.8148193359375, 'zcp_synflow': 75.63825055936154, 'zcp_zen': 77.62443542480469, 'zcp_val_accuracy': 0.8917267918586731}
| |
NASBench101_287465
|
NASBench101
|
287465
|
ae0700394cb5477ccf3f930861d447ce
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_830[FLOAT, 128x3x3x3]
%onnx::Conv_831[FLOAT, 128]
%onnx::Conv_833[FLOAT, 43x128x1x1]
%onnx::Conv_834[FLOAT, 43]
%onnx::Conv_836[FLOAT, 43x43x1x1]
%onnx::Conv_839[FLOAT, 43x128x1x1]
%onnx::Conv_842[FLOAT, 43x43x3x3]
%onnx::Conv_845[FLOAT, 42x42x1x1]
%onnx::Conv_846[FLOAT, 42]
%onnx::Conv_848[FLOAT, 43x128x1x1]
%onnx::Conv_851[FLOAT, 43x43x1x1]
%onnx::Conv_854[FLOAT, 43x128x1x1]
%onnx::Conv_857[FLOAT, 43x43x3x3]
%onnx::Conv_860[FLOAT, 42x42x1x1]
%onnx::Conv_863[FLOAT, 43x128x1x1]
%onnx::Conv_866[FLOAT, 43x43x1x1]
%onnx::Conv_869[FLOAT, 43x128x1x1]
%onnx::Conv_872[FLOAT, 43x43x3x3]
%onnx::Conv_875[FLOAT, 42x42x1x1]
%onnx::Conv_878[FLOAT, 86x128x1x1]
%onnx::Conv_879[FLOAT, 86]
%onnx::Conv_881[FLOAT, 86x86x1x1]
%onnx::Conv_884[FLOAT, 85x128x1x1]
%onnx::Conv_885[FLOAT, 85]
%onnx::Conv_887[FLOAT, 85x85x3x3]
%onnx::Conv_890[FLOAT, 85x85x1x1]
%onnx::Conv_893[FLOAT, 86x256x1x1]
%onnx::Conv_896[FLOAT, 86x86x1x1]
%onnx::Conv_899[FLOAT, 85x256x1x1]
%onnx::Conv_902[FLOAT, 85x85x3x3]
%onnx::Conv_905[FLOAT, 85x85x1x1]
%onnx::Conv_908[FLOAT, 86x256x1x1]
%onnx::Conv_911[FLOAT, 86x86x1x1]
%onnx::Conv_914[FLOAT, 85x256x1x1]
%onnx::Conv_917[FLOAT, 85x85x3x3]
%onnx::Conv_920[FLOAT, 85x85x1x1]
%onnx::Conv_923[FLOAT, 171x256x1x1]
%onnx::Conv_924[FLOAT, 171]
%onnx::Conv_926[FLOAT, 171x171x1x1]
%onnx::Conv_929[FLOAT, 171x256x1x1]
%onnx::Conv_932[FLOAT, 171x171x3x3]
%onnx::Conv_935[FLOAT, 170x170x1x1]
%onnx::Conv_936[FLOAT, 170]
%onnx::Conv_938[FLOAT, 171x512x1x1]
%onnx::Conv_941[FLOAT, 171x171x1x1]
%onnx::Conv_944[FLOAT, 171x512x1x1]
%onnx::Conv_947[FLOAT, 171x171x3x3]
%onnx::Conv_950[FLOAT, 170x170x1x1]
%onnx::Conv_953[FLOAT, 171x512x1x1]
%onnx::Conv_956[FLOAT, 171x171x1x1]
%onnx::Conv_959[FLOAT, 171x512x1x1]
%onnx::Conv_962[FLOAT, 171x171x3x3]
%onnx::Conv_965[FLOAT, 170x170x1x1]
) {
%onnx::Conv_966 = Identity(%onnx::Conv_936)
%onnx::Conv_963 = Identity(%onnx::Conv_924)
%onnx::Conv_960 = Identity(%onnx::Conv_924)
%onnx::Conv_957 = Identity(%onnx::Conv_924)
%onnx::Conv_954 = Identity(%onnx::Conv_924)
%onnx::Conv_951 = Identity(%onnx::Conv_936)
%onnx::Conv_948 = Identity(%onnx::Conv_924)
%onnx::Conv_945 = Identity(%onnx::Conv_924)
%onnx::Conv_942 = Identity(%onnx::Conv_924)
%onnx::Conv_939 = Identity(%onnx::Conv_924)
%onnx::Conv_933 = Identity(%onnx::Conv_924)
%onnx::Conv_930 = Identity(%onnx::Conv_924)
%onnx::Conv_927 = Identity(%onnx::Conv_924)
%onnx::Conv_921 = Identity(%onnx::Conv_885)
%onnx::Conv_918 = Identity(%onnx::Conv_885)
%onnx::Conv_915 = Identity(%onnx::Conv_885)
%onnx::Conv_912 = Identity(%onnx::Conv_879)
%onnx::Conv_909 = Identity(%onnx::Conv_879)
%onnx::Conv_906 = Identity(%onnx::Conv_885)
%onnx::Conv_903 = Identity(%onnx::Conv_885)
%onnx::Conv_900 = Identity(%onnx::Conv_885)
%onnx::Conv_897 = Identity(%onnx::Conv_879)
%onnx::Conv_894 = Identity(%onnx::Conv_879)
%onnx::Conv_891 = Identity(%onnx::Conv_885)
%onnx::Conv_888 = Identity(%onnx::Conv_885)
%onnx::Conv_882 = Identity(%onnx::Conv_879)
%onnx::Conv_876 = Identity(%onnx::Conv_846)
%onnx::Conv_873 = Identity(%onnx::Conv_834)
%onnx::Conv_870 = Identity(%onnx::Conv_834)
%onnx::Conv_867 = Identity(%onnx::Conv_834)
%onnx::Conv_864 = Identity(%onnx::Conv_834)
%onnx::Conv_861 = Identity(%onnx::Conv_846)
%onnx::Conv_858 = Identity(%onnx::Conv_834)
%onnx::Conv_855 = Identity(%onnx::Conv_834)
%onnx::Conv_852 = Identity(%onnx::Conv_834)
%onnx::Conv_849 = Identity(%onnx::Conv_834)
%onnx::Conv_843 = Identity(%onnx::Conv_834)
%onnx::Conv_840 = Identity(%onnx::Conv_834)
%onnx::Conv_837 = Identity(%onnx::Conv_834)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_830, %onnx::Conv_831)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_6_output_0)
%/layers.1/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_1_output_0 = Slice(%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/Constant_8_output_0, %/layers.1/Constant_9_output_0, %/layers.1/Constant_7_output_0, %/layers.1/Constant_10_output_0)
%/layers.1/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_11_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/Slice_1_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_6_output_0)
%/layers.2/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_1_output_0 = Slice(%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/Constant_8_output_0, %/layers.2/Constant_9_output_0, %/layers.2/Constant_7_output_0, %/layers.2/Constant_10_output_0)
%/layers.2/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_11_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/Slice_1_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_6_output_0)
%/layers.3/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_1_output_0 = Slice(%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/Constant_8_output_0, %/layers.3/Constant_9_output_0, %/layers.3/Constant_7_output_0, %/layers.3/Constant_10_output_0)
%/layers.3/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_11_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/Slice_1_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_6_output_0)
%/layers.9/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_1_output_0 = Slice(%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/Constant_8_output_0, %/layers.9/Constant_9_output_0, %/layers.9/Constant_7_output_0, %/layers.9/Constant_10_output_0)
%/layers.9/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_11_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/Slice_1_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_6_output_0)
%/layers.10/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_1_output_0 = Slice(%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/Constant_8_output_0, %/layers.10/Constant_9_output_0, %/layers.10/Constant_7_output_0, %/layers.10/Constant_10_output_0)
%/layers.10/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_11_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/Slice_1_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_6_output_0)
%/layers.11/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_1_output_0 = Slice(%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/Constant_8_output_0, %/layers.11/Constant_9_output_0, %/layers.11/Constant_7_output_0, %/layers.11/Constant_10_output_0)
%/layers.11/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_11_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/Slice_1_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%828 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %828
}
|
val_accuracy
| 91.937101
| 567,190,784
| 1,861,666
|
{'zcp_epe_nas': 147.82604943683478, 'zcp_fisher': 20.354774475097656, 'zcp_flops': 9075052544.0, 'zcp_grad_norm': 76.332763671875, 'zcp_grasp': 5.6094970703125, 'zcp_jacov': -16.056006635255788, 'zcp_l2_norm': 762.8192749023438, 'zcp_nwot': 216.00390698101498, 'zcp_params': 1861666.0, 'zcp_plain': 0.006942962761968, 'zcp_snip': 388.4320068359375, 'zcp_synflow': 85.58406879972372, 'zcp_zen': 74.56825256347656, 'zcp_val_accuracy': 0.868790090084075}
| |
NASBench101_119684
|
NASBench101
|
119684
|
484c1409f2aef5c66a3c93d4e100cb8e
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_743[FLOAT, 128x3x3x3]
%onnx::Conv_744[FLOAT, 128]
%onnx::Conv_746[FLOAT, 64x128x1x1]
%onnx::Conv_747[FLOAT, 64]
%onnx::Conv_749[FLOAT, 64x128x1x1]
%onnx::Conv_752[FLOAT, 64x128x1x1]
%onnx::Conv_755[FLOAT, 64x64x3x3]
%onnx::Conv_758[FLOAT, 128x128x1x1]
%onnx::Conv_761[FLOAT, 64x128x1x1]
%onnx::Conv_764[FLOAT, 64x128x1x1]
%onnx::Conv_767[FLOAT, 64x128x1x1]
%onnx::Conv_770[FLOAT, 64x64x3x3]
%onnx::Conv_773[FLOAT, 128x128x1x1]
%onnx::Conv_776[FLOAT, 64x128x1x1]
%onnx::Conv_779[FLOAT, 64x128x1x1]
%onnx::Conv_782[FLOAT, 64x128x1x1]
%onnx::Conv_785[FLOAT, 64x64x3x3]
%onnx::Conv_788[FLOAT, 128x128x1x1]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 128x128x1x1]
%onnx::Conv_797[FLOAT, 128x128x1x1]
%onnx::Conv_800[FLOAT, 128x128x3x3]
%onnx::Conv_803[FLOAT, 256x128x1x1]
%onnx::Conv_804[FLOAT, 256]
%onnx::Conv_806[FLOAT, 128x256x1x1]
%onnx::Conv_809[FLOAT, 128x256x1x1]
%onnx::Conv_812[FLOAT, 128x256x1x1]
%onnx::Conv_815[FLOAT, 128x128x3x3]
%onnx::Conv_818[FLOAT, 256x256x1x1]
%onnx::Conv_821[FLOAT, 128x256x1x1]
%onnx::Conv_824[FLOAT, 128x256x1x1]
%onnx::Conv_827[FLOAT, 128x256x1x1]
%onnx::Conv_830[FLOAT, 128x128x3x3]
%onnx::Conv_833[FLOAT, 256x256x1x1]
%onnx::Conv_836[FLOAT, 256x256x1x1]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x256x1x1]
%onnx::Conv_845[FLOAT, 256x256x3x3]
%onnx::Conv_848[FLOAT, 512x256x1x1]
%onnx::Conv_849[FLOAT, 512]
%onnx::Conv_851[FLOAT, 256x512x1x1]
%onnx::Conv_854[FLOAT, 256x512x1x1]
%onnx::Conv_857[FLOAT, 256x512x1x1]
%onnx::Conv_860[FLOAT, 256x256x3x3]
%onnx::Conv_863[FLOAT, 512x512x1x1]
%onnx::Conv_866[FLOAT, 256x512x1x1]
%onnx::Conv_869[FLOAT, 256x512x1x1]
%onnx::Conv_872[FLOAT, 256x512x1x1]
%onnx::Conv_875[FLOAT, 256x256x3x3]
%onnx::Conv_878[FLOAT, 512x512x1x1]
) {
%onnx::Conv_879 = Identity(%onnx::Conv_849)
%onnx::Conv_876 = Identity(%onnx::Conv_804)
%onnx::Conv_873 = Identity(%onnx::Conv_804)
%onnx::Conv_870 = Identity(%onnx::Conv_804)
%onnx::Conv_867 = Identity(%onnx::Conv_804)
%onnx::Conv_864 = Identity(%onnx::Conv_849)
%onnx::Conv_861 = Identity(%onnx::Conv_804)
%onnx::Conv_858 = Identity(%onnx::Conv_804)
%onnx::Conv_855 = Identity(%onnx::Conv_804)
%onnx::Conv_852 = Identity(%onnx::Conv_804)
%onnx::Conv_846 = Identity(%onnx::Conv_804)
%onnx::Conv_843 = Identity(%onnx::Conv_804)
%onnx::Conv_840 = Identity(%onnx::Conv_804)
%onnx::Conv_837 = Identity(%onnx::Conv_804)
%onnx::Conv_834 = Identity(%onnx::Conv_804)
%onnx::Conv_831 = Identity(%onnx::Conv_744)
%onnx::Conv_828 = Identity(%onnx::Conv_744)
%onnx::Conv_825 = Identity(%onnx::Conv_744)
%onnx::Conv_822 = Identity(%onnx::Conv_744)
%onnx::Conv_819 = Identity(%onnx::Conv_804)
%onnx::Conv_816 = Identity(%onnx::Conv_744)
%onnx::Conv_813 = Identity(%onnx::Conv_744)
%onnx::Conv_810 = Identity(%onnx::Conv_744)
%onnx::Conv_807 = Identity(%onnx::Conv_744)
%onnx::Conv_801 = Identity(%onnx::Conv_744)
%onnx::Conv_798 = Identity(%onnx::Conv_744)
%onnx::Conv_795 = Identity(%onnx::Conv_744)
%onnx::Conv_792 = Identity(%onnx::Conv_744)
%onnx::Conv_789 = Identity(%onnx::Conv_744)
%onnx::Conv_786 = Identity(%onnx::Conv_747)
%onnx::Conv_783 = Identity(%onnx::Conv_747)
%onnx::Conv_780 = Identity(%onnx::Conv_747)
%onnx::Conv_777 = Identity(%onnx::Conv_747)
%onnx::Conv_774 = Identity(%onnx::Conv_744)
%onnx::Conv_771 = Identity(%onnx::Conv_747)
%onnx::Conv_768 = Identity(%onnx::Conv_747)
%onnx::Conv_765 = Identity(%onnx::Conv_747)
%onnx::Conv_762 = Identity(%onnx::Conv_747)
%onnx::Conv_759 = Identity(%onnx::Conv_744)
%onnx::Conv_756 = Identity(%onnx::Conv_747)
%onnx::Conv_753 = Identity(%onnx::Conv_747)
%onnx::Conv_750 = Identity(%onnx::Conv_747)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_743, %onnx::Conv_744)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_4_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_4_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_4_output_0)
%741 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %741
}
|
val_accuracy
| 92.878604
| 1,375,217,664
| 4,518,282
|
{'zcp_epe_nas': 147.9127658620033, 'zcp_fisher': 3.443371534347534, 'zcp_flops': 22003482624.0, 'zcp_grad_norm': 33.37827682495117, 'zcp_grasp': -5.312232971191406, 'zcp_jacov': -16.05527346229709, 'zcp_l2_norm': 935.96923828125, 'zcp_nwot': 223.7456357044464, 'zcp_params': 4518282.0, 'zcp_plain': 0.089483268558979, 'zcp_snip': 218.6082763671875, 'zcp_synflow': 77.014155821521, 'zcp_zen': 95.52640533447266, 'zcp_val_accuracy': 0.9200721383094781}
| |
NASBench101_113950
|
NASBench101
|
113950
|
44d322164d8cab0fcd8c76708b4ce3dd
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_860[FLOAT, 128x3x3x3]
%onnx::Conv_861[FLOAT, 128]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%onnx::Conv_866[FLOAT, 128x128x1x1]
%onnx::Conv_869[FLOAT, 128x128x1x1]
%onnx::Conv_872[FLOAT, 128x128x1x1]
%onnx::Conv_875[FLOAT, 128x128x3x3]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 128x128x1x1]
%onnx::Conv_884[FLOAT, 128x128x1x1]
%onnx::Conv_887[FLOAT, 128x128x1x1]
%onnx::Conv_890[FLOAT, 128x128x1x1]
%onnx::Conv_893[FLOAT, 128x128x3x3]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%onnx::Conv_899[FLOAT, 128x128x1x1]
%onnx::Conv_902[FLOAT, 128x128x1x1]
%onnx::Conv_905[FLOAT, 128x128x1x1]
%onnx::Conv_908[FLOAT, 128x128x1x1]
%onnx::Conv_911[FLOAT, 128x128x3x3]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 256x128x1x1]
%onnx::Conv_918[FLOAT, 256]
%onnx::Conv_920[FLOAT, 256x256x1x1]
%onnx::Conv_923[FLOAT, 256x128x1x1]
%onnx::Conv_926[FLOAT, 256x256x1x1]
%onnx::Conv_929[FLOAT, 256x256x3x3]
%onnx::Conv_932[FLOAT, 256x128x1x1]
%onnx::Conv_935[FLOAT, 256x256x1x1]
%onnx::Conv_938[FLOAT, 256x256x1x1]
%onnx::Conv_941[FLOAT, 256x256x1x1]
%onnx::Conv_944[FLOAT, 256x256x1x1]
%onnx::Conv_947[FLOAT, 256x256x3x3]
%onnx::Conv_950[FLOAT, 256x256x1x1]
%onnx::Conv_953[FLOAT, 256x256x1x1]
%onnx::Conv_956[FLOAT, 256x256x1x1]
%onnx::Conv_959[FLOAT, 256x256x1x1]
%onnx::Conv_962[FLOAT, 256x256x1x1]
%onnx::Conv_965[FLOAT, 256x256x3x3]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 512x256x1x1]
%onnx::Conv_972[FLOAT, 512]
%onnx::Conv_974[FLOAT, 512x512x1x1]
%onnx::Conv_977[FLOAT, 512x256x1x1]
%onnx::Conv_980[FLOAT, 512x512x1x1]
%onnx::Conv_983[FLOAT, 512x512x3x3]
%onnx::Conv_986[FLOAT, 512x256x1x1]
%onnx::Conv_989[FLOAT, 512x512x1x1]
%onnx::Conv_992[FLOAT, 512x512x1x1]
%onnx::Conv_995[FLOAT, 512x512x1x1]
%onnx::Conv_998[FLOAT, 512x512x1x1]
%onnx::Conv_1001[FLOAT, 512x512x3x3]
%onnx::Conv_1004[FLOAT, 512x512x1x1]
%onnx::Conv_1007[FLOAT, 512x512x1x1]
%onnx::Conv_1010[FLOAT, 512x512x1x1]
%onnx::Conv_1013[FLOAT, 512x512x1x1]
%onnx::Conv_1016[FLOAT, 512x512x1x1]
%onnx::Conv_1019[FLOAT, 512x512x3x3]
%onnx::Conv_1022[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1023 = Identity(%onnx::Conv_972)
%onnx::Conv_1020 = Identity(%onnx::Conv_972)
%onnx::Conv_1017 = Identity(%onnx::Conv_972)
%onnx::Conv_1014 = Identity(%onnx::Conv_972)
%onnx::Conv_1011 = Identity(%onnx::Conv_972)
%onnx::Conv_1008 = Identity(%onnx::Conv_972)
%onnx::Conv_1005 = Identity(%onnx::Conv_972)
%onnx::Conv_1002 = Identity(%onnx::Conv_972)
%onnx::Conv_999 = Identity(%onnx::Conv_972)
%onnx::Conv_996 = Identity(%onnx::Conv_972)
%onnx::Conv_993 = Identity(%onnx::Conv_972)
%onnx::Conv_990 = Identity(%onnx::Conv_972)
%onnx::Conv_987 = Identity(%onnx::Conv_972)
%onnx::Conv_984 = Identity(%onnx::Conv_972)
%onnx::Conv_981 = Identity(%onnx::Conv_972)
%onnx::Conv_978 = Identity(%onnx::Conv_972)
%onnx::Conv_975 = Identity(%onnx::Conv_972)
%onnx::Conv_969 = Identity(%onnx::Conv_918)
%onnx::Conv_966 = Identity(%onnx::Conv_918)
%onnx::Conv_963 = Identity(%onnx::Conv_918)
%onnx::Conv_960 = Identity(%onnx::Conv_918)
%onnx::Conv_957 = Identity(%onnx::Conv_918)
%onnx::Conv_954 = Identity(%onnx::Conv_918)
%onnx::Conv_951 = Identity(%onnx::Conv_918)
%onnx::Conv_948 = Identity(%onnx::Conv_918)
%onnx::Conv_945 = Identity(%onnx::Conv_918)
%onnx::Conv_942 = Identity(%onnx::Conv_918)
%onnx::Conv_939 = Identity(%onnx::Conv_918)
%onnx::Conv_936 = Identity(%onnx::Conv_918)
%onnx::Conv_933 = Identity(%onnx::Conv_918)
%onnx::Conv_930 = Identity(%onnx::Conv_918)
%onnx::Conv_927 = Identity(%onnx::Conv_918)
%onnx::Conv_924 = Identity(%onnx::Conv_918)
%onnx::Conv_921 = Identity(%onnx::Conv_918)
%onnx::Conv_915 = Identity(%onnx::Conv_861)
%onnx::Conv_912 = Identity(%onnx::Conv_861)
%onnx::Conv_909 = Identity(%onnx::Conv_861)
%onnx::Conv_906 = Identity(%onnx::Conv_861)
%onnx::Conv_903 = Identity(%onnx::Conv_861)
%onnx::Conv_900 = Identity(%onnx::Conv_861)
%onnx::Conv_897 = Identity(%onnx::Conv_861)
%onnx::Conv_894 = Identity(%onnx::Conv_861)
%onnx::Conv_891 = Identity(%onnx::Conv_861)
%onnx::Conv_888 = Identity(%onnx::Conv_861)
%onnx::Conv_885 = Identity(%onnx::Conv_861)
%onnx::Conv_882 = Identity(%onnx::Conv_861)
%onnx::Conv_879 = Identity(%onnx::Conv_861)
%onnx::Conv_876 = Identity(%onnx::Conv_861)
%onnx::Conv_873 = Identity(%onnx::Conv_861)
%onnx::Conv_870 = Identity(%onnx::Conv_861)
%onnx::Conv_867 = Identity(%onnx::Conv_861)
%onnx::Conv_864 = Identity(%onnx::Conv_861)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_860, %onnx::Conv_861)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.5/maxpool/MaxPool_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_5_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.5/maxpool/MaxPool_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_5_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.5/maxpool/MaxPool_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_5_output_0)
%858 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %858
}
|
val_accuracy
| 92.117387
| 4,168,361,984
| 14,000,266
|
{'zcp_epe_nas': 114.14260180605902, 'zcp_fisher': 42.071781158447266, 'zcp_flops': 66693791744.0, 'zcp_grad_norm': 133.2331085205078, 'zcp_grasp': -34.143798828125, 'zcp_jacov': -16.052339111248866, 'zcp_l2_norm': 1226.77734375, 'zcp_nwot': 234.7732335987624, 'zcp_params': 14000266.0, 'zcp_plain': 0.16128362715244202, 'zcp_snip': 1137.038818359375, 'zcp_synflow': 99.86232417775877, 'zcp_zen': 113.64317321777344, 'zcp_val_accuracy': 0.8978365659713741}
| |
NASBench101_12076
|
NASBench101
|
12076
|
0740459738e9601f98671cc23670c7fe
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_986[FLOAT, 128x3x3x3]
%onnx::Conv_987[FLOAT, 128]
%onnx::Conv_989[FLOAT, 64x128x1x1]
%onnx::Conv_990[FLOAT, 64]
%onnx::Conv_992[FLOAT, 64x64x1x1]
%onnx::Conv_995[FLOAT, 64x128x1x1]
%onnx::Conv_998[FLOAT, 64x64x1x1]
%onnx::Conv_1001[FLOAT, 64x128x1x1]
%onnx::Conv_1004[FLOAT, 64x64x3x3]
%onnx::Conv_1007[FLOAT, 64x64x3x3]
%onnx::Conv_1010[FLOAT, 64x128x1x1]
%onnx::Conv_1013[FLOAT, 64x64x1x1]
%onnx::Conv_1016[FLOAT, 64x128x1x1]
%onnx::Conv_1019[FLOAT, 64x64x1x1]
%onnx::Conv_1022[FLOAT, 64x128x1x1]
%onnx::Conv_1025[FLOAT, 64x64x3x3]
%onnx::Conv_1028[FLOAT, 64x64x3x3]
%onnx::Conv_1031[FLOAT, 64x128x1x1]
%onnx::Conv_1034[FLOAT, 64x64x1x1]
%onnx::Conv_1037[FLOAT, 64x128x1x1]
%onnx::Conv_1040[FLOAT, 64x64x1x1]
%onnx::Conv_1043[FLOAT, 64x128x1x1]
%onnx::Conv_1046[FLOAT, 64x64x3x3]
%onnx::Conv_1049[FLOAT, 64x64x3x3]
%onnx::Conv_1052[FLOAT, 128x128x1x1]
%onnx::Conv_1055[FLOAT, 128x128x1x1]
%onnx::Conv_1058[FLOAT, 128x128x1x1]
%onnx::Conv_1061[FLOAT, 128x128x1x1]
%onnx::Conv_1064[FLOAT, 128x128x1x1]
%onnx::Conv_1067[FLOAT, 128x128x3x3]
%onnx::Conv_1070[FLOAT, 128x128x3x3]
%onnx::Conv_1073[FLOAT, 128x256x1x1]
%onnx::Conv_1076[FLOAT, 128x128x1x1]
%onnx::Conv_1079[FLOAT, 128x256x1x1]
%onnx::Conv_1082[FLOAT, 128x128x1x1]
%onnx::Conv_1085[FLOAT, 128x256x1x1]
%onnx::Conv_1088[FLOAT, 128x128x3x3]
%onnx::Conv_1091[FLOAT, 128x128x3x3]
%onnx::Conv_1094[FLOAT, 128x256x1x1]
%onnx::Conv_1097[FLOAT, 128x128x1x1]
%onnx::Conv_1100[FLOAT, 128x256x1x1]
%onnx::Conv_1103[FLOAT, 128x128x1x1]
%onnx::Conv_1106[FLOAT, 128x256x1x1]
%onnx::Conv_1109[FLOAT, 128x128x3x3]
%onnx::Conv_1112[FLOAT, 128x128x3x3]
%onnx::Conv_1115[FLOAT, 256x256x1x1]
%onnx::Conv_1116[FLOAT, 256]
%onnx::Conv_1118[FLOAT, 256x256x1x1]
%onnx::Conv_1121[FLOAT, 256x256x1x1]
%onnx::Conv_1124[FLOAT, 256x256x1x1]
%onnx::Conv_1127[FLOAT, 256x256x1x1]
%onnx::Conv_1130[FLOAT, 256x256x3x3]
%onnx::Conv_1133[FLOAT, 256x256x3x3]
%onnx::Conv_1136[FLOAT, 256x512x1x1]
%onnx::Conv_1139[FLOAT, 256x256x1x1]
%onnx::Conv_1142[FLOAT, 256x512x1x1]
%onnx::Conv_1145[FLOAT, 256x256x1x1]
%onnx::Conv_1148[FLOAT, 256x512x1x1]
%onnx::Conv_1151[FLOAT, 256x256x3x3]
%onnx::Conv_1154[FLOAT, 256x256x3x3]
%onnx::Conv_1157[FLOAT, 256x512x1x1]
%onnx::Conv_1160[FLOAT, 256x256x1x1]
%onnx::Conv_1163[FLOAT, 256x512x1x1]
%onnx::Conv_1166[FLOAT, 256x256x1x1]
%onnx::Conv_1169[FLOAT, 256x512x1x1]
%onnx::Conv_1172[FLOAT, 256x256x3x3]
%onnx::Conv_1175[FLOAT, 256x256x3x3]
) {
%onnx::Conv_1176 = Identity(%onnx::Conv_1116)
%onnx::Conv_1173 = Identity(%onnx::Conv_1116)
%onnx::Conv_1170 = Identity(%onnx::Conv_1116)
%onnx::Conv_1167 = Identity(%onnx::Conv_1116)
%onnx::Conv_1164 = Identity(%onnx::Conv_1116)
%onnx::Conv_1161 = Identity(%onnx::Conv_1116)
%onnx::Conv_1158 = Identity(%onnx::Conv_1116)
%onnx::Conv_1155 = Identity(%onnx::Conv_1116)
%onnx::Conv_1152 = Identity(%onnx::Conv_1116)
%onnx::Conv_1149 = Identity(%onnx::Conv_1116)
%onnx::Conv_1146 = Identity(%onnx::Conv_1116)
%onnx::Conv_1143 = Identity(%onnx::Conv_1116)
%onnx::Conv_1140 = Identity(%onnx::Conv_1116)
%onnx::Conv_1137 = Identity(%onnx::Conv_1116)
%onnx::Conv_1134 = Identity(%onnx::Conv_1116)
%onnx::Conv_1131 = Identity(%onnx::Conv_1116)
%onnx::Conv_1128 = Identity(%onnx::Conv_1116)
%onnx::Conv_1125 = Identity(%onnx::Conv_1116)
%onnx::Conv_1122 = Identity(%onnx::Conv_1116)
%onnx::Conv_1119 = Identity(%onnx::Conv_1116)
%onnx::Conv_1113 = Identity(%onnx::Conv_987)
%onnx::Conv_1110 = Identity(%onnx::Conv_987)
%onnx::Conv_1107 = Identity(%onnx::Conv_987)
%onnx::Conv_1104 = Identity(%onnx::Conv_987)
%onnx::Conv_1101 = Identity(%onnx::Conv_987)
%onnx::Conv_1098 = Identity(%onnx::Conv_987)
%onnx::Conv_1095 = Identity(%onnx::Conv_987)
%onnx::Conv_1092 = Identity(%onnx::Conv_987)
%onnx::Conv_1089 = Identity(%onnx::Conv_987)
%onnx::Conv_1086 = Identity(%onnx::Conv_987)
%onnx::Conv_1083 = Identity(%onnx::Conv_987)
%onnx::Conv_1080 = Identity(%onnx::Conv_987)
%onnx::Conv_1077 = Identity(%onnx::Conv_987)
%onnx::Conv_1074 = Identity(%onnx::Conv_987)
%onnx::Conv_1071 = Identity(%onnx::Conv_987)
%onnx::Conv_1068 = Identity(%onnx::Conv_987)
%onnx::Conv_1065 = Identity(%onnx::Conv_987)
%onnx::Conv_1062 = Identity(%onnx::Conv_987)
%onnx::Conv_1059 = Identity(%onnx::Conv_987)
%onnx::Conv_1056 = Identity(%onnx::Conv_987)
%onnx::Conv_1053 = Identity(%onnx::Conv_987)
%onnx::Conv_1050 = Identity(%onnx::Conv_990)
%onnx::Conv_1047 = Identity(%onnx::Conv_990)
%onnx::Conv_1044 = Identity(%onnx::Conv_990)
%onnx::Conv_1041 = Identity(%onnx::Conv_990)
%onnx::Conv_1038 = Identity(%onnx::Conv_990)
%onnx::Conv_1035 = Identity(%onnx::Conv_990)
%onnx::Conv_1032 = Identity(%onnx::Conv_990)
%onnx::Conv_1029 = Identity(%onnx::Conv_990)
%onnx::Conv_1026 = Identity(%onnx::Conv_990)
%onnx::Conv_1023 = Identity(%onnx::Conv_990)
%onnx::Conv_1020 = Identity(%onnx::Conv_990)
%onnx::Conv_1017 = Identity(%onnx::Conv_990)
%onnx::Conv_1014 = Identity(%onnx::Conv_990)
%onnx::Conv_1011 = Identity(%onnx::Conv_990)
%onnx::Conv_1008 = Identity(%onnx::Conv_990)
%onnx::Conv_1005 = Identity(%onnx::Conv_990)
%onnx::Conv_1002 = Identity(%onnx::Conv_990)
%onnx::Conv_999 = Identity(%onnx::Conv_990)
%onnx::Conv_996 = Identity(%onnx::Conv_990)
%onnx::Conv_993 = Identity(%onnx::Conv_990)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_986, %onnx::Conv_987)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1169, %onnx::Conv_1170)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1172, %onnx::Conv_1173)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_1175, %onnx::Conv_1176)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%984 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %984
}
|
val_accuracy
| 93.980366
| 1,940,006,912
| 6,491,146
|
{'zcp_epe_nas': 115.36904935588257, 'zcp_fisher': 6.018793106079102, 'zcp_flops': 31040110592.0, 'zcp_grad_norm': 54.94780731201172, 'zcp_grasp': -5.945587158203125, 'zcp_jacov': -16.039613467880187, 'zcp_l2_norm': 1190.799072265625, 'zcp_nwot': 226.56957553719516, 'zcp_params': 6491146.0, 'zcp_plain': 0.075968854129314, 'zcp_snip': 328.62774658203125, 'zcp_synflow': 123.1102796236093, 'zcp_zen': 109.19892120361328, 'zcp_val_accuracy': 0.922475934028625}
| |
NASBench101_322258
|
NASBench101
|
322258
|
c30074115772471eddd5cb543401095f
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_968[FLOAT, 128x3x3x3]
%onnx::Conv_969[FLOAT, 128]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 128x128x1x1]
%onnx::Conv_983[FLOAT, 128x128x3x3]
%onnx::Conv_986[FLOAT, 128x128x1x1]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x1x1]
%onnx::Conv_998[FLOAT, 128x128x1x1]
%onnx::Conv_1001[FLOAT, 128x128x1x1]
%onnx::Conv_1004[FLOAT, 128x128x3x3]
%onnx::Conv_1007[FLOAT, 128x128x1x1]
%onnx::Conv_1010[FLOAT, 128x128x1x1]
%onnx::Conv_1013[FLOAT, 128x128x1x1]
%onnx::Conv_1016[FLOAT, 128x128x1x1]
%onnx::Conv_1019[FLOAT, 128x128x1x1]
%onnx::Conv_1022[FLOAT, 128x128x1x1]
%onnx::Conv_1025[FLOAT, 128x128x3x3]
%onnx::Conv_1028[FLOAT, 128x128x1x1]
%onnx::Conv_1031[FLOAT, 128x128x1x1]
%onnx::Conv_1034[FLOAT, 256x128x1x1]
%onnx::Conv_1035[FLOAT, 256]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 256x256x1x1]
%onnx::Conv_1043[FLOAT, 256x128x1x1]
%onnx::Conv_1046[FLOAT, 256x256x3x3]
%onnx::Conv_1049[FLOAT, 256x256x1x1]
%onnx::Conv_1052[FLOAT, 256x256x1x1]
%onnx::Conv_1055[FLOAT, 256x256x1x1]
%onnx::Conv_1058[FLOAT, 256x256x1x1]
%onnx::Conv_1061[FLOAT, 256x256x1x1]
%onnx::Conv_1064[FLOAT, 256x256x1x1]
%onnx::Conv_1067[FLOAT, 256x256x3x3]
%onnx::Conv_1070[FLOAT, 256x256x1x1]
%onnx::Conv_1073[FLOAT, 256x256x1x1]
%onnx::Conv_1076[FLOAT, 256x256x1x1]
%onnx::Conv_1079[FLOAT, 256x256x1x1]
%onnx::Conv_1082[FLOAT, 256x256x1x1]
%onnx::Conv_1085[FLOAT, 256x256x1x1]
%onnx::Conv_1088[FLOAT, 256x256x3x3]
%onnx::Conv_1091[FLOAT, 256x256x1x1]
%onnx::Conv_1094[FLOAT, 256x256x1x1]
%onnx::Conv_1097[FLOAT, 512x256x1x1]
%onnx::Conv_1098[FLOAT, 512]
%onnx::Conv_1100[FLOAT, 512x512x1x1]
%onnx::Conv_1103[FLOAT, 512x512x1x1]
%onnx::Conv_1106[FLOAT, 512x256x1x1]
%onnx::Conv_1109[FLOAT, 512x512x3x3]
%onnx::Conv_1112[FLOAT, 512x512x1x1]
%onnx::Conv_1115[FLOAT, 512x512x1x1]
%onnx::Conv_1118[FLOAT, 512x512x1x1]
%onnx::Conv_1121[FLOAT, 512x512x1x1]
%onnx::Conv_1124[FLOAT, 512x512x1x1]
%onnx::Conv_1127[FLOAT, 512x512x1x1]
%onnx::Conv_1130[FLOAT, 512x512x3x3]
%onnx::Conv_1133[FLOAT, 512x512x1x1]
%onnx::Conv_1136[FLOAT, 512x512x1x1]
%onnx::Conv_1139[FLOAT, 512x512x1x1]
%onnx::Conv_1142[FLOAT, 512x512x1x1]
%onnx::Conv_1145[FLOAT, 512x512x1x1]
%onnx::Conv_1148[FLOAT, 512x512x1x1]
%onnx::Conv_1151[FLOAT, 512x512x3x3]
%onnx::Conv_1154[FLOAT, 512x512x1x1]
%onnx::Conv_1157[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1158 = Identity(%onnx::Conv_1098)
%onnx::Conv_1155 = Identity(%onnx::Conv_1098)
%onnx::Conv_1152 = Identity(%onnx::Conv_1098)
%onnx::Conv_1149 = Identity(%onnx::Conv_1098)
%onnx::Conv_1146 = Identity(%onnx::Conv_1098)
%onnx::Conv_1143 = Identity(%onnx::Conv_1098)
%onnx::Conv_1140 = Identity(%onnx::Conv_1098)
%onnx::Conv_1137 = Identity(%onnx::Conv_1098)
%onnx::Conv_1134 = Identity(%onnx::Conv_1098)
%onnx::Conv_1131 = Identity(%onnx::Conv_1098)
%onnx::Conv_1128 = Identity(%onnx::Conv_1098)
%onnx::Conv_1125 = Identity(%onnx::Conv_1098)
%onnx::Conv_1122 = Identity(%onnx::Conv_1098)
%onnx::Conv_1119 = Identity(%onnx::Conv_1098)
%onnx::Conv_1116 = Identity(%onnx::Conv_1098)
%onnx::Conv_1113 = Identity(%onnx::Conv_1098)
%onnx::Conv_1110 = Identity(%onnx::Conv_1098)
%onnx::Conv_1107 = Identity(%onnx::Conv_1098)
%onnx::Conv_1104 = Identity(%onnx::Conv_1098)
%onnx::Conv_1101 = Identity(%onnx::Conv_1098)
%onnx::Conv_1095 = Identity(%onnx::Conv_1035)
%onnx::Conv_1092 = Identity(%onnx::Conv_1035)
%onnx::Conv_1089 = Identity(%onnx::Conv_1035)
%onnx::Conv_1086 = Identity(%onnx::Conv_1035)
%onnx::Conv_1083 = Identity(%onnx::Conv_1035)
%onnx::Conv_1080 = Identity(%onnx::Conv_1035)
%onnx::Conv_1077 = Identity(%onnx::Conv_1035)
%onnx::Conv_1074 = Identity(%onnx::Conv_1035)
%onnx::Conv_1071 = Identity(%onnx::Conv_1035)
%onnx::Conv_1068 = Identity(%onnx::Conv_1035)
%onnx::Conv_1065 = Identity(%onnx::Conv_1035)
%onnx::Conv_1062 = Identity(%onnx::Conv_1035)
%onnx::Conv_1059 = Identity(%onnx::Conv_1035)
%onnx::Conv_1056 = Identity(%onnx::Conv_1035)
%onnx::Conv_1053 = Identity(%onnx::Conv_1035)
%onnx::Conv_1050 = Identity(%onnx::Conv_1035)
%onnx::Conv_1047 = Identity(%onnx::Conv_1035)
%onnx::Conv_1044 = Identity(%onnx::Conv_1035)
%onnx::Conv_1041 = Identity(%onnx::Conv_1035)
%onnx::Conv_1038 = Identity(%onnx::Conv_1035)
%onnx::Conv_1032 = Identity(%onnx::Conv_969)
%onnx::Conv_1029 = Identity(%onnx::Conv_969)
%onnx::Conv_1026 = Identity(%onnx::Conv_969)
%onnx::Conv_1023 = Identity(%onnx::Conv_969)
%onnx::Conv_1020 = Identity(%onnx::Conv_969)
%onnx::Conv_1017 = Identity(%onnx::Conv_969)
%onnx::Conv_1014 = Identity(%onnx::Conv_969)
%onnx::Conv_1011 = Identity(%onnx::Conv_969)
%onnx::Conv_1008 = Identity(%onnx::Conv_969)
%onnx::Conv_1005 = Identity(%onnx::Conv_969)
%onnx::Conv_1002 = Identity(%onnx::Conv_969)
%onnx::Conv_999 = Identity(%onnx::Conv_969)
%onnx::Conv_996 = Identity(%onnx::Conv_969)
%onnx::Conv_993 = Identity(%onnx::Conv_969)
%onnx::Conv_990 = Identity(%onnx::Conv_969)
%onnx::Conv_987 = Identity(%onnx::Conv_969)
%onnx::Conv_984 = Identity(%onnx::Conv_969)
%onnx::Conv_981 = Identity(%onnx::Conv_969)
%onnx::Conv_978 = Identity(%onnx::Conv_969)
%onnx::Conv_975 = Identity(%onnx::Conv_969)
%onnx::Conv_972 = Identity(%onnx::Conv_969)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_968, %onnx::Conv_969)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%966 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %966
}
|
val_accuracy
| 91.276044
| 4,509,411,328
| 15,201,674
|
{'zcp_epe_nas': 112.15798814892129, 'zcp_fisher': 852.3182983398438, 'zcp_flops': 72150581248.0, 'zcp_grad_norm': 620.6483154296875, 'zcp_grasp': 3782.9375, 'zcp_jacov': -16.044519318639637, 'zcp_l2_norm': 1454.39501953125, 'zcp_nwot': 237.7331682724656, 'zcp_params': 15201674.0, 'zcp_plain': 0.0031751566566520003, 'zcp_snip': 4074.99658203125, 'zcp_synflow': 148.35360505178275, 'zcp_zen': 113.2509536743164, 'zcp_val_accuracy': 0.877704322338104}
| |
NASBench101_256767
|
NASBench101
|
256767
|
9b75dc3556af1bf844c85e95047e882f
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_869[FLOAT, 128x3x3x3]
%onnx::Conv_870[FLOAT, 128]
%onnx::Conv_872[FLOAT, 128x128x1x1]
%onnx::Conv_875[FLOAT, 128x128x1x1]
%onnx::Conv_878[FLOAT, 128x128x3x3]
%onnx::Conv_881[FLOAT, 128x128x3x3]
%onnx::Conv_884[FLOAT, 128x128x3x3]
%onnx::Conv_887[FLOAT, 128x128x3x3]
%onnx::Conv_890[FLOAT, 128x128x1x1]
%onnx::Conv_893[FLOAT, 128x128x1x1]
%onnx::Conv_896[FLOAT, 128x128x3x3]
%onnx::Conv_899[FLOAT, 128x128x3x3]
%onnx::Conv_902[FLOAT, 128x128x3x3]
%onnx::Conv_905[FLOAT, 128x128x3x3]
%onnx::Conv_908[FLOAT, 128x128x1x1]
%onnx::Conv_911[FLOAT, 128x128x1x1]
%onnx::Conv_914[FLOAT, 128x128x3x3]
%onnx::Conv_917[FLOAT, 128x128x3x3]
%onnx::Conv_920[FLOAT, 128x128x3x3]
%onnx::Conv_923[FLOAT, 128x128x3x3]
%onnx::Conv_926[FLOAT, 256x128x1x1]
%onnx::Conv_927[FLOAT, 256]
%onnx::Conv_929[FLOAT, 256x256x1x1]
%onnx::Conv_932[FLOAT, 256x256x3x3]
%onnx::Conv_935[FLOAT, 256x256x3x3]
%onnx::Conv_938[FLOAT, 256x256x3x3]
%onnx::Conv_941[FLOAT, 256x256x3x3]
%onnx::Conv_944[FLOAT, 256x256x1x1]
%onnx::Conv_947[FLOAT, 256x256x1x1]
%onnx::Conv_950[FLOAT, 256x256x3x3]
%onnx::Conv_953[FLOAT, 256x256x3x3]
%onnx::Conv_956[FLOAT, 256x256x3x3]
%onnx::Conv_959[FLOAT, 256x256x3x3]
%onnx::Conv_962[FLOAT, 256x256x1x1]
%onnx::Conv_965[FLOAT, 256x256x1x1]
%onnx::Conv_968[FLOAT, 256x256x3x3]
%onnx::Conv_971[FLOAT, 256x256x3x3]
%onnx::Conv_974[FLOAT, 256x256x3x3]
%onnx::Conv_977[FLOAT, 256x256x3x3]
%onnx::Conv_980[FLOAT, 512x256x1x1]
%onnx::Conv_981[FLOAT, 512]
%onnx::Conv_983[FLOAT, 512x512x1x1]
%onnx::Conv_986[FLOAT, 512x512x3x3]
%onnx::Conv_989[FLOAT, 512x512x3x3]
%onnx::Conv_992[FLOAT, 512x512x3x3]
%onnx::Conv_995[FLOAT, 512x512x3x3]
%onnx::Conv_998[FLOAT, 512x512x1x1]
%onnx::Conv_1001[FLOAT, 512x512x1x1]
%onnx::Conv_1004[FLOAT, 512x512x3x3]
%onnx::Conv_1007[FLOAT, 512x512x3x3]
%onnx::Conv_1010[FLOAT, 512x512x3x3]
%onnx::Conv_1013[FLOAT, 512x512x3x3]
%onnx::Conv_1016[FLOAT, 512x512x1x1]
%onnx::Conv_1019[FLOAT, 512x512x1x1]
%onnx::Conv_1022[FLOAT, 512x512x3x3]
%onnx::Conv_1025[FLOAT, 512x512x3x3]
%onnx::Conv_1028[FLOAT, 512x512x3x3]
%onnx::Conv_1031[FLOAT, 512x512x3x3]
) {
%onnx::Conv_1032 = Identity(%onnx::Conv_981)
%onnx::Conv_1029 = Identity(%onnx::Conv_981)
%onnx::Conv_1026 = Identity(%onnx::Conv_981)
%onnx::Conv_1023 = Identity(%onnx::Conv_981)
%onnx::Conv_1020 = Identity(%onnx::Conv_981)
%onnx::Conv_1017 = Identity(%onnx::Conv_981)
%onnx::Conv_1014 = Identity(%onnx::Conv_981)
%onnx::Conv_1011 = Identity(%onnx::Conv_981)
%onnx::Conv_1008 = Identity(%onnx::Conv_981)
%onnx::Conv_1005 = Identity(%onnx::Conv_981)
%onnx::Conv_1002 = Identity(%onnx::Conv_981)
%onnx::Conv_999 = Identity(%onnx::Conv_981)
%onnx::Conv_996 = Identity(%onnx::Conv_981)
%onnx::Conv_993 = Identity(%onnx::Conv_981)
%onnx::Conv_990 = Identity(%onnx::Conv_981)
%onnx::Conv_987 = Identity(%onnx::Conv_981)
%onnx::Conv_984 = Identity(%onnx::Conv_981)
%onnx::Conv_978 = Identity(%onnx::Conv_927)
%onnx::Conv_975 = Identity(%onnx::Conv_927)
%onnx::Conv_972 = Identity(%onnx::Conv_927)
%onnx::Conv_969 = Identity(%onnx::Conv_927)
%onnx::Conv_966 = Identity(%onnx::Conv_927)
%onnx::Conv_963 = Identity(%onnx::Conv_927)
%onnx::Conv_960 = Identity(%onnx::Conv_927)
%onnx::Conv_957 = Identity(%onnx::Conv_927)
%onnx::Conv_954 = Identity(%onnx::Conv_927)
%onnx::Conv_951 = Identity(%onnx::Conv_927)
%onnx::Conv_948 = Identity(%onnx::Conv_927)
%onnx::Conv_945 = Identity(%onnx::Conv_927)
%onnx::Conv_942 = Identity(%onnx::Conv_927)
%onnx::Conv_939 = Identity(%onnx::Conv_927)
%onnx::Conv_936 = Identity(%onnx::Conv_927)
%onnx::Conv_933 = Identity(%onnx::Conv_927)
%onnx::Conv_930 = Identity(%onnx::Conv_927)
%onnx::Conv_924 = Identity(%onnx::Conv_870)
%onnx::Conv_921 = Identity(%onnx::Conv_870)
%onnx::Conv_918 = Identity(%onnx::Conv_870)
%onnx::Conv_915 = Identity(%onnx::Conv_870)
%onnx::Conv_912 = Identity(%onnx::Conv_870)
%onnx::Conv_909 = Identity(%onnx::Conv_870)
%onnx::Conv_906 = Identity(%onnx::Conv_870)
%onnx::Conv_903 = Identity(%onnx::Conv_870)
%onnx::Conv_900 = Identity(%onnx::Conv_870)
%onnx::Conv_897 = Identity(%onnx::Conv_870)
%onnx::Conv_894 = Identity(%onnx::Conv_870)
%onnx::Conv_891 = Identity(%onnx::Conv_870)
%onnx::Conv_888 = Identity(%onnx::Conv_870)
%onnx::Conv_885 = Identity(%onnx::Conv_870)
%onnx::Conv_882 = Identity(%onnx::Conv_870)
%onnx::Conv_879 = Identity(%onnx::Conv_870)
%onnx::Conv_876 = Identity(%onnx::Conv_870)
%onnx::Conv_873 = Identity(%onnx::Conv_870)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_869, %onnx::Conv_870)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%867 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %867
}
|
val_accuracy
| 88.100964
| 11,483,228,160
| 39,100,554
|
{'zcp_epe_nas': 138.0230159465126, 'zcp_fisher': 2287.784912109375, 'zcp_flops': 183731650560.0, 'zcp_grad_norm': 907.0750732421875, 'zcp_grasp': -21178.65625, 'zcp_jacov': -16.04476010621391, 'zcp_l2_norm': 1258.1513671875, 'zcp_nwot': 235.04029622670922, 'zcp_params': 39100554.0, 'zcp_plain': -0.021948939189314003, 'zcp_snip': 6788.07177734375, 'zcp_synflow': 200.69739365101017, 'zcp_zen': 128.3365020751953, 'zcp_val_accuracy': 0.9222756624221801}
| |
NASBench101_66151
|
NASBench101
|
66151
|
282762b5a6606c0e0c0e40eda803709f
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_734[FLOAT, 128x3x3x3]
%onnx::Conv_735[FLOAT, 128]
%onnx::Conv_737[FLOAT, 128x128x1x1]
%onnx::Conv_740[FLOAT, 128x128x1x1]
%onnx::Conv_743[FLOAT, 128x128x1x1]
%onnx::Conv_746[FLOAT, 128x128x1x1]
%onnx::Conv_749[FLOAT, 128x128x3x3]
%onnx::Conv_752[FLOAT, 128x128x1x1]
%onnx::Conv_755[FLOAT, 128x128x1x1]
%onnx::Conv_758[FLOAT, 128x128x1x1]
%onnx::Conv_761[FLOAT, 128x128x1x1]
%onnx::Conv_764[FLOAT, 128x128x3x3]
%onnx::Conv_767[FLOAT, 128x128x1x1]
%onnx::Conv_770[FLOAT, 128x128x1x1]
%onnx::Conv_773[FLOAT, 128x128x1x1]
%onnx::Conv_776[FLOAT, 128x128x1x1]
%onnx::Conv_779[FLOAT, 128x128x3x3]
%onnx::Conv_782[FLOAT, 256x128x1x1]
%onnx::Conv_783[FLOAT, 256]
%onnx::Conv_785[FLOAT, 256x128x1x1]
%onnx::Conv_788[FLOAT, 256x256x1x1]
%onnx::Conv_791[FLOAT, 256x256x1x1]
%onnx::Conv_794[FLOAT, 256x256x3x3]
%onnx::Conv_797[FLOAT, 256x256x1x1]
%onnx::Conv_800[FLOAT, 256x256x1x1]
%onnx::Conv_803[FLOAT, 256x256x1x1]
%onnx::Conv_806[FLOAT, 256x256x1x1]
%onnx::Conv_809[FLOAT, 256x256x3x3]
%onnx::Conv_812[FLOAT, 256x256x1x1]
%onnx::Conv_815[FLOAT, 256x256x1x1]
%onnx::Conv_818[FLOAT, 256x256x1x1]
%onnx::Conv_821[FLOAT, 256x256x1x1]
%onnx::Conv_824[FLOAT, 256x256x3x3]
%onnx::Conv_827[FLOAT, 512x256x1x1]
%onnx::Conv_828[FLOAT, 512]
%onnx::Conv_830[FLOAT, 512x256x1x1]
%onnx::Conv_833[FLOAT, 512x512x1x1]
%onnx::Conv_836[FLOAT, 512x512x1x1]
%onnx::Conv_839[FLOAT, 512x512x3x3]
%onnx::Conv_842[FLOAT, 512x512x1x1]
%onnx::Conv_845[FLOAT, 512x512x1x1]
%onnx::Conv_848[FLOAT, 512x512x1x1]
%onnx::Conv_851[FLOAT, 512x512x1x1]
%onnx::Conv_854[FLOAT, 512x512x3x3]
%onnx::Conv_857[FLOAT, 512x512x1x1]
%onnx::Conv_860[FLOAT, 512x512x1x1]
%onnx::Conv_863[FLOAT, 512x512x1x1]
%onnx::Conv_866[FLOAT, 512x512x1x1]
%onnx::Conv_869[FLOAT, 512x512x3x3]
) {
%onnx::Conv_870 = Identity(%onnx::Conv_828)
%onnx::Conv_867 = Identity(%onnx::Conv_828)
%onnx::Conv_864 = Identity(%onnx::Conv_828)
%onnx::Conv_861 = Identity(%onnx::Conv_828)
%onnx::Conv_858 = Identity(%onnx::Conv_828)
%onnx::Conv_855 = Identity(%onnx::Conv_828)
%onnx::Conv_852 = Identity(%onnx::Conv_828)
%onnx::Conv_849 = Identity(%onnx::Conv_828)
%onnx::Conv_846 = Identity(%onnx::Conv_828)
%onnx::Conv_843 = Identity(%onnx::Conv_828)
%onnx::Conv_840 = Identity(%onnx::Conv_828)
%onnx::Conv_837 = Identity(%onnx::Conv_828)
%onnx::Conv_834 = Identity(%onnx::Conv_828)
%onnx::Conv_831 = Identity(%onnx::Conv_828)
%onnx::Conv_825 = Identity(%onnx::Conv_783)
%onnx::Conv_822 = Identity(%onnx::Conv_783)
%onnx::Conv_819 = Identity(%onnx::Conv_783)
%onnx::Conv_816 = Identity(%onnx::Conv_783)
%onnx::Conv_813 = Identity(%onnx::Conv_783)
%onnx::Conv_810 = Identity(%onnx::Conv_783)
%onnx::Conv_807 = Identity(%onnx::Conv_783)
%onnx::Conv_804 = Identity(%onnx::Conv_783)
%onnx::Conv_801 = Identity(%onnx::Conv_783)
%onnx::Conv_798 = Identity(%onnx::Conv_783)
%onnx::Conv_795 = Identity(%onnx::Conv_783)
%onnx::Conv_792 = Identity(%onnx::Conv_783)
%onnx::Conv_789 = Identity(%onnx::Conv_783)
%onnx::Conv_786 = Identity(%onnx::Conv_783)
%onnx::Conv_780 = Identity(%onnx::Conv_735)
%onnx::Conv_777 = Identity(%onnx::Conv_735)
%onnx::Conv_774 = Identity(%onnx::Conv_735)
%onnx::Conv_771 = Identity(%onnx::Conv_735)
%onnx::Conv_768 = Identity(%onnx::Conv_735)
%onnx::Conv_765 = Identity(%onnx::Conv_735)
%onnx::Conv_762 = Identity(%onnx::Conv_735)
%onnx::Conv_759 = Identity(%onnx::Conv_735)
%onnx::Conv_756 = Identity(%onnx::Conv_735)
%onnx::Conv_753 = Identity(%onnx::Conv_735)
%onnx::Conv_750 = Identity(%onnx::Conv_735)
%onnx::Conv_747 = Identity(%onnx::Conv_735)
%onnx::Conv_744 = Identity(%onnx::Conv_735)
%onnx::Conv_741 = Identity(%onnx::Conv_735)
%onnx::Conv_738 = Identity(%onnx::Conv_735)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_734, %onnx::Conv_735)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%732 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %732
}
|
val_accuracy
| 92.13742
| 3,894,421,504
| 13,126,538
|
{'zcp_epe_nas': 68.8065447877576, 'zcp_fisher': 18.702451705932617, 'zcp_flops': 62310744064.0, 'zcp_grad_norm': 67.40654754638672, 'zcp_grasp': -3.454498291015625, 'zcp_jacov': -16.04872111605425, 'zcp_l2_norm': 1030.673583984375, 'zcp_nwot': 231.70364145821782, 'zcp_params': 13126538.0, 'zcp_plain': 0.035569787025451, 'zcp_snip': 577.0584716796875, 'zcp_synflow': 120.2511714707239, 'zcp_zen': 91.43547058105469, 'zcp_val_accuracy': 0.875801265239715}
| |
NASBench101_206316
|
NASBench101
|
206316
|
7ceedf857e2fc4dae2280c8fdf467b5b
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_986[FLOAT, 128x3x3x3]
%onnx::Conv_987[FLOAT, 128]
%onnx::Conv_989[FLOAT, 64x128x1x1]
%onnx::Conv_990[FLOAT, 64]
%onnx::Conv_992[FLOAT, 64x64x3x3]
%onnx::Conv_995[FLOAT, 64x128x1x1]
%onnx::Conv_998[FLOAT, 64x64x1x1]
%onnx::Conv_1001[FLOAT, 64x128x1x1]
%onnx::Conv_1004[FLOAT, 64x64x3x3]
%onnx::Conv_1007[FLOAT, 64x64x1x1]
%onnx::Conv_1010[FLOAT, 64x128x1x1]
%onnx::Conv_1013[FLOAT, 64x64x3x3]
%onnx::Conv_1016[FLOAT, 64x128x1x1]
%onnx::Conv_1019[FLOAT, 64x64x1x1]
%onnx::Conv_1022[FLOAT, 64x128x1x1]
%onnx::Conv_1025[FLOAT, 64x64x3x3]
%onnx::Conv_1028[FLOAT, 64x64x1x1]
%onnx::Conv_1031[FLOAT, 64x128x1x1]
%onnx::Conv_1034[FLOAT, 64x64x3x3]
%onnx::Conv_1037[FLOAT, 64x128x1x1]
%onnx::Conv_1040[FLOAT, 64x64x1x1]
%onnx::Conv_1043[FLOAT, 64x128x1x1]
%onnx::Conv_1046[FLOAT, 64x64x3x3]
%onnx::Conv_1049[FLOAT, 64x64x1x1]
%onnx::Conv_1052[FLOAT, 128x128x1x1]
%onnx::Conv_1055[FLOAT, 128x128x3x3]
%onnx::Conv_1058[FLOAT, 128x128x1x1]
%onnx::Conv_1061[FLOAT, 128x128x1x1]
%onnx::Conv_1064[FLOAT, 128x128x1x1]
%onnx::Conv_1067[FLOAT, 128x128x3x3]
%onnx::Conv_1070[FLOAT, 128x128x1x1]
%onnx::Conv_1073[FLOAT, 128x256x1x1]
%onnx::Conv_1076[FLOAT, 128x128x3x3]
%onnx::Conv_1079[FLOAT, 128x256x1x1]
%onnx::Conv_1082[FLOAT, 128x128x1x1]
%onnx::Conv_1085[FLOAT, 128x256x1x1]
%onnx::Conv_1088[FLOAT, 128x128x3x3]
%onnx::Conv_1091[FLOAT, 128x128x1x1]
%onnx::Conv_1094[FLOAT, 128x256x1x1]
%onnx::Conv_1097[FLOAT, 128x128x3x3]
%onnx::Conv_1100[FLOAT, 128x256x1x1]
%onnx::Conv_1103[FLOAT, 128x128x1x1]
%onnx::Conv_1106[FLOAT, 128x256x1x1]
%onnx::Conv_1109[FLOAT, 128x128x3x3]
%onnx::Conv_1112[FLOAT, 128x128x1x1]
%onnx::Conv_1115[FLOAT, 256x256x1x1]
%onnx::Conv_1116[FLOAT, 256]
%onnx::Conv_1118[FLOAT, 256x256x3x3]
%onnx::Conv_1121[FLOAT, 256x256x1x1]
%onnx::Conv_1124[FLOAT, 256x256x1x1]
%onnx::Conv_1127[FLOAT, 256x256x1x1]
%onnx::Conv_1130[FLOAT, 256x256x3x3]
%onnx::Conv_1133[FLOAT, 256x256x1x1]
%onnx::Conv_1136[FLOAT, 256x512x1x1]
%onnx::Conv_1139[FLOAT, 256x256x3x3]
%onnx::Conv_1142[FLOAT, 256x512x1x1]
%onnx::Conv_1145[FLOAT, 256x256x1x1]
%onnx::Conv_1148[FLOAT, 256x512x1x1]
%onnx::Conv_1151[FLOAT, 256x256x3x3]
%onnx::Conv_1154[FLOAT, 256x256x1x1]
%onnx::Conv_1157[FLOAT, 256x512x1x1]
%onnx::Conv_1160[FLOAT, 256x256x3x3]
%onnx::Conv_1163[FLOAT, 256x512x1x1]
%onnx::Conv_1166[FLOAT, 256x256x1x1]
%onnx::Conv_1169[FLOAT, 256x512x1x1]
%onnx::Conv_1172[FLOAT, 256x256x3x3]
%onnx::Conv_1175[FLOAT, 256x256x1x1]
) {
%onnx::Conv_1176 = Identity(%onnx::Conv_1116)
%onnx::Conv_1173 = Identity(%onnx::Conv_1116)
%onnx::Conv_1170 = Identity(%onnx::Conv_1116)
%onnx::Conv_1167 = Identity(%onnx::Conv_1116)
%onnx::Conv_1164 = Identity(%onnx::Conv_1116)
%onnx::Conv_1161 = Identity(%onnx::Conv_1116)
%onnx::Conv_1158 = Identity(%onnx::Conv_1116)
%onnx::Conv_1155 = Identity(%onnx::Conv_1116)
%onnx::Conv_1152 = Identity(%onnx::Conv_1116)
%onnx::Conv_1149 = Identity(%onnx::Conv_1116)
%onnx::Conv_1146 = Identity(%onnx::Conv_1116)
%onnx::Conv_1143 = Identity(%onnx::Conv_1116)
%onnx::Conv_1140 = Identity(%onnx::Conv_1116)
%onnx::Conv_1137 = Identity(%onnx::Conv_1116)
%onnx::Conv_1134 = Identity(%onnx::Conv_1116)
%onnx::Conv_1131 = Identity(%onnx::Conv_1116)
%onnx::Conv_1128 = Identity(%onnx::Conv_1116)
%onnx::Conv_1125 = Identity(%onnx::Conv_1116)
%onnx::Conv_1122 = Identity(%onnx::Conv_1116)
%onnx::Conv_1119 = Identity(%onnx::Conv_1116)
%onnx::Conv_1113 = Identity(%onnx::Conv_987)
%onnx::Conv_1110 = Identity(%onnx::Conv_987)
%onnx::Conv_1107 = Identity(%onnx::Conv_987)
%onnx::Conv_1104 = Identity(%onnx::Conv_987)
%onnx::Conv_1101 = Identity(%onnx::Conv_987)
%onnx::Conv_1098 = Identity(%onnx::Conv_987)
%onnx::Conv_1095 = Identity(%onnx::Conv_987)
%onnx::Conv_1092 = Identity(%onnx::Conv_987)
%onnx::Conv_1089 = Identity(%onnx::Conv_987)
%onnx::Conv_1086 = Identity(%onnx::Conv_987)
%onnx::Conv_1083 = Identity(%onnx::Conv_987)
%onnx::Conv_1080 = Identity(%onnx::Conv_987)
%onnx::Conv_1077 = Identity(%onnx::Conv_987)
%onnx::Conv_1074 = Identity(%onnx::Conv_987)
%onnx::Conv_1071 = Identity(%onnx::Conv_987)
%onnx::Conv_1068 = Identity(%onnx::Conv_987)
%onnx::Conv_1065 = Identity(%onnx::Conv_987)
%onnx::Conv_1062 = Identity(%onnx::Conv_987)
%onnx::Conv_1059 = Identity(%onnx::Conv_987)
%onnx::Conv_1056 = Identity(%onnx::Conv_987)
%onnx::Conv_1053 = Identity(%onnx::Conv_987)
%onnx::Conv_1050 = Identity(%onnx::Conv_990)
%onnx::Conv_1047 = Identity(%onnx::Conv_990)
%onnx::Conv_1044 = Identity(%onnx::Conv_990)
%onnx::Conv_1041 = Identity(%onnx::Conv_990)
%onnx::Conv_1038 = Identity(%onnx::Conv_990)
%onnx::Conv_1035 = Identity(%onnx::Conv_990)
%onnx::Conv_1032 = Identity(%onnx::Conv_990)
%onnx::Conv_1029 = Identity(%onnx::Conv_990)
%onnx::Conv_1026 = Identity(%onnx::Conv_990)
%onnx::Conv_1023 = Identity(%onnx::Conv_990)
%onnx::Conv_1020 = Identity(%onnx::Conv_990)
%onnx::Conv_1017 = Identity(%onnx::Conv_990)
%onnx::Conv_1014 = Identity(%onnx::Conv_990)
%onnx::Conv_1011 = Identity(%onnx::Conv_990)
%onnx::Conv_1008 = Identity(%onnx::Conv_990)
%onnx::Conv_1005 = Identity(%onnx::Conv_990)
%onnx::Conv_1002 = Identity(%onnx::Conv_990)
%onnx::Conv_999 = Identity(%onnx::Conv_990)
%onnx::Conv_996 = Identity(%onnx::Conv_990)
%onnx::Conv_993 = Identity(%onnx::Conv_990)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_986, %onnx::Conv_987)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1169, %onnx::Conv_1170)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1172, %onnx::Conv_1173)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_1175, %onnx::Conv_1176)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%984 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %984
}
|
val_accuracy
| 93.048877
| 1,940,006,912
| 6,491,146
|
{'zcp_epe_nas': 108.43759949501758, 'zcp_fisher': 16.726016998291016, 'zcp_flops': 31040110592.0, 'zcp_grad_norm': 73.83296966552734, 'zcp_grasp': -0.01971435546875, 'zcp_jacov': -16.05419300124337, 'zcp_l2_norm': 1188.4158935546875, 'zcp_nwot': 226.19810330810108, 'zcp_params': 6491146.0, 'zcp_plain': 0.026370313018560004, 'zcp_snip': 452.4458923339844, 'zcp_synflow': 119.98014174951805, 'zcp_zen': 109.62992095947266, 'zcp_val_accuracy': 0.9295873641967771}
| |
NASBench101_222884
|
NASBench101
|
222884
|
870e3d638312de8ce2ea119e1acdeb68
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_554[FLOAT, 128x3x3x3]
%onnx::Conv_555[FLOAT, 128]
%onnx::Conv_557[FLOAT, 64x128x1x1]
%onnx::Conv_558[FLOAT, 64]
%onnx::Conv_560[FLOAT, 64x64x3x3]
%onnx::Conv_563[FLOAT, 64x64x1x1]
%onnx::Conv_566[FLOAT, 64x128x1x1]
%onnx::Conv_569[FLOAT, 64x64x3x3]
%onnx::Conv_572[FLOAT, 64x64x1x1]
%onnx::Conv_575[FLOAT, 64x128x1x1]
%onnx::Conv_578[FLOAT, 64x64x3x3]
%onnx::Conv_581[FLOAT, 64x64x1x1]
%onnx::Conv_584[FLOAT, 128x128x1x1]
%onnx::Conv_587[FLOAT, 128x128x3x3]
%onnx::Conv_590[FLOAT, 128x128x1x1]
%onnx::Conv_593[FLOAT, 128x256x1x1]
%onnx::Conv_596[FLOAT, 128x128x3x3]
%onnx::Conv_599[FLOAT, 128x128x1x1]
%onnx::Conv_602[FLOAT, 128x256x1x1]
%onnx::Conv_605[FLOAT, 128x128x3x3]
%onnx::Conv_608[FLOAT, 128x128x1x1]
%onnx::Conv_611[FLOAT, 256x256x1x1]
%onnx::Conv_612[FLOAT, 256]
%onnx::Conv_614[FLOAT, 256x256x3x3]
%onnx::Conv_617[FLOAT, 256x256x1x1]
%onnx::Conv_620[FLOAT, 256x512x1x1]
%onnx::Conv_623[FLOAT, 256x256x3x3]
%onnx::Conv_626[FLOAT, 256x256x1x1]
%onnx::Conv_629[FLOAT, 256x512x1x1]
%onnx::Conv_632[FLOAT, 256x256x3x3]
%onnx::Conv_635[FLOAT, 256x256x1x1]
) {
%onnx::Conv_636 = Identity(%onnx::Conv_612)
%onnx::Conv_633 = Identity(%onnx::Conv_612)
%onnx::Conv_630 = Identity(%onnx::Conv_612)
%onnx::Conv_627 = Identity(%onnx::Conv_612)
%onnx::Conv_624 = Identity(%onnx::Conv_612)
%onnx::Conv_621 = Identity(%onnx::Conv_612)
%onnx::Conv_618 = Identity(%onnx::Conv_612)
%onnx::Conv_615 = Identity(%onnx::Conv_612)
%onnx::Conv_609 = Identity(%onnx::Conv_555)
%onnx::Conv_606 = Identity(%onnx::Conv_555)
%onnx::Conv_603 = Identity(%onnx::Conv_555)
%onnx::Conv_600 = Identity(%onnx::Conv_555)
%onnx::Conv_597 = Identity(%onnx::Conv_555)
%onnx::Conv_594 = Identity(%onnx::Conv_555)
%onnx::Conv_591 = Identity(%onnx::Conv_555)
%onnx::Conv_588 = Identity(%onnx::Conv_555)
%onnx::Conv_585 = Identity(%onnx::Conv_555)
%onnx::Conv_582 = Identity(%onnx::Conv_558)
%onnx::Conv_579 = Identity(%onnx::Conv_558)
%onnx::Conv_576 = Identity(%onnx::Conv_558)
%onnx::Conv_573 = Identity(%onnx::Conv_558)
%onnx::Conv_570 = Identity(%onnx::Conv_558)
%onnx::Conv_567 = Identity(%onnx::Conv_558)
%onnx::Conv_564 = Identity(%onnx::Conv_558)
%onnx::Conv_561 = Identity(%onnx::Conv_558)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_554, %onnx::Conv_555)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_557, %onnx::Conv_558)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_560, %onnx::Conv_561)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_563, %onnx::Conv_564)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_566, %onnx::Conv_567)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_569, %onnx::Conv_570)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_572, %onnx::Conv_573)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_575, %onnx::Conv_576)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_578, %onnx::Conv_579)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_581, %onnx::Conv_582)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_584, %onnx::Conv_585)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_587, %onnx::Conv_588)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_590, %onnx::Conv_591)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_593, %onnx::Conv_594)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_596, %onnx::Conv_597)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_599, %onnx::Conv_600)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_602, %onnx::Conv_603)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_605, %onnx::Conv_606)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_608, %onnx::Conv_609)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_611, %onnx::Conv_612)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_614, %onnx::Conv_615)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_617, %onnx::Conv_618)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_620, %onnx::Conv_621)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_623, %onnx::Conv_624)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_626, %onnx::Conv_627)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_629, %onnx::Conv_630)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_632, %onnx::Conv_633)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_635, %onnx::Conv_636)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%552 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %552
}
|
val_accuracy
| 89.252806
| 905,586,688
| 3,031,562
|
{'zcp_epe_nas': 91.32308595736421, 'zcp_fisher': 8.541971206665039, 'zcp_flops': 14489387008.0, 'zcp_grad_norm': 42.2202033996582, 'zcp_grasp': -0.8838043212890621, 'zcp_jacov': -16.059965015899174, 'zcp_l2_norm': 498.5306396484375, 'zcp_nwot': 214.1014163875445, 'zcp_params': 3031562.0, 'zcp_plain': 0.000776783097535, 'zcp_snip': 265.9876708984375, 'zcp_synflow': 91.23948438325937, 'zcp_zen': 61.94529342651367, 'zcp_val_accuracy': 0.908954322338104}
| |
NASBench101_157803
|
NASBench101
|
157803
|
5f8861b2d19fd345ed13072efc7b4f6a
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_635[FLOAT, 128x3x3x3]
%onnx::Conv_636[FLOAT, 128]
%onnx::Conv_638[FLOAT, 64x128x1x1]
%onnx::Conv_639[FLOAT, 64]
%onnx::Conv_641[FLOAT, 64x64x3x3]
%onnx::Conv_644[FLOAT, 64x128x1x1]
%onnx::Conv_647[FLOAT, 64x64x1x1]
%onnx::Conv_650[FLOAT, 64x128x1x1]
%onnx::Conv_653[FLOAT, 64x64x3x3]
%onnx::Conv_656[FLOAT, 64x128x1x1]
%onnx::Conv_659[FLOAT, 64x64x1x1]
%onnx::Conv_662[FLOAT, 64x128x1x1]
%onnx::Conv_665[FLOAT, 64x64x3x3]
%onnx::Conv_668[FLOAT, 64x128x1x1]
%onnx::Conv_671[FLOAT, 64x64x1x1]
%onnx::Conv_674[FLOAT, 128x128x1x1]
%onnx::Conv_677[FLOAT, 128x128x3x3]
%onnx::Conv_680[FLOAT, 128x128x1x1]
%onnx::Conv_683[FLOAT, 128x128x1x1]
%onnx::Conv_686[FLOAT, 128x256x1x1]
%onnx::Conv_689[FLOAT, 128x128x3x3]
%onnx::Conv_692[FLOAT, 128x256x1x1]
%onnx::Conv_695[FLOAT, 128x128x1x1]
%onnx::Conv_698[FLOAT, 128x256x1x1]
%onnx::Conv_701[FLOAT, 128x128x3x3]
%onnx::Conv_704[FLOAT, 128x256x1x1]
%onnx::Conv_707[FLOAT, 128x128x1x1]
%onnx::Conv_710[FLOAT, 256x256x1x1]
%onnx::Conv_711[FLOAT, 256]
%onnx::Conv_713[FLOAT, 256x256x3x3]
%onnx::Conv_716[FLOAT, 256x256x1x1]
%onnx::Conv_719[FLOAT, 256x256x1x1]
%onnx::Conv_722[FLOAT, 256x512x1x1]
%onnx::Conv_725[FLOAT, 256x256x3x3]
%onnx::Conv_728[FLOAT, 256x512x1x1]
%onnx::Conv_731[FLOAT, 256x256x1x1]
%onnx::Conv_734[FLOAT, 256x512x1x1]
%onnx::Conv_737[FLOAT, 256x256x3x3]
%onnx::Conv_740[FLOAT, 256x512x1x1]
%onnx::Conv_743[FLOAT, 256x256x1x1]
) {
%onnx::Conv_744 = Identity(%onnx::Conv_711)
%onnx::Conv_741 = Identity(%onnx::Conv_711)
%onnx::Conv_738 = Identity(%onnx::Conv_711)
%onnx::Conv_735 = Identity(%onnx::Conv_711)
%onnx::Conv_732 = Identity(%onnx::Conv_711)
%onnx::Conv_729 = Identity(%onnx::Conv_711)
%onnx::Conv_726 = Identity(%onnx::Conv_711)
%onnx::Conv_723 = Identity(%onnx::Conv_711)
%onnx::Conv_720 = Identity(%onnx::Conv_711)
%onnx::Conv_717 = Identity(%onnx::Conv_711)
%onnx::Conv_714 = Identity(%onnx::Conv_711)
%onnx::Conv_708 = Identity(%onnx::Conv_636)
%onnx::Conv_705 = Identity(%onnx::Conv_636)
%onnx::Conv_702 = Identity(%onnx::Conv_636)
%onnx::Conv_699 = Identity(%onnx::Conv_636)
%onnx::Conv_696 = Identity(%onnx::Conv_636)
%onnx::Conv_693 = Identity(%onnx::Conv_636)
%onnx::Conv_690 = Identity(%onnx::Conv_636)
%onnx::Conv_687 = Identity(%onnx::Conv_636)
%onnx::Conv_684 = Identity(%onnx::Conv_636)
%onnx::Conv_681 = Identity(%onnx::Conv_636)
%onnx::Conv_678 = Identity(%onnx::Conv_636)
%onnx::Conv_675 = Identity(%onnx::Conv_636)
%onnx::Conv_672 = Identity(%onnx::Conv_639)
%onnx::Conv_669 = Identity(%onnx::Conv_639)
%onnx::Conv_666 = Identity(%onnx::Conv_639)
%onnx::Conv_663 = Identity(%onnx::Conv_639)
%onnx::Conv_660 = Identity(%onnx::Conv_639)
%onnx::Conv_657 = Identity(%onnx::Conv_639)
%onnx::Conv_654 = Identity(%onnx::Conv_639)
%onnx::Conv_651 = Identity(%onnx::Conv_639)
%onnx::Conv_648 = Identity(%onnx::Conv_639)
%onnx::Conv_645 = Identity(%onnx::Conv_639)
%onnx::Conv_642 = Identity(%onnx::Conv_639)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_635, %onnx::Conv_636)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_638, %onnx::Conv_639)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_641, %onnx::Conv_642)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_644, %onnx::Conv_645)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_647, %onnx::Conv_648)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_650, %onnx::Conv_651)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_653, %onnx::Conv_654)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_656, %onnx::Conv_657)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_659, %onnx::Conv_660)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_662, %onnx::Conv_663)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%633 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %633
}
|
val_accuracy
| 91.516429
| 1,042,556,928
| 3,468,426
|
{'zcp_epe_nas': 85.06717125493086, 'zcp_fisher': 6.560801029205322, 'zcp_flops': 16680910848.0, 'zcp_grad_norm': 57.141517639160156, 'zcp_grasp': -2.929168701171875, 'zcp_jacov': -16.048795380464174, 'zcp_l2_norm': 694.3871459960938, 'zcp_nwot': 218.25327136719775, 'zcp_params': 3468426.0, 'zcp_plain': 0.052737914025783005, 'zcp_snip': 330.10955810546875, 'zcp_synflow': 84.49689092307534, 'zcp_zen': 69.5622329711914, 'zcp_val_accuracy': 0.9124599099159241}
| |
NASBench101_56367
|
NASBench101
|
56367
|
22482c61c8b087f72a39115936f16b35
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_743[FLOAT, 128x3x3x3]
%onnx::Conv_744[FLOAT, 128]
%onnx::Conv_746[FLOAT, 64x128x1x1]
%onnx::Conv_747[FLOAT, 64]
%onnx::Conv_749[FLOAT, 64x64x3x3]
%onnx::Conv_752[FLOAT, 64x128x1x1]
%onnx::Conv_755[FLOAT, 64x64x3x3]
%onnx::Conv_758[FLOAT, 64x64x3x3]
%onnx::Conv_761[FLOAT, 64x128x1x1]
%onnx::Conv_764[FLOAT, 64x64x3x3]
%onnx::Conv_767[FLOAT, 64x128x1x1]
%onnx::Conv_770[FLOAT, 64x64x3x3]
%onnx::Conv_773[FLOAT, 64x64x3x3]
%onnx::Conv_776[FLOAT, 64x128x1x1]
%onnx::Conv_779[FLOAT, 64x64x3x3]
%onnx::Conv_782[FLOAT, 64x128x1x1]
%onnx::Conv_785[FLOAT, 64x64x3x3]
%onnx::Conv_788[FLOAT, 64x64x3x3]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 128x128x3x3]
%onnx::Conv_797[FLOAT, 128x128x1x1]
%onnx::Conv_800[FLOAT, 128x128x3x3]
%onnx::Conv_803[FLOAT, 128x128x3x3]
%onnx::Conv_806[FLOAT, 128x256x1x1]
%onnx::Conv_809[FLOAT, 128x128x3x3]
%onnx::Conv_812[FLOAT, 128x256x1x1]
%onnx::Conv_815[FLOAT, 128x128x3x3]
%onnx::Conv_818[FLOAT, 128x128x3x3]
%onnx::Conv_821[FLOAT, 128x256x1x1]
%onnx::Conv_824[FLOAT, 128x128x3x3]
%onnx::Conv_827[FLOAT, 128x256x1x1]
%onnx::Conv_830[FLOAT, 128x128x3x3]
%onnx::Conv_833[FLOAT, 128x128x3x3]
%onnx::Conv_836[FLOAT, 256x256x1x1]
%onnx::Conv_837[FLOAT, 256]
%onnx::Conv_839[FLOAT, 256x256x3x3]
%onnx::Conv_842[FLOAT, 256x256x1x1]
%onnx::Conv_845[FLOAT, 256x256x3x3]
%onnx::Conv_848[FLOAT, 256x256x3x3]
%onnx::Conv_851[FLOAT, 256x512x1x1]
%onnx::Conv_854[FLOAT, 256x256x3x3]
%onnx::Conv_857[FLOAT, 256x512x1x1]
%onnx::Conv_860[FLOAT, 256x256x3x3]
%onnx::Conv_863[FLOAT, 256x256x3x3]
%onnx::Conv_866[FLOAT, 256x512x1x1]
%onnx::Conv_869[FLOAT, 256x256x3x3]
%onnx::Conv_872[FLOAT, 256x512x1x1]
%onnx::Conv_875[FLOAT, 256x256x3x3]
%onnx::Conv_878[FLOAT, 256x256x3x3]
) {
%onnx::Conv_879 = Identity(%onnx::Conv_837)
%onnx::Conv_876 = Identity(%onnx::Conv_837)
%onnx::Conv_873 = Identity(%onnx::Conv_837)
%onnx::Conv_870 = Identity(%onnx::Conv_837)
%onnx::Conv_867 = Identity(%onnx::Conv_837)
%onnx::Conv_864 = Identity(%onnx::Conv_837)
%onnx::Conv_861 = Identity(%onnx::Conv_837)
%onnx::Conv_858 = Identity(%onnx::Conv_837)
%onnx::Conv_855 = Identity(%onnx::Conv_837)
%onnx::Conv_852 = Identity(%onnx::Conv_837)
%onnx::Conv_849 = Identity(%onnx::Conv_837)
%onnx::Conv_846 = Identity(%onnx::Conv_837)
%onnx::Conv_843 = Identity(%onnx::Conv_837)
%onnx::Conv_840 = Identity(%onnx::Conv_837)
%onnx::Conv_834 = Identity(%onnx::Conv_744)
%onnx::Conv_831 = Identity(%onnx::Conv_744)
%onnx::Conv_828 = Identity(%onnx::Conv_744)
%onnx::Conv_825 = Identity(%onnx::Conv_744)
%onnx::Conv_822 = Identity(%onnx::Conv_744)
%onnx::Conv_819 = Identity(%onnx::Conv_744)
%onnx::Conv_816 = Identity(%onnx::Conv_744)
%onnx::Conv_813 = Identity(%onnx::Conv_744)
%onnx::Conv_810 = Identity(%onnx::Conv_744)
%onnx::Conv_807 = Identity(%onnx::Conv_744)
%onnx::Conv_804 = Identity(%onnx::Conv_744)
%onnx::Conv_801 = Identity(%onnx::Conv_744)
%onnx::Conv_798 = Identity(%onnx::Conv_744)
%onnx::Conv_795 = Identity(%onnx::Conv_744)
%onnx::Conv_792 = Identity(%onnx::Conv_744)
%onnx::Conv_789 = Identity(%onnx::Conv_747)
%onnx::Conv_786 = Identity(%onnx::Conv_747)
%onnx::Conv_783 = Identity(%onnx::Conv_747)
%onnx::Conv_780 = Identity(%onnx::Conv_747)
%onnx::Conv_777 = Identity(%onnx::Conv_747)
%onnx::Conv_774 = Identity(%onnx::Conv_747)
%onnx::Conv_771 = Identity(%onnx::Conv_747)
%onnx::Conv_768 = Identity(%onnx::Conv_747)
%onnx::Conv_765 = Identity(%onnx::Conv_747)
%onnx::Conv_762 = Identity(%onnx::Conv_747)
%onnx::Conv_759 = Identity(%onnx::Conv_747)
%onnx::Conv_756 = Identity(%onnx::Conv_747)
%onnx::Conv_753 = Identity(%onnx::Conv_747)
%onnx::Conv_750 = Identity(%onnx::Conv_747)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_743, %onnx::Conv_744)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%741 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %741
}
|
val_accuracy
| 92.107373
| 2,328,766,464
| 7,857,930
|
{'zcp_epe_nas': 138.72647944488443, 'zcp_fisher': 8.175954818725586, 'zcp_flops': 37260263424.0, 'zcp_grad_norm': 52.50331115722656, 'zcp_grasp': 0.7249755859375, 'zcp_jacov': -16.049361274853467, 'zcp_l2_norm': 843.6376953125, 'zcp_nwot': 221.03450351209202, 'zcp_params': 7857930.0, 'zcp_plain': -0.038196314126253, 'zcp_snip': 351.27191162109375, 'zcp_synflow': 127.29911294881249, 'zcp_zen': 100.85519409179688, 'zcp_val_accuracy': 0.9027444124221801}
| |
NASBench101_236434
|
NASBench101
|
236434
|
8f116586351db7a329450ee6d6d8f4c2
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_833[FLOAT, 128x3x3x3]
%onnx::Conv_834[FLOAT, 128]
%onnx::Conv_836[FLOAT, 43x128x1x1]
%onnx::Conv_837[FLOAT, 43]
%onnx::Conv_839[FLOAT, 43x43x3x3]
%onnx::Conv_842[FLOAT, 43x43x1x1]
%onnx::Conv_845[FLOAT, 43x43x3x3]
%onnx::Conv_848[FLOAT, 42x128x1x1]
%onnx::Conv_849[FLOAT, 42]
%onnx::Conv_851[FLOAT, 43x128x1x1]
%onnx::Conv_854[FLOAT, 43x43x3x3]
%onnx::Conv_857[FLOAT, 43x43x1x1]
%onnx::Conv_860[FLOAT, 43x43x3x3]
%onnx::Conv_863[FLOAT, 42x128x1x1]
%onnx::Conv_866[FLOAT, 43x128x1x1]
%onnx::Conv_869[FLOAT, 43x43x3x3]
%onnx::Conv_872[FLOAT, 43x43x1x1]
%onnx::Conv_875[FLOAT, 43x43x3x3]
%onnx::Conv_878[FLOAT, 42x128x1x1]
%onnx::Conv_881[FLOAT, 86x128x1x1]
%onnx::Conv_882[FLOAT, 86]
%onnx::Conv_884[FLOAT, 86x86x3x3]
%onnx::Conv_887[FLOAT, 85x85x1x1]
%onnx::Conv_888[FLOAT, 85]
%onnx::Conv_890[FLOAT, 85x85x3x3]
%onnx::Conv_893[FLOAT, 85x128x1x1]
%onnx::Conv_896[FLOAT, 86x256x1x1]
%onnx::Conv_899[FLOAT, 86x86x3x3]
%onnx::Conv_902[FLOAT, 85x85x1x1]
%onnx::Conv_905[FLOAT, 85x85x3x3]
%onnx::Conv_908[FLOAT, 85x256x1x1]
%onnx::Conv_911[FLOAT, 86x256x1x1]
%onnx::Conv_914[FLOAT, 86x86x3x3]
%onnx::Conv_917[FLOAT, 85x85x1x1]
%onnx::Conv_920[FLOAT, 85x85x3x3]
%onnx::Conv_923[FLOAT, 85x256x1x1]
%onnx::Conv_926[FLOAT, 171x256x1x1]
%onnx::Conv_927[FLOAT, 171]
%onnx::Conv_929[FLOAT, 171x171x3x3]
%onnx::Conv_932[FLOAT, 171x171x1x1]
%onnx::Conv_935[FLOAT, 171x171x3x3]
%onnx::Conv_938[FLOAT, 170x256x1x1]
%onnx::Conv_939[FLOAT, 170]
%onnx::Conv_941[FLOAT, 171x512x1x1]
%onnx::Conv_944[FLOAT, 171x171x3x3]
%onnx::Conv_947[FLOAT, 171x171x1x1]
%onnx::Conv_950[FLOAT, 171x171x3x3]
%onnx::Conv_953[FLOAT, 170x512x1x1]
%onnx::Conv_956[FLOAT, 171x512x1x1]
%onnx::Conv_959[FLOAT, 171x171x3x3]
%onnx::Conv_962[FLOAT, 171x171x1x1]
%onnx::Conv_965[FLOAT, 171x171x3x3]
%onnx::Conv_968[FLOAT, 170x512x1x1]
) {
%onnx::Conv_969 = Identity(%onnx::Conv_939)
%onnx::Conv_966 = Identity(%onnx::Conv_927)
%onnx::Conv_963 = Identity(%onnx::Conv_927)
%onnx::Conv_960 = Identity(%onnx::Conv_927)
%onnx::Conv_957 = Identity(%onnx::Conv_927)
%onnx::Conv_954 = Identity(%onnx::Conv_939)
%onnx::Conv_951 = Identity(%onnx::Conv_927)
%onnx::Conv_948 = Identity(%onnx::Conv_927)
%onnx::Conv_945 = Identity(%onnx::Conv_927)
%onnx::Conv_942 = Identity(%onnx::Conv_927)
%onnx::Conv_936 = Identity(%onnx::Conv_927)
%onnx::Conv_933 = Identity(%onnx::Conv_927)
%onnx::Conv_930 = Identity(%onnx::Conv_927)
%onnx::Conv_924 = Identity(%onnx::Conv_888)
%onnx::Conv_921 = Identity(%onnx::Conv_888)
%onnx::Conv_918 = Identity(%onnx::Conv_888)
%onnx::Conv_915 = Identity(%onnx::Conv_882)
%onnx::Conv_912 = Identity(%onnx::Conv_882)
%onnx::Conv_909 = Identity(%onnx::Conv_888)
%onnx::Conv_906 = Identity(%onnx::Conv_888)
%onnx::Conv_903 = Identity(%onnx::Conv_888)
%onnx::Conv_900 = Identity(%onnx::Conv_882)
%onnx::Conv_897 = Identity(%onnx::Conv_882)
%onnx::Conv_894 = Identity(%onnx::Conv_888)
%onnx::Conv_891 = Identity(%onnx::Conv_888)
%onnx::Conv_885 = Identity(%onnx::Conv_882)
%onnx::Conv_879 = Identity(%onnx::Conv_849)
%onnx::Conv_876 = Identity(%onnx::Conv_837)
%onnx::Conv_873 = Identity(%onnx::Conv_837)
%onnx::Conv_870 = Identity(%onnx::Conv_837)
%onnx::Conv_867 = Identity(%onnx::Conv_837)
%onnx::Conv_864 = Identity(%onnx::Conv_849)
%onnx::Conv_861 = Identity(%onnx::Conv_837)
%onnx::Conv_858 = Identity(%onnx::Conv_837)
%onnx::Conv_855 = Identity(%onnx::Conv_837)
%onnx::Conv_852 = Identity(%onnx::Conv_837)
%onnx::Conv_846 = Identity(%onnx::Conv_837)
%onnx::Conv_843 = Identity(%onnx::Conv_837)
%onnx::Conv_840 = Identity(%onnx::Conv_837)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_833, %onnx::Conv_834)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_6_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_7_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_8_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_6_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_7_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_8_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_6_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_7_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_8_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_4_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_7_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_8_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_4_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_7_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_8_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_4_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_7_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_8_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_6_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_7_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_8_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_6_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_7_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_8_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_6_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_7_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_8_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%831 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %831
}
|
val_accuracy
| 90.715146
| 838,486,144
| 2,784,944
|
{'zcp_epe_nas': 88.9174197175155, 'zcp_fisher': 268.44390869140625, 'zcp_flops': 13415778304.0, 'zcp_grad_norm': 313.5303039550781, 'zcp_grasp': 108.50390625, 'zcp_jacov': -16.051976184358274, 'zcp_l2_norm': 762.4105224609375, 'zcp_nwot': 215.86219737931518, 'zcp_params': 2784944.0, 'zcp_plain': 0.019270293414592, 'zcp_snip': 1412.0848388671875, 'zcp_synflow': 115.82338854259866, 'zcp_zen': 79.61708068847656, 'zcp_val_accuracy': 0.869691491127014}
| |
NASBench101_204830
|
NASBench101
|
204830
|
7c058d19925202db5487de8bf40e656d
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_878[FLOAT, 128x3x3x3]
%onnx::Conv_879[FLOAT, 128]
%onnx::Conv_881[FLOAT, 128x128x1x1]
%onnx::Conv_884[FLOAT, 128x128x1x1]
%onnx::Conv_887[FLOAT, 128x128x1x1]
%onnx::Conv_890[FLOAT, 128x128x1x1]
%onnx::Conv_893[FLOAT, 128x128x1x1]
%onnx::Conv_896[FLOAT, 128x128x3x3]
%onnx::Conv_899[FLOAT, 128x128x1x1]
%onnx::Conv_902[FLOAT, 128x128x1x1]
%onnx::Conv_905[FLOAT, 128x128x1x1]
%onnx::Conv_908[FLOAT, 128x128x1x1]
%onnx::Conv_911[FLOAT, 128x128x1x1]
%onnx::Conv_914[FLOAT, 128x128x3x3]
%onnx::Conv_917[FLOAT, 128x128x1x1]
%onnx::Conv_920[FLOAT, 128x128x1x1]
%onnx::Conv_923[FLOAT, 128x128x1x1]
%onnx::Conv_926[FLOAT, 128x128x1x1]
%onnx::Conv_929[FLOAT, 128x128x1x1]
%onnx::Conv_932[FLOAT, 128x128x3x3]
%onnx::Conv_935[FLOAT, 256x128x1x1]
%onnx::Conv_936[FLOAT, 256]
%onnx::Conv_938[FLOAT, 256x256x1x1]
%onnx::Conv_941[FLOAT, 256x256x1x1]
%onnx::Conv_944[FLOAT, 256x128x1x1]
%onnx::Conv_947[FLOAT, 256x128x1x1]
%onnx::Conv_950[FLOAT, 256x256x3x3]
%onnx::Conv_953[FLOAT, 256x256x1x1]
%onnx::Conv_956[FLOAT, 256x256x1x1]
%onnx::Conv_959[FLOAT, 256x256x1x1]
%onnx::Conv_962[FLOAT, 256x256x1x1]
%onnx::Conv_965[FLOAT, 256x256x1x1]
%onnx::Conv_968[FLOAT, 256x256x3x3]
%onnx::Conv_971[FLOAT, 256x256x1x1]
%onnx::Conv_974[FLOAT, 256x256x1x1]
%onnx::Conv_977[FLOAT, 256x256x1x1]
%onnx::Conv_980[FLOAT, 256x256x1x1]
%onnx::Conv_983[FLOAT, 256x256x1x1]
%onnx::Conv_986[FLOAT, 256x256x3x3]
%onnx::Conv_989[FLOAT, 512x256x1x1]
%onnx::Conv_990[FLOAT, 512]
%onnx::Conv_992[FLOAT, 512x512x1x1]
%onnx::Conv_995[FLOAT, 512x512x1x1]
%onnx::Conv_998[FLOAT, 512x256x1x1]
%onnx::Conv_1001[FLOAT, 512x256x1x1]
%onnx::Conv_1004[FLOAT, 512x512x3x3]
%onnx::Conv_1007[FLOAT, 512x512x1x1]
%onnx::Conv_1010[FLOAT, 512x512x1x1]
%onnx::Conv_1013[FLOAT, 512x512x1x1]
%onnx::Conv_1016[FLOAT, 512x512x1x1]
%onnx::Conv_1019[FLOAT, 512x512x1x1]
%onnx::Conv_1022[FLOAT, 512x512x3x3]
%onnx::Conv_1025[FLOAT, 512x512x1x1]
%onnx::Conv_1028[FLOAT, 512x512x1x1]
%onnx::Conv_1031[FLOAT, 512x512x1x1]
%onnx::Conv_1034[FLOAT, 512x512x1x1]
%onnx::Conv_1037[FLOAT, 512x512x1x1]
%onnx::Conv_1040[FLOAT, 512x512x3x3]
) {
%onnx::Conv_1041 = Identity(%onnx::Conv_990)
%onnx::Conv_1038 = Identity(%onnx::Conv_990)
%onnx::Conv_1035 = Identity(%onnx::Conv_990)
%onnx::Conv_1032 = Identity(%onnx::Conv_990)
%onnx::Conv_1029 = Identity(%onnx::Conv_990)
%onnx::Conv_1026 = Identity(%onnx::Conv_990)
%onnx::Conv_1023 = Identity(%onnx::Conv_990)
%onnx::Conv_1020 = Identity(%onnx::Conv_990)
%onnx::Conv_1017 = Identity(%onnx::Conv_990)
%onnx::Conv_1014 = Identity(%onnx::Conv_990)
%onnx::Conv_1011 = Identity(%onnx::Conv_990)
%onnx::Conv_1008 = Identity(%onnx::Conv_990)
%onnx::Conv_1005 = Identity(%onnx::Conv_990)
%onnx::Conv_1002 = Identity(%onnx::Conv_990)
%onnx::Conv_999 = Identity(%onnx::Conv_990)
%onnx::Conv_996 = Identity(%onnx::Conv_990)
%onnx::Conv_993 = Identity(%onnx::Conv_990)
%onnx::Conv_987 = Identity(%onnx::Conv_936)
%onnx::Conv_984 = Identity(%onnx::Conv_936)
%onnx::Conv_981 = Identity(%onnx::Conv_936)
%onnx::Conv_978 = Identity(%onnx::Conv_936)
%onnx::Conv_975 = Identity(%onnx::Conv_936)
%onnx::Conv_972 = Identity(%onnx::Conv_936)
%onnx::Conv_969 = Identity(%onnx::Conv_936)
%onnx::Conv_966 = Identity(%onnx::Conv_936)
%onnx::Conv_963 = Identity(%onnx::Conv_936)
%onnx::Conv_960 = Identity(%onnx::Conv_936)
%onnx::Conv_957 = Identity(%onnx::Conv_936)
%onnx::Conv_954 = Identity(%onnx::Conv_936)
%onnx::Conv_951 = Identity(%onnx::Conv_936)
%onnx::Conv_948 = Identity(%onnx::Conv_936)
%onnx::Conv_945 = Identity(%onnx::Conv_936)
%onnx::Conv_942 = Identity(%onnx::Conv_936)
%onnx::Conv_939 = Identity(%onnx::Conv_936)
%onnx::Conv_933 = Identity(%onnx::Conv_879)
%onnx::Conv_930 = Identity(%onnx::Conv_879)
%onnx::Conv_927 = Identity(%onnx::Conv_879)
%onnx::Conv_924 = Identity(%onnx::Conv_879)
%onnx::Conv_921 = Identity(%onnx::Conv_879)
%onnx::Conv_918 = Identity(%onnx::Conv_879)
%onnx::Conv_915 = Identity(%onnx::Conv_879)
%onnx::Conv_912 = Identity(%onnx::Conv_879)
%onnx::Conv_909 = Identity(%onnx::Conv_879)
%onnx::Conv_906 = Identity(%onnx::Conv_879)
%onnx::Conv_903 = Identity(%onnx::Conv_879)
%onnx::Conv_900 = Identity(%onnx::Conv_879)
%onnx::Conv_897 = Identity(%onnx::Conv_879)
%onnx::Conv_894 = Identity(%onnx::Conv_879)
%onnx::Conv_891 = Identity(%onnx::Conv_879)
%onnx::Conv_888 = Identity(%onnx::Conv_879)
%onnx::Conv_885 = Identity(%onnx::Conv_879)
%onnx::Conv_882 = Identity(%onnx::Conv_879)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_878, %onnx::Conv_879)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%876 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %876
}
|
val_accuracy
| 93.108976
| 4,168,361,984
| 14,000,266
|
{'zcp_epe_nas': 148.8253857280779, 'zcp_fisher': 10.290794372558594, 'zcp_flops': 66693791744.0, 'zcp_grad_norm': 53.12247848510742, 'zcp_grasp': -2.67144775390625, 'zcp_jacov': -16.061401978346865, 'zcp_l2_norm': 1226.725341796875, 'zcp_nwot': 234.2107216645086, 'zcp_params': 14000266.0, 'zcp_plain': 0.036722738295793006, 'zcp_snip': 434.89190673828125, 'zcp_synflow': 119.9575192066701, 'zcp_zen': 100.75668334960938, 'zcp_val_accuracy': 0.9364984035491941}
| |
NASBench101_184928
|
NASBench101
|
184928
|
6fd821d1e78331e9965f977ded6d8e51
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_887[FLOAT, 128x3x3x3]
%onnx::Conv_888[FLOAT, 128]
%onnx::Conv_890[FLOAT, 64x128x1x1]
%onnx::Conv_891[FLOAT, 64]
%onnx::Conv_893[FLOAT, 64x64x1x1]
%onnx::Conv_896[FLOAT, 64x128x1x1]
%onnx::Conv_899[FLOAT, 64x64x1x1]
%onnx::Conv_902[FLOAT, 64x64x1x1]
%onnx::Conv_905[FLOAT, 64x64x1x1]
%onnx::Conv_908[FLOAT, 64x128x1x1]
%onnx::Conv_911[FLOAT, 64x64x1x1]
%onnx::Conv_914[FLOAT, 64x128x1x1]
%onnx::Conv_917[FLOAT, 64x64x1x1]
%onnx::Conv_920[FLOAT, 64x64x1x1]
%onnx::Conv_923[FLOAT, 64x64x1x1]
%onnx::Conv_926[FLOAT, 64x128x1x1]
%onnx::Conv_929[FLOAT, 64x64x1x1]
%onnx::Conv_932[FLOAT, 64x128x1x1]
%onnx::Conv_935[FLOAT, 64x64x1x1]
%onnx::Conv_938[FLOAT, 64x64x1x1]
%onnx::Conv_941[FLOAT, 64x64x1x1]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%onnx::Conv_953[FLOAT, 128x128x1x1]
%onnx::Conv_956[FLOAT, 128x128x1x1]
%onnx::Conv_959[FLOAT, 128x128x1x1]
%onnx::Conv_962[FLOAT, 128x256x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x256x1x1]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 128x256x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x256x1x1]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x1x1]
%onnx::Conv_998[FLOAT, 256x256x1x1]
%onnx::Conv_999[FLOAT, 256]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 256x256x1x1]
%onnx::Conv_1007[FLOAT, 256x256x1x1]
%onnx::Conv_1010[FLOAT, 256x256x1x1]
%onnx::Conv_1013[FLOAT, 256x256x1x1]
%onnx::Conv_1016[FLOAT, 256x512x1x1]
%onnx::Conv_1019[FLOAT, 256x256x1x1]
%onnx::Conv_1022[FLOAT, 256x512x1x1]
%onnx::Conv_1025[FLOAT, 256x256x1x1]
%onnx::Conv_1028[FLOAT, 256x256x1x1]
%onnx::Conv_1031[FLOAT, 256x256x1x1]
%onnx::Conv_1034[FLOAT, 256x512x1x1]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 256x512x1x1]
%onnx::Conv_1043[FLOAT, 256x256x1x1]
%onnx::Conv_1046[FLOAT, 256x256x1x1]
%onnx::Conv_1049[FLOAT, 256x256x1x1]
) {
%onnx::Conv_1050 = Identity(%onnx::Conv_999)
%onnx::Conv_1047 = Identity(%onnx::Conv_999)
%onnx::Conv_1044 = Identity(%onnx::Conv_999)
%onnx::Conv_1041 = Identity(%onnx::Conv_999)
%onnx::Conv_1038 = Identity(%onnx::Conv_999)
%onnx::Conv_1035 = Identity(%onnx::Conv_999)
%onnx::Conv_1032 = Identity(%onnx::Conv_999)
%onnx::Conv_1029 = Identity(%onnx::Conv_999)
%onnx::Conv_1026 = Identity(%onnx::Conv_999)
%onnx::Conv_1023 = Identity(%onnx::Conv_999)
%onnx::Conv_1020 = Identity(%onnx::Conv_999)
%onnx::Conv_1017 = Identity(%onnx::Conv_999)
%onnx::Conv_1014 = Identity(%onnx::Conv_999)
%onnx::Conv_1011 = Identity(%onnx::Conv_999)
%onnx::Conv_1008 = Identity(%onnx::Conv_999)
%onnx::Conv_1005 = Identity(%onnx::Conv_999)
%onnx::Conv_1002 = Identity(%onnx::Conv_999)
%onnx::Conv_996 = Identity(%onnx::Conv_888)
%onnx::Conv_993 = Identity(%onnx::Conv_888)
%onnx::Conv_990 = Identity(%onnx::Conv_888)
%onnx::Conv_987 = Identity(%onnx::Conv_888)
%onnx::Conv_984 = Identity(%onnx::Conv_888)
%onnx::Conv_981 = Identity(%onnx::Conv_888)
%onnx::Conv_978 = Identity(%onnx::Conv_888)
%onnx::Conv_975 = Identity(%onnx::Conv_888)
%onnx::Conv_972 = Identity(%onnx::Conv_888)
%onnx::Conv_969 = Identity(%onnx::Conv_888)
%onnx::Conv_966 = Identity(%onnx::Conv_888)
%onnx::Conv_963 = Identity(%onnx::Conv_888)
%onnx::Conv_960 = Identity(%onnx::Conv_888)
%onnx::Conv_957 = Identity(%onnx::Conv_888)
%onnx::Conv_954 = Identity(%onnx::Conv_888)
%onnx::Conv_951 = Identity(%onnx::Conv_888)
%onnx::Conv_948 = Identity(%onnx::Conv_888)
%onnx::Conv_945 = Identity(%onnx::Conv_888)
%onnx::Conv_942 = Identity(%onnx::Conv_891)
%onnx::Conv_939 = Identity(%onnx::Conv_891)
%onnx::Conv_936 = Identity(%onnx::Conv_891)
%onnx::Conv_933 = Identity(%onnx::Conv_891)
%onnx::Conv_930 = Identity(%onnx::Conv_891)
%onnx::Conv_927 = Identity(%onnx::Conv_891)
%onnx::Conv_924 = Identity(%onnx::Conv_891)
%onnx::Conv_921 = Identity(%onnx::Conv_891)
%onnx::Conv_918 = Identity(%onnx::Conv_891)
%onnx::Conv_915 = Identity(%onnx::Conv_891)
%onnx::Conv_912 = Identity(%onnx::Conv_891)
%onnx::Conv_909 = Identity(%onnx::Conv_891)
%onnx::Conv_906 = Identity(%onnx::Conv_891)
%onnx::Conv_903 = Identity(%onnx::Conv_891)
%onnx::Conv_900 = Identity(%onnx::Conv_891)
%onnx::Conv_897 = Identity(%onnx::Conv_891)
%onnx::Conv_894 = Identity(%onnx::Conv_891)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_887, %onnx::Conv_888)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%885 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %885
}
|
val_accuracy
| 82.301682
| 595,077,120
| 1,925,514
|
{'zcp_epe_nas': 115.23082945646541, 'zcp_fisher': 112.47966003417969, 'zcp_flops': 9521233920.0, 'zcp_grad_norm': 255.2000732421875, 'zcp_grasp': -481.958984375, 'zcp_jacov': -16.047772000145287, 'zcp_l2_norm': 994.0467529296875, 'zcp_nwot': 224.67800307669714, 'zcp_params': 1925514.0, 'zcp_plain': 0.061718445271253, 'zcp_snip': 1162.5137939453125, 'zcp_synflow': 121.4026891231667, 'zcp_zen': 82.18360900878906, 'zcp_val_accuracy': 0.8848156929016111}
| |
NASBench101_228777
|
NASBench101
|
228777
|
8a93e2f290f7ecf8d3e1228014e4f419
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_653[FLOAT, 128x3x3x3]
%onnx::Conv_654[FLOAT, 128]
%onnx::Conv_656[FLOAT, 128x128x1x1]
%onnx::Conv_659[FLOAT, 128x128x3x3]
%onnx::Conv_662[FLOAT, 128x128x3x3]
%onnx::Conv_665[FLOAT, 128x128x1x1]
%onnx::Conv_668[FLOAT, 128x128x1x1]
%onnx::Conv_671[FLOAT, 128x128x3x3]
%onnx::Conv_674[FLOAT, 128x128x3x3]
%onnx::Conv_677[FLOAT, 128x128x1x1]
%onnx::Conv_680[FLOAT, 128x128x1x1]
%onnx::Conv_683[FLOAT, 128x128x3x3]
%onnx::Conv_686[FLOAT, 128x128x3x3]
%onnx::Conv_689[FLOAT, 128x128x1x1]
%onnx::Conv_692[FLOAT, 256x128x1x1]
%onnx::Conv_693[FLOAT, 256]
%onnx::Conv_695[FLOAT, 256x256x3x3]
%onnx::Conv_698[FLOAT, 256x256x3x3]
%onnx::Conv_701[FLOAT, 256x128x1x1]
%onnx::Conv_704[FLOAT, 256x256x1x1]
%onnx::Conv_707[FLOAT, 256x256x3x3]
%onnx::Conv_710[FLOAT, 256x256x3x3]
%onnx::Conv_713[FLOAT, 256x256x1x1]
%onnx::Conv_716[FLOAT, 256x256x1x1]
%onnx::Conv_719[FLOAT, 256x256x3x3]
%onnx::Conv_722[FLOAT, 256x256x3x3]
%onnx::Conv_725[FLOAT, 256x256x1x1]
%onnx::Conv_728[FLOAT, 512x256x1x1]
%onnx::Conv_729[FLOAT, 512]
%onnx::Conv_731[FLOAT, 512x512x3x3]
%onnx::Conv_734[FLOAT, 512x512x3x3]
%onnx::Conv_737[FLOAT, 512x256x1x1]
%onnx::Conv_740[FLOAT, 512x512x1x1]
%onnx::Conv_743[FLOAT, 512x512x3x3]
%onnx::Conv_746[FLOAT, 512x512x3x3]
%onnx::Conv_749[FLOAT, 512x512x1x1]
%onnx::Conv_752[FLOAT, 512x512x1x1]
%onnx::Conv_755[FLOAT, 512x512x3x3]
%onnx::Conv_758[FLOAT, 512x512x3x3]
%onnx::Conv_761[FLOAT, 512x512x1x1]
) {
%onnx::Conv_762 = Identity(%onnx::Conv_729)
%onnx::Conv_759 = Identity(%onnx::Conv_729)
%onnx::Conv_756 = Identity(%onnx::Conv_729)
%onnx::Conv_753 = Identity(%onnx::Conv_729)
%onnx::Conv_750 = Identity(%onnx::Conv_729)
%onnx::Conv_747 = Identity(%onnx::Conv_729)
%onnx::Conv_744 = Identity(%onnx::Conv_729)
%onnx::Conv_741 = Identity(%onnx::Conv_729)
%onnx::Conv_738 = Identity(%onnx::Conv_729)
%onnx::Conv_735 = Identity(%onnx::Conv_729)
%onnx::Conv_732 = Identity(%onnx::Conv_729)
%onnx::Conv_726 = Identity(%onnx::Conv_693)
%onnx::Conv_723 = Identity(%onnx::Conv_693)
%onnx::Conv_720 = Identity(%onnx::Conv_693)
%onnx::Conv_717 = Identity(%onnx::Conv_693)
%onnx::Conv_714 = Identity(%onnx::Conv_693)
%onnx::Conv_711 = Identity(%onnx::Conv_693)
%onnx::Conv_708 = Identity(%onnx::Conv_693)
%onnx::Conv_705 = Identity(%onnx::Conv_693)
%onnx::Conv_702 = Identity(%onnx::Conv_693)
%onnx::Conv_699 = Identity(%onnx::Conv_693)
%onnx::Conv_696 = Identity(%onnx::Conv_693)
%onnx::Conv_690 = Identity(%onnx::Conv_654)
%onnx::Conv_687 = Identity(%onnx::Conv_654)
%onnx::Conv_684 = Identity(%onnx::Conv_654)
%onnx::Conv_681 = Identity(%onnx::Conv_654)
%onnx::Conv_678 = Identity(%onnx::Conv_654)
%onnx::Conv_675 = Identity(%onnx::Conv_654)
%onnx::Conv_672 = Identity(%onnx::Conv_654)
%onnx::Conv_669 = Identity(%onnx::Conv_654)
%onnx::Conv_666 = Identity(%onnx::Conv_654)
%onnx::Conv_663 = Identity(%onnx::Conv_654)
%onnx::Conv_660 = Identity(%onnx::Conv_654)
%onnx::Conv_657 = Identity(%onnx::Conv_654)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_653, %onnx::Conv_654)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_656, %onnx::Conv_657)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_659, %onnx::Conv_660)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_662, %onnx::Conv_663)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%651 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %651
}
|
val_accuracy
| 89.973956
| 6,002,845,696
| 20,346,506
|
{'zcp_epe_nas': 86.8871940738597, 'zcp_fisher': 34.29116439819336, 'zcp_flops': 96045531136.0, 'zcp_grad_norm': 98.82582092285156, 'zcp_grasp': 4.138702392578125, 'zcp_jacov': -16.064905622988856, 'zcp_l2_norm': 818.9185180664062, 'zcp_nwot': 228.35766907055756, 'zcp_params': 20346506.0, 'zcp_plain': -0.024091038852930003, 'zcp_snip': 957.9261474609375, 'zcp_synflow': 77.14848963044604, 'zcp_zen': 97.15001678466797, 'zcp_val_accuracy': 0.8828125}
| |
NASBench101_215073
|
NASBench101
|
215073
|
824b02f93f1190d33e4d0f4558c6ac07
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_689[FLOAT, 128x3x3x3]
%onnx::Conv_690[FLOAT, 128]
%onnx::Conv_692[FLOAT, 128x128x1x1]
%onnx::Conv_695[FLOAT, 128x128x3x3]
%onnx::Conv_698[FLOAT, 128x128x1x1]
%onnx::Conv_701[FLOAT, 128x128x3x3]
%onnx::Conv_704[FLOAT, 128x128x1x1]
%onnx::Conv_707[FLOAT, 128x128x3x3]
%onnx::Conv_710[FLOAT, 128x128x1x1]
%onnx::Conv_713[FLOAT, 128x128x3x3]
%onnx::Conv_716[FLOAT, 128x128x1x1]
%onnx::Conv_719[FLOAT, 128x128x3x3]
%onnx::Conv_722[FLOAT, 128x128x1x1]
%onnx::Conv_725[FLOAT, 128x128x3x3]
%onnx::Conv_728[FLOAT, 256x128x1x1]
%onnx::Conv_729[FLOAT, 256]
%onnx::Conv_731[FLOAT, 256x256x3x3]
%onnx::Conv_734[FLOAT, 256x128x1x1]
%onnx::Conv_737[FLOAT, 256x256x3x3]
%onnx::Conv_740[FLOAT, 256x256x1x1]
%onnx::Conv_743[FLOAT, 256x256x3x3]
%onnx::Conv_746[FLOAT, 256x256x1x1]
%onnx::Conv_749[FLOAT, 256x256x3x3]
%onnx::Conv_752[FLOAT, 256x256x1x1]
%onnx::Conv_755[FLOAT, 256x256x3x3]
%onnx::Conv_758[FLOAT, 256x256x1x1]
%onnx::Conv_761[FLOAT, 256x256x3x3]
%onnx::Conv_764[FLOAT, 512x256x1x1]
%onnx::Conv_765[FLOAT, 512]
%onnx::Conv_767[FLOAT, 512x512x3x3]
%onnx::Conv_770[FLOAT, 512x256x1x1]
%onnx::Conv_773[FLOAT, 512x512x3x3]
%onnx::Conv_776[FLOAT, 512x512x1x1]
%onnx::Conv_779[FLOAT, 512x512x3x3]
%onnx::Conv_782[FLOAT, 512x512x1x1]
%onnx::Conv_785[FLOAT, 512x512x3x3]
%onnx::Conv_788[FLOAT, 512x512x1x1]
%onnx::Conv_791[FLOAT, 512x512x3x3]
%onnx::Conv_794[FLOAT, 512x512x1x1]
%onnx::Conv_797[FLOAT, 512x512x3x3]
) {
%onnx::Conv_798 = Identity(%onnx::Conv_765)
%onnx::Conv_795 = Identity(%onnx::Conv_765)
%onnx::Conv_792 = Identity(%onnx::Conv_765)
%onnx::Conv_789 = Identity(%onnx::Conv_765)
%onnx::Conv_786 = Identity(%onnx::Conv_765)
%onnx::Conv_783 = Identity(%onnx::Conv_765)
%onnx::Conv_780 = Identity(%onnx::Conv_765)
%onnx::Conv_777 = Identity(%onnx::Conv_765)
%onnx::Conv_774 = Identity(%onnx::Conv_765)
%onnx::Conv_771 = Identity(%onnx::Conv_765)
%onnx::Conv_768 = Identity(%onnx::Conv_765)
%onnx::Conv_762 = Identity(%onnx::Conv_729)
%onnx::Conv_759 = Identity(%onnx::Conv_729)
%onnx::Conv_756 = Identity(%onnx::Conv_729)
%onnx::Conv_753 = Identity(%onnx::Conv_729)
%onnx::Conv_750 = Identity(%onnx::Conv_729)
%onnx::Conv_747 = Identity(%onnx::Conv_729)
%onnx::Conv_744 = Identity(%onnx::Conv_729)
%onnx::Conv_741 = Identity(%onnx::Conv_729)
%onnx::Conv_738 = Identity(%onnx::Conv_729)
%onnx::Conv_735 = Identity(%onnx::Conv_729)
%onnx::Conv_732 = Identity(%onnx::Conv_729)
%onnx::Conv_726 = Identity(%onnx::Conv_690)
%onnx::Conv_723 = Identity(%onnx::Conv_690)
%onnx::Conv_720 = Identity(%onnx::Conv_690)
%onnx::Conv_717 = Identity(%onnx::Conv_690)
%onnx::Conv_714 = Identity(%onnx::Conv_690)
%onnx::Conv_711 = Identity(%onnx::Conv_690)
%onnx::Conv_708 = Identity(%onnx::Conv_690)
%onnx::Conv_705 = Identity(%onnx::Conv_690)
%onnx::Conv_702 = Identity(%onnx::Conv_690)
%onnx::Conv_699 = Identity(%onnx::Conv_690)
%onnx::Conv_696 = Identity(%onnx::Conv_690)
%onnx::Conv_693 = Identity(%onnx::Conv_690)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_689, %onnx::Conv_690)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_6_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_6_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_6_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_6_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_6_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_6_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_6_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_6_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_6_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%687 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %687
}
|
val_accuracy
| 90.114182
| 6,002,845,696
| 20,346,506
|
{'zcp_epe_nas': 77.82880888357766, 'zcp_fisher': 304.6248474121094, 'zcp_flops': 96045531136.0, 'zcp_grad_norm': 286.0826721191406, 'zcp_grasp': -573.39794921875, 'zcp_jacov': -16.063825748059163, 'zcp_l2_norm': 818.1632690429688, 'zcp_nwot': 228.74928362649712, 'zcp_params': 20346506.0, 'zcp_plain': 0.814574599266052, 'zcp_snip': 2578.90771484375, 'zcp_synflow': 79.63946887053086, 'zcp_zen': 96.59065246582031, 'zcp_val_accuracy': 0.9008413553237911}
| |
NASBench101_318039
|
NASBench101
|
318039
|
c068f6d017a91ca576bb4715f97bc582
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_797[FLOAT, 128x3x3x3]
%onnx::Conv_798[FLOAT, 128]
%onnx::Conv_800[FLOAT, 64x128x1x1]
%onnx::Conv_801[FLOAT, 64]
%onnx::Conv_803[FLOAT, 64x64x1x1]
%onnx::Conv_806[FLOAT, 64x64x1x1]
%onnx::Conv_809[FLOAT, 64x128x1x1]
%onnx::Conv_812[FLOAT, 64x64x3x3]
%onnx::Conv_815[FLOAT, 64x128x1x1]
%onnx::Conv_818[FLOAT, 64x64x1x1]
%onnx::Conv_821[FLOAT, 64x64x1x1]
%onnx::Conv_824[FLOAT, 64x128x1x1]
%onnx::Conv_827[FLOAT, 64x64x3x3]
%onnx::Conv_830[FLOAT, 64x128x1x1]
%onnx::Conv_833[FLOAT, 64x64x1x1]
%onnx::Conv_836[FLOAT, 64x64x1x1]
%onnx::Conv_839[FLOAT, 64x128x1x1]
%onnx::Conv_842[FLOAT, 64x64x3x3]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x1x1]
%onnx::Conv_851[FLOAT, 128x128x1x1]
%onnx::Conv_854[FLOAT, 128x128x1x1]
%onnx::Conv_857[FLOAT, 128x128x3x3]
%onnx::Conv_860[FLOAT, 128x256x1x1]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%onnx::Conv_866[FLOAT, 128x128x1x1]
%onnx::Conv_869[FLOAT, 128x256x1x1]
%onnx::Conv_872[FLOAT, 128x128x3x3]
%onnx::Conv_875[FLOAT, 128x256x1x1]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 128x128x1x1]
%onnx::Conv_884[FLOAT, 128x256x1x1]
%onnx::Conv_887[FLOAT, 128x128x3x3]
%onnx::Conv_890[FLOAT, 256x256x1x1]
%onnx::Conv_891[FLOAT, 256]
%onnx::Conv_893[FLOAT, 256x256x1x1]
%onnx::Conv_896[FLOAT, 256x256x1x1]
%onnx::Conv_899[FLOAT, 256x256x1x1]
%onnx::Conv_902[FLOAT, 256x256x3x3]
%onnx::Conv_905[FLOAT, 256x512x1x1]
%onnx::Conv_908[FLOAT, 256x256x1x1]
%onnx::Conv_911[FLOAT, 256x256x1x1]
%onnx::Conv_914[FLOAT, 256x512x1x1]
%onnx::Conv_917[FLOAT, 256x256x3x3]
%onnx::Conv_920[FLOAT, 256x512x1x1]
%onnx::Conv_923[FLOAT, 256x256x1x1]
%onnx::Conv_926[FLOAT, 256x256x1x1]
%onnx::Conv_929[FLOAT, 256x512x1x1]
%onnx::Conv_932[FLOAT, 256x256x3x3]
) {
%onnx::Conv_933 = Identity(%onnx::Conv_891)
%onnx::Conv_930 = Identity(%onnx::Conv_891)
%onnx::Conv_927 = Identity(%onnx::Conv_891)
%onnx::Conv_924 = Identity(%onnx::Conv_891)
%onnx::Conv_921 = Identity(%onnx::Conv_891)
%onnx::Conv_918 = Identity(%onnx::Conv_891)
%onnx::Conv_915 = Identity(%onnx::Conv_891)
%onnx::Conv_912 = Identity(%onnx::Conv_891)
%onnx::Conv_909 = Identity(%onnx::Conv_891)
%onnx::Conv_906 = Identity(%onnx::Conv_891)
%onnx::Conv_903 = Identity(%onnx::Conv_891)
%onnx::Conv_900 = Identity(%onnx::Conv_891)
%onnx::Conv_897 = Identity(%onnx::Conv_891)
%onnx::Conv_894 = Identity(%onnx::Conv_891)
%onnx::Conv_888 = Identity(%onnx::Conv_798)
%onnx::Conv_885 = Identity(%onnx::Conv_798)
%onnx::Conv_882 = Identity(%onnx::Conv_798)
%onnx::Conv_879 = Identity(%onnx::Conv_798)
%onnx::Conv_876 = Identity(%onnx::Conv_798)
%onnx::Conv_873 = Identity(%onnx::Conv_798)
%onnx::Conv_870 = Identity(%onnx::Conv_798)
%onnx::Conv_867 = Identity(%onnx::Conv_798)
%onnx::Conv_864 = Identity(%onnx::Conv_798)
%onnx::Conv_861 = Identity(%onnx::Conv_798)
%onnx::Conv_858 = Identity(%onnx::Conv_798)
%onnx::Conv_855 = Identity(%onnx::Conv_798)
%onnx::Conv_852 = Identity(%onnx::Conv_798)
%onnx::Conv_849 = Identity(%onnx::Conv_798)
%onnx::Conv_846 = Identity(%onnx::Conv_798)
%onnx::Conv_843 = Identity(%onnx::Conv_801)
%onnx::Conv_840 = Identity(%onnx::Conv_801)
%onnx::Conv_837 = Identity(%onnx::Conv_801)
%onnx::Conv_834 = Identity(%onnx::Conv_801)
%onnx::Conv_831 = Identity(%onnx::Conv_801)
%onnx::Conv_828 = Identity(%onnx::Conv_801)
%onnx::Conv_825 = Identity(%onnx::Conv_801)
%onnx::Conv_822 = Identity(%onnx::Conv_801)
%onnx::Conv_819 = Identity(%onnx::Conv_801)
%onnx::Conv_816 = Identity(%onnx::Conv_801)
%onnx::Conv_813 = Identity(%onnx::Conv_801)
%onnx::Conv_810 = Identity(%onnx::Conv_801)
%onnx::Conv_807 = Identity(%onnx::Conv_801)
%onnx::Conv_804 = Identity(%onnx::Conv_801)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_797, %onnx::Conv_798)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_6_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_6_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_6_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_6_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_6_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_6_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_6_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_6_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_6_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%795 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %795
}
|
val_accuracy
| 91.175884
| 1,120,806,912
| 3,729,162
|
{'zcp_epe_nas': 80.50870242777138, 'zcp_fisher': 29.77923011779785, 'zcp_flops': 17932910592.0, 'zcp_grad_norm': 98.30656433105469, 'zcp_grasp': -1.3089599609375, 'zcp_jacov': -16.05110906771673, 'zcp_l2_norm': 843.9085083007812, 'zcp_nwot': 221.82319866963877, 'zcp_params': 3729162.0, 'zcp_plain': 0.064306408166885, 'zcp_snip': 568.722412109375, 'zcp_synflow': 92.09640233597933, 'zcp_zen': 81.38261413574219, 'zcp_val_accuracy': 0.9016426205635071}
| |
NASBench101_318139
|
NASBench101
|
318139
|
c077f00ce41f2e69333be3bced669809
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_977[FLOAT, 128x3x3x3]
%onnx::Conv_978[FLOAT, 128]
%onnx::Conv_980[FLOAT, 64x128x1x1]
%onnx::Conv_981[FLOAT, 64]
%onnx::Conv_983[FLOAT, 64x64x3x3]
%onnx::Conv_986[FLOAT, 64x64x3x3]
%onnx::Conv_989[FLOAT, 64x64x3x3]
%onnx::Conv_992[FLOAT, 64x128x1x1]
%onnx::Conv_995[FLOAT, 64x64x3x3]
%onnx::Conv_998[FLOAT, 64x64x1x1]
%onnx::Conv_1001[FLOAT, 64x128x1x1]
%onnx::Conv_1004[FLOAT, 64x64x3x3]
%onnx::Conv_1007[FLOAT, 64x64x3x3]
%onnx::Conv_1010[FLOAT, 64x64x3x3]
%onnx::Conv_1013[FLOAT, 64x128x1x1]
%onnx::Conv_1016[FLOAT, 64x64x3x3]
%onnx::Conv_1019[FLOAT, 64x64x1x1]
%onnx::Conv_1022[FLOAT, 64x128x1x1]
%onnx::Conv_1025[FLOAT, 64x64x3x3]
%onnx::Conv_1028[FLOAT, 64x64x3x3]
%onnx::Conv_1031[FLOAT, 64x64x3x3]
%onnx::Conv_1034[FLOAT, 64x128x1x1]
%onnx::Conv_1037[FLOAT, 64x64x3x3]
%onnx::Conv_1040[FLOAT, 64x64x1x1]
%onnx::Conv_1043[FLOAT, 128x128x1x1]
%onnx::Conv_1046[FLOAT, 128x128x3x3]
%onnx::Conv_1049[FLOAT, 128x128x3x3]
%onnx::Conv_1052[FLOAT, 128x128x3x3]
%onnx::Conv_1055[FLOAT, 128x128x1x1]
%onnx::Conv_1058[FLOAT, 128x128x3x3]
%onnx::Conv_1061[FLOAT, 128x128x1x1]
%onnx::Conv_1064[FLOAT, 128x256x1x1]
%onnx::Conv_1067[FLOAT, 128x128x3x3]
%onnx::Conv_1070[FLOAT, 128x128x3x3]
%onnx::Conv_1073[FLOAT, 128x128x3x3]
%onnx::Conv_1076[FLOAT, 128x256x1x1]
%onnx::Conv_1079[FLOAT, 128x128x3x3]
%onnx::Conv_1082[FLOAT, 128x128x1x1]
%onnx::Conv_1085[FLOAT, 128x256x1x1]
%onnx::Conv_1088[FLOAT, 128x128x3x3]
%onnx::Conv_1091[FLOAT, 128x128x3x3]
%onnx::Conv_1094[FLOAT, 128x128x3x3]
%onnx::Conv_1097[FLOAT, 128x256x1x1]
%onnx::Conv_1100[FLOAT, 128x128x3x3]
%onnx::Conv_1103[FLOAT, 128x128x1x1]
%onnx::Conv_1106[FLOAT, 256x256x1x1]
%onnx::Conv_1107[FLOAT, 256]
%onnx::Conv_1109[FLOAT, 256x256x3x3]
%onnx::Conv_1112[FLOAT, 256x256x3x3]
%onnx::Conv_1115[FLOAT, 256x256x3x3]
%onnx::Conv_1118[FLOAT, 256x256x1x1]
%onnx::Conv_1121[FLOAT, 256x256x3x3]
%onnx::Conv_1124[FLOAT, 256x256x1x1]
%onnx::Conv_1127[FLOAT, 256x512x1x1]
%onnx::Conv_1130[FLOAT, 256x256x3x3]
%onnx::Conv_1133[FLOAT, 256x256x3x3]
%onnx::Conv_1136[FLOAT, 256x256x3x3]
%onnx::Conv_1139[FLOAT, 256x512x1x1]
%onnx::Conv_1142[FLOAT, 256x256x3x3]
%onnx::Conv_1145[FLOAT, 256x256x1x1]
%onnx::Conv_1148[FLOAT, 256x512x1x1]
%onnx::Conv_1151[FLOAT, 256x256x3x3]
%onnx::Conv_1154[FLOAT, 256x256x3x3]
%onnx::Conv_1157[FLOAT, 256x256x3x3]
%onnx::Conv_1160[FLOAT, 256x512x1x1]
%onnx::Conv_1163[FLOAT, 256x256x3x3]
%onnx::Conv_1166[FLOAT, 256x256x1x1]
) {
%onnx::Conv_1167 = Identity(%onnx::Conv_1107)
%onnx::Conv_1164 = Identity(%onnx::Conv_1107)
%onnx::Conv_1161 = Identity(%onnx::Conv_1107)
%onnx::Conv_1158 = Identity(%onnx::Conv_1107)
%onnx::Conv_1155 = Identity(%onnx::Conv_1107)
%onnx::Conv_1152 = Identity(%onnx::Conv_1107)
%onnx::Conv_1149 = Identity(%onnx::Conv_1107)
%onnx::Conv_1146 = Identity(%onnx::Conv_1107)
%onnx::Conv_1143 = Identity(%onnx::Conv_1107)
%onnx::Conv_1140 = Identity(%onnx::Conv_1107)
%onnx::Conv_1137 = Identity(%onnx::Conv_1107)
%onnx::Conv_1134 = Identity(%onnx::Conv_1107)
%onnx::Conv_1131 = Identity(%onnx::Conv_1107)
%onnx::Conv_1128 = Identity(%onnx::Conv_1107)
%onnx::Conv_1125 = Identity(%onnx::Conv_1107)
%onnx::Conv_1122 = Identity(%onnx::Conv_1107)
%onnx::Conv_1119 = Identity(%onnx::Conv_1107)
%onnx::Conv_1116 = Identity(%onnx::Conv_1107)
%onnx::Conv_1113 = Identity(%onnx::Conv_1107)
%onnx::Conv_1110 = Identity(%onnx::Conv_1107)
%onnx::Conv_1104 = Identity(%onnx::Conv_978)
%onnx::Conv_1101 = Identity(%onnx::Conv_978)
%onnx::Conv_1098 = Identity(%onnx::Conv_978)
%onnx::Conv_1095 = Identity(%onnx::Conv_978)
%onnx::Conv_1092 = Identity(%onnx::Conv_978)
%onnx::Conv_1089 = Identity(%onnx::Conv_978)
%onnx::Conv_1086 = Identity(%onnx::Conv_978)
%onnx::Conv_1083 = Identity(%onnx::Conv_978)
%onnx::Conv_1080 = Identity(%onnx::Conv_978)
%onnx::Conv_1077 = Identity(%onnx::Conv_978)
%onnx::Conv_1074 = Identity(%onnx::Conv_978)
%onnx::Conv_1071 = Identity(%onnx::Conv_978)
%onnx::Conv_1068 = Identity(%onnx::Conv_978)
%onnx::Conv_1065 = Identity(%onnx::Conv_978)
%onnx::Conv_1062 = Identity(%onnx::Conv_978)
%onnx::Conv_1059 = Identity(%onnx::Conv_978)
%onnx::Conv_1056 = Identity(%onnx::Conv_978)
%onnx::Conv_1053 = Identity(%onnx::Conv_978)
%onnx::Conv_1050 = Identity(%onnx::Conv_978)
%onnx::Conv_1047 = Identity(%onnx::Conv_978)
%onnx::Conv_1044 = Identity(%onnx::Conv_978)
%onnx::Conv_1041 = Identity(%onnx::Conv_981)
%onnx::Conv_1038 = Identity(%onnx::Conv_981)
%onnx::Conv_1035 = Identity(%onnx::Conv_981)
%onnx::Conv_1032 = Identity(%onnx::Conv_981)
%onnx::Conv_1029 = Identity(%onnx::Conv_981)
%onnx::Conv_1026 = Identity(%onnx::Conv_981)
%onnx::Conv_1023 = Identity(%onnx::Conv_981)
%onnx::Conv_1020 = Identity(%onnx::Conv_981)
%onnx::Conv_1017 = Identity(%onnx::Conv_981)
%onnx::Conv_1014 = Identity(%onnx::Conv_981)
%onnx::Conv_1011 = Identity(%onnx::Conv_981)
%onnx::Conv_1008 = Identity(%onnx::Conv_981)
%onnx::Conv_1005 = Identity(%onnx::Conv_981)
%onnx::Conv_1002 = Identity(%onnx::Conv_981)
%onnx::Conv_999 = Identity(%onnx::Conv_981)
%onnx::Conv_996 = Identity(%onnx::Conv_981)
%onnx::Conv_993 = Identity(%onnx::Conv_981)
%onnx::Conv_990 = Identity(%onnx::Conv_981)
%onnx::Conv_987 = Identity(%onnx::Conv_981)
%onnx::Conv_984 = Identity(%onnx::Conv_981)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_977, %onnx::Conv_978)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%975 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %975
}
|
val_accuracy
| 93.509614
| 3,089,246,208
| 10,443,786
|
{'zcp_epe_nas': 125.81639735369943, 'zcp_fisher': 19.657583236694336, 'zcp_flops': 49427939328.0, 'zcp_grad_norm': 96.65373229980469, 'zcp_grasp': -1.107177734375, 'zcp_jacov': -16.059400307823424, 'zcp_l2_norm': 1143.835693359375, 'zcp_nwot': 226.7839421776326, 'zcp_params': 10443786.0, 'zcp_plain': 0.004727460443973, 'zcp_snip': 593.4244995117188, 'zcp_synflow': 149.3568004765727, 'zcp_zen': 124.98274993896484, 'zcp_val_accuracy': 0.8588742017745971}
| |
NASBench101_135965
|
NASBench101
|
135965
|
5236b9527b9106ffb6139468573a75e1
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_809[FLOAT, 128x3x3x3]
%onnx::Conv_810[FLOAT, 128]
%onnx::Conv_812[FLOAT, 43x128x1x1]
%onnx::Conv_813[FLOAT, 43]
%onnx::Conv_815[FLOAT, 43x128x1x1]
%onnx::Conv_818[FLOAT, 43x43x3x3]
%onnx::Conv_821[FLOAT, 43x43x1x1]
%onnx::Conv_824[FLOAT, 42x42x3x3]
%onnx::Conv_825[FLOAT, 42]
%onnx::Conv_827[FLOAT, 43x128x1x1]
%onnx::Conv_830[FLOAT, 43x128x1x1]
%onnx::Conv_833[FLOAT, 43x43x3x3]
%onnx::Conv_836[FLOAT, 43x43x1x1]
%onnx::Conv_839[FLOAT, 42x42x3x3]
%onnx::Conv_842[FLOAT, 43x128x1x1]
%onnx::Conv_845[FLOAT, 43x128x1x1]
%onnx::Conv_848[FLOAT, 43x43x3x3]
%onnx::Conv_851[FLOAT, 43x43x1x1]
%onnx::Conv_854[FLOAT, 42x42x3x3]
%onnx::Conv_857[FLOAT, 86x128x1x1]
%onnx::Conv_858[FLOAT, 86]
%onnx::Conv_860[FLOAT, 85x128x1x1]
%onnx::Conv_861[FLOAT, 85]
%onnx::Conv_863[FLOAT, 85x85x3x3]
%onnx::Conv_866[FLOAT, 85x85x1x1]
%onnx::Conv_869[FLOAT, 85x85x3x3]
%onnx::Conv_872[FLOAT, 86x256x1x1]
%onnx::Conv_875[FLOAT, 85x256x1x1]
%onnx::Conv_878[FLOAT, 85x85x3x3]
%onnx::Conv_881[FLOAT, 85x85x1x1]
%onnx::Conv_884[FLOAT, 85x85x3x3]
%onnx::Conv_887[FLOAT, 86x256x1x1]
%onnx::Conv_890[FLOAT, 85x256x1x1]
%onnx::Conv_893[FLOAT, 85x85x3x3]
%onnx::Conv_896[FLOAT, 85x85x1x1]
%onnx::Conv_899[FLOAT, 85x85x3x3]
%onnx::Conv_902[FLOAT, 171x256x1x1]
%onnx::Conv_903[FLOAT, 171]
%onnx::Conv_905[FLOAT, 171x256x1x1]
%onnx::Conv_908[FLOAT, 171x171x3x3]
%onnx::Conv_911[FLOAT, 171x171x1x1]
%onnx::Conv_914[FLOAT, 170x170x3x3]
%onnx::Conv_915[FLOAT, 170]
%onnx::Conv_917[FLOAT, 171x512x1x1]
%onnx::Conv_920[FLOAT, 171x512x1x1]
%onnx::Conv_923[FLOAT, 171x171x3x3]
%onnx::Conv_926[FLOAT, 171x171x1x1]
%onnx::Conv_929[FLOAT, 170x170x3x3]
%onnx::Conv_932[FLOAT, 171x512x1x1]
%onnx::Conv_935[FLOAT, 171x512x1x1]
%onnx::Conv_938[FLOAT, 171x171x3x3]
%onnx::Conv_941[FLOAT, 171x171x1x1]
%onnx::Conv_944[FLOAT, 170x170x3x3]
) {
%onnx::Conv_945 = Identity(%onnx::Conv_915)
%onnx::Conv_942 = Identity(%onnx::Conv_903)
%onnx::Conv_939 = Identity(%onnx::Conv_903)
%onnx::Conv_936 = Identity(%onnx::Conv_903)
%onnx::Conv_933 = Identity(%onnx::Conv_903)
%onnx::Conv_930 = Identity(%onnx::Conv_915)
%onnx::Conv_927 = Identity(%onnx::Conv_903)
%onnx::Conv_924 = Identity(%onnx::Conv_903)
%onnx::Conv_921 = Identity(%onnx::Conv_903)
%onnx::Conv_918 = Identity(%onnx::Conv_903)
%onnx::Conv_912 = Identity(%onnx::Conv_903)
%onnx::Conv_909 = Identity(%onnx::Conv_903)
%onnx::Conv_906 = Identity(%onnx::Conv_903)
%onnx::Conv_900 = Identity(%onnx::Conv_861)
%onnx::Conv_897 = Identity(%onnx::Conv_861)
%onnx::Conv_894 = Identity(%onnx::Conv_861)
%onnx::Conv_891 = Identity(%onnx::Conv_861)
%onnx::Conv_888 = Identity(%onnx::Conv_858)
%onnx::Conv_885 = Identity(%onnx::Conv_861)
%onnx::Conv_882 = Identity(%onnx::Conv_861)
%onnx::Conv_879 = Identity(%onnx::Conv_861)
%onnx::Conv_876 = Identity(%onnx::Conv_861)
%onnx::Conv_873 = Identity(%onnx::Conv_858)
%onnx::Conv_870 = Identity(%onnx::Conv_861)
%onnx::Conv_867 = Identity(%onnx::Conv_861)
%onnx::Conv_864 = Identity(%onnx::Conv_861)
%onnx::Conv_855 = Identity(%onnx::Conv_825)
%onnx::Conv_852 = Identity(%onnx::Conv_813)
%onnx::Conv_849 = Identity(%onnx::Conv_813)
%onnx::Conv_846 = Identity(%onnx::Conv_813)
%onnx::Conv_843 = Identity(%onnx::Conv_813)
%onnx::Conv_840 = Identity(%onnx::Conv_825)
%onnx::Conv_837 = Identity(%onnx::Conv_813)
%onnx::Conv_834 = Identity(%onnx::Conv_813)
%onnx::Conv_831 = Identity(%onnx::Conv_813)
%onnx::Conv_828 = Identity(%onnx::Conv_813)
%onnx::Conv_822 = Identity(%onnx::Conv_813)
%onnx::Conv_819 = Identity(%onnx::Conv_813)
%onnx::Conv_816 = Identity(%onnx::Conv_813)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_809, %onnx::Conv_810)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_2_output_0, %/layers.1/Constant_5_output_0)
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_1_output_0 = Slice(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_7_output_0, %/layers.1/Constant_8_output_0, %/layers.1/Constant_6_output_0, %/layers.1/Constant_9_output_0)
%/layers.1/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_10_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/Slice_1_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_2_output_0, %/layers.2/Constant_5_output_0)
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_1_output_0 = Slice(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_7_output_0, %/layers.2/Constant_8_output_0, %/layers.2/Constant_6_output_0, %/layers.2/Constant_9_output_0)
%/layers.2/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_10_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/Slice_1_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_2_output_0, %/layers.3/Constant_5_output_0)
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_1_output_0 = Slice(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_7_output_0, %/layers.3/Constant_8_output_0, %/layers.3/Constant_6_output_0, %/layers.3/Constant_9_output_0)
%/layers.3/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_10_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/Slice_1_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_1_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_1_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_1_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_2_output_0, %/layers.9/Constant_5_output_0)
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_1_output_0 = Slice(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_7_output_0, %/layers.9/Constant_8_output_0, %/layers.9/Constant_6_output_0, %/layers.9/Constant_9_output_0)
%/layers.9/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_10_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/Slice_1_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_2_output_0, %/layers.10/Constant_5_output_0)
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_1_output_0 = Slice(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_7_output_0, %/layers.10/Constant_8_output_0, %/layers.10/Constant_6_output_0, %/layers.10/Constant_9_output_0)
%/layers.10/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_10_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/Slice_1_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_2_output_0, %/layers.11/Constant_5_output_0)
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_1_output_0 = Slice(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_7_output_0, %/layers.11/Constant_8_output_0, %/layers.11/Constant_6_output_0, %/layers.11/Constant_9_output_0)
%/layers.11/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_10_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/Slice_1_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%807 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %807
}
|
val_accuracy
| 90.134215
| 831,187,712
| 2,770,483
|
{'zcp_epe_nas': 78.56304127201142, 'zcp_fisher': 8.208694458007812, 'zcp_flops': 13299003392.0, 'zcp_grad_norm': 57.5108528137207, 'zcp_grasp': 1.710906982421875, 'zcp_jacov': -16.058392018110304, 'zcp_l2_norm': 761.7943115234375, 'zcp_nwot': 215.4875677496098, 'zcp_params': 2770483.0, 'zcp_plain': 0.004750701133161, 'zcp_snip': 292.934814453125, 'zcp_synflow': 116.74657617586601, 'zcp_zen': 84.29886627197266, 'zcp_val_accuracy': 0.868689894676208}
| |
NASBench101_292306
|
NASBench101
|
292306
|
b0f60faa9f5eb1e87426d07ba7398147
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_743[FLOAT, 128x3x3x3]
%onnx::Conv_744[FLOAT, 128]
%onnx::Conv_746[FLOAT, 64x128x1x1]
%onnx::Conv_747[FLOAT, 64]
%onnx::Conv_749[FLOAT, 64x128x1x1]
%onnx::Conv_752[FLOAT, 64x64x3x3]
%onnx::Conv_755[FLOAT, 64x128x1x1]
%onnx::Conv_758[FLOAT, 128x128x1x1]
%onnx::Conv_761[FLOAT, 64x128x1x1]
%onnx::Conv_764[FLOAT, 64x128x1x1]
%onnx::Conv_767[FLOAT, 64x64x3x3]
%onnx::Conv_770[FLOAT, 64x128x1x1]
%onnx::Conv_773[FLOAT, 128x128x1x1]
%onnx::Conv_776[FLOAT, 64x128x1x1]
%onnx::Conv_779[FLOAT, 64x128x1x1]
%onnx::Conv_782[FLOAT, 64x64x3x3]
%onnx::Conv_785[FLOAT, 64x128x1x1]
%onnx::Conv_788[FLOAT, 128x128x1x1]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 128x128x1x1]
%onnx::Conv_797[FLOAT, 128x128x3x3]
%onnx::Conv_800[FLOAT, 128x128x1x1]
%onnx::Conv_803[FLOAT, 256x128x1x1]
%onnx::Conv_804[FLOAT, 256]
%onnx::Conv_806[FLOAT, 128x256x1x1]
%onnx::Conv_809[FLOAT, 128x256x1x1]
%onnx::Conv_812[FLOAT, 128x128x3x3]
%onnx::Conv_815[FLOAT, 128x256x1x1]
%onnx::Conv_818[FLOAT, 256x256x1x1]
%onnx::Conv_821[FLOAT, 128x256x1x1]
%onnx::Conv_824[FLOAT, 128x256x1x1]
%onnx::Conv_827[FLOAT, 128x128x3x3]
%onnx::Conv_830[FLOAT, 128x256x1x1]
%onnx::Conv_833[FLOAT, 256x256x1x1]
%onnx::Conv_836[FLOAT, 256x256x1x1]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x256x3x3]
%onnx::Conv_845[FLOAT, 256x256x1x1]
%onnx::Conv_848[FLOAT, 512x256x1x1]
%onnx::Conv_849[FLOAT, 512]
%onnx::Conv_851[FLOAT, 256x512x1x1]
%onnx::Conv_854[FLOAT, 256x512x1x1]
%onnx::Conv_857[FLOAT, 256x256x3x3]
%onnx::Conv_860[FLOAT, 256x512x1x1]
%onnx::Conv_863[FLOAT, 512x512x1x1]
%onnx::Conv_866[FLOAT, 256x512x1x1]
%onnx::Conv_869[FLOAT, 256x512x1x1]
%onnx::Conv_872[FLOAT, 256x256x3x3]
%onnx::Conv_875[FLOAT, 256x512x1x1]
%onnx::Conv_878[FLOAT, 512x512x1x1]
) {
%onnx::Conv_879 = Identity(%onnx::Conv_849)
%onnx::Conv_876 = Identity(%onnx::Conv_804)
%onnx::Conv_873 = Identity(%onnx::Conv_804)
%onnx::Conv_870 = Identity(%onnx::Conv_804)
%onnx::Conv_867 = Identity(%onnx::Conv_804)
%onnx::Conv_864 = Identity(%onnx::Conv_849)
%onnx::Conv_861 = Identity(%onnx::Conv_804)
%onnx::Conv_858 = Identity(%onnx::Conv_804)
%onnx::Conv_855 = Identity(%onnx::Conv_804)
%onnx::Conv_852 = Identity(%onnx::Conv_804)
%onnx::Conv_846 = Identity(%onnx::Conv_804)
%onnx::Conv_843 = Identity(%onnx::Conv_804)
%onnx::Conv_840 = Identity(%onnx::Conv_804)
%onnx::Conv_837 = Identity(%onnx::Conv_804)
%onnx::Conv_834 = Identity(%onnx::Conv_804)
%onnx::Conv_831 = Identity(%onnx::Conv_744)
%onnx::Conv_828 = Identity(%onnx::Conv_744)
%onnx::Conv_825 = Identity(%onnx::Conv_744)
%onnx::Conv_822 = Identity(%onnx::Conv_744)
%onnx::Conv_819 = Identity(%onnx::Conv_804)
%onnx::Conv_816 = Identity(%onnx::Conv_744)
%onnx::Conv_813 = Identity(%onnx::Conv_744)
%onnx::Conv_810 = Identity(%onnx::Conv_744)
%onnx::Conv_807 = Identity(%onnx::Conv_744)
%onnx::Conv_801 = Identity(%onnx::Conv_744)
%onnx::Conv_798 = Identity(%onnx::Conv_744)
%onnx::Conv_795 = Identity(%onnx::Conv_744)
%onnx::Conv_792 = Identity(%onnx::Conv_744)
%onnx::Conv_789 = Identity(%onnx::Conv_744)
%onnx::Conv_786 = Identity(%onnx::Conv_747)
%onnx::Conv_783 = Identity(%onnx::Conv_747)
%onnx::Conv_780 = Identity(%onnx::Conv_747)
%onnx::Conv_777 = Identity(%onnx::Conv_747)
%onnx::Conv_774 = Identity(%onnx::Conv_744)
%onnx::Conv_771 = Identity(%onnx::Conv_747)
%onnx::Conv_768 = Identity(%onnx::Conv_747)
%onnx::Conv_765 = Identity(%onnx::Conv_747)
%onnx::Conv_762 = Identity(%onnx::Conv_747)
%onnx::Conv_759 = Identity(%onnx::Conv_744)
%onnx::Conv_756 = Identity(%onnx::Conv_747)
%onnx::Conv_753 = Identity(%onnx::Conv_747)
%onnx::Conv_750 = Identity(%onnx::Conv_747)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_743, %onnx::Conv_744)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_4_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_4_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_4_output_0)
%741 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %741
}
|
val_accuracy
| 90.544873
| 1,375,217,664
| 4,518,282
|
{'zcp_epe_nas': 164.36556265693957, 'zcp_fisher': 7.4361371994018555, 'zcp_flops': 22003482624.0, 'zcp_grad_norm': 62.42425537109375, 'zcp_grasp': -70.44314575195312, 'zcp_jacov': -16.058599163505814, 'zcp_l2_norm': 935.9583129882812, 'zcp_nwot': 223.8683049144941, 'zcp_params': 4518282.0, 'zcp_plain': 0.419362515211105, 'zcp_snip': 372.9922180175781, 'zcp_synflow': 61.88841065597074, 'zcp_zen': 96.09831237792969, 'zcp_val_accuracy': 0.8596754670143121}
| |
NASBench101_339734
|
NASBench101
|
339734
|
cd6f52f5c63db9100086f56fd67f16db
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_1013[FLOAT, 128x3x3x3]
%onnx::Conv_1014[FLOAT, 128]
%onnx::Conv_1016[FLOAT, 43x128x1x1]
%onnx::Conv_1017[FLOAT, 43]
%onnx::Conv_1019[FLOAT, 43x43x3x3]
%onnx::Conv_1022[FLOAT, 43x128x1x1]
%onnx::Conv_1025[FLOAT, 43x43x1x1]
%onnx::Conv_1028[FLOAT, 43x43x3x3]
%onnx::Conv_1031[FLOAT, 43x43x3x3]
%onnx::Conv_1034[FLOAT, 42x42x3x3]
%onnx::Conv_1035[FLOAT, 42]
%onnx::Conv_1037[FLOAT, 43x128x1x1]
%onnx::Conv_1040[FLOAT, 43x43x3x3]
%onnx::Conv_1043[FLOAT, 43x128x1x1]
%onnx::Conv_1046[FLOAT, 43x43x1x1]
%onnx::Conv_1049[FLOAT, 43x43x3x3]
%onnx::Conv_1052[FLOAT, 43x43x3x3]
%onnx::Conv_1055[FLOAT, 42x42x3x3]
%onnx::Conv_1058[FLOAT, 43x128x1x1]
%onnx::Conv_1061[FLOAT, 43x43x3x3]
%onnx::Conv_1064[FLOAT, 43x128x1x1]
%onnx::Conv_1067[FLOAT, 43x43x1x1]
%onnx::Conv_1070[FLOAT, 43x43x3x3]
%onnx::Conv_1073[FLOAT, 43x43x3x3]
%onnx::Conv_1076[FLOAT, 42x42x3x3]
%onnx::Conv_1079[FLOAT, 86x128x1x1]
%onnx::Conv_1080[FLOAT, 86]
%onnx::Conv_1082[FLOAT, 86x86x3x3]
%onnx::Conv_1085[FLOAT, 86x128x1x1]
%onnx::Conv_1088[FLOAT, 86x86x1x1]
%onnx::Conv_1091[FLOAT, 85x85x3x3]
%onnx::Conv_1092[FLOAT, 85]
%onnx::Conv_1094[FLOAT, 85x85x3x3]
%onnx::Conv_1097[FLOAT, 85x85x3x3]
%onnx::Conv_1100[FLOAT, 86x256x1x1]
%onnx::Conv_1103[FLOAT, 86x86x3x3]
%onnx::Conv_1106[FLOAT, 86x256x1x1]
%onnx::Conv_1109[FLOAT, 86x86x1x1]
%onnx::Conv_1112[FLOAT, 85x85x3x3]
%onnx::Conv_1115[FLOAT, 85x85x3x3]
%onnx::Conv_1118[FLOAT, 85x85x3x3]
%onnx::Conv_1121[FLOAT, 86x256x1x1]
%onnx::Conv_1124[FLOAT, 86x86x3x3]
%onnx::Conv_1127[FLOAT, 86x256x1x1]
%onnx::Conv_1130[FLOAT, 86x86x1x1]
%onnx::Conv_1133[FLOAT, 85x85x3x3]
%onnx::Conv_1136[FLOAT, 85x85x3x3]
%onnx::Conv_1139[FLOAT, 85x85x3x3]
%onnx::Conv_1142[FLOAT, 171x256x1x1]
%onnx::Conv_1143[FLOAT, 171]
%onnx::Conv_1145[FLOAT, 171x171x3x3]
%onnx::Conv_1148[FLOAT, 171x256x1x1]
%onnx::Conv_1151[FLOAT, 171x171x1x1]
%onnx::Conv_1154[FLOAT, 171x171x3x3]
%onnx::Conv_1157[FLOAT, 171x171x3x3]
%onnx::Conv_1160[FLOAT, 170x170x3x3]
%onnx::Conv_1161[FLOAT, 170]
%onnx::Conv_1163[FLOAT, 171x512x1x1]
%onnx::Conv_1166[FLOAT, 171x171x3x3]
%onnx::Conv_1169[FLOAT, 171x512x1x1]
%onnx::Conv_1172[FLOAT, 171x171x1x1]
%onnx::Conv_1175[FLOAT, 171x171x3x3]
%onnx::Conv_1178[FLOAT, 171x171x3x3]
%onnx::Conv_1181[FLOAT, 170x170x3x3]
%onnx::Conv_1184[FLOAT, 171x512x1x1]
%onnx::Conv_1187[FLOAT, 171x171x3x3]
%onnx::Conv_1190[FLOAT, 171x512x1x1]
%onnx::Conv_1193[FLOAT, 171x171x1x1]
%onnx::Conv_1196[FLOAT, 171x171x3x3]
%onnx::Conv_1199[FLOAT, 171x171x3x3]
%onnx::Conv_1202[FLOAT, 170x170x3x3]
) {
%onnx::Conv_1203 = Identity(%onnx::Conv_1161)
%onnx::Conv_1200 = Identity(%onnx::Conv_1143)
%onnx::Conv_1197 = Identity(%onnx::Conv_1143)
%onnx::Conv_1194 = Identity(%onnx::Conv_1143)
%onnx::Conv_1191 = Identity(%onnx::Conv_1143)
%onnx::Conv_1188 = Identity(%onnx::Conv_1143)
%onnx::Conv_1185 = Identity(%onnx::Conv_1143)
%onnx::Conv_1182 = Identity(%onnx::Conv_1161)
%onnx::Conv_1179 = Identity(%onnx::Conv_1143)
%onnx::Conv_1176 = Identity(%onnx::Conv_1143)
%onnx::Conv_1173 = Identity(%onnx::Conv_1143)
%onnx::Conv_1170 = Identity(%onnx::Conv_1143)
%onnx::Conv_1167 = Identity(%onnx::Conv_1143)
%onnx::Conv_1164 = Identity(%onnx::Conv_1143)
%onnx::Conv_1158 = Identity(%onnx::Conv_1143)
%onnx::Conv_1155 = Identity(%onnx::Conv_1143)
%onnx::Conv_1152 = Identity(%onnx::Conv_1143)
%onnx::Conv_1149 = Identity(%onnx::Conv_1143)
%onnx::Conv_1146 = Identity(%onnx::Conv_1143)
%onnx::Conv_1140 = Identity(%onnx::Conv_1092)
%onnx::Conv_1137 = Identity(%onnx::Conv_1092)
%onnx::Conv_1134 = Identity(%onnx::Conv_1092)
%onnx::Conv_1131 = Identity(%onnx::Conv_1080)
%onnx::Conv_1128 = Identity(%onnx::Conv_1080)
%onnx::Conv_1125 = Identity(%onnx::Conv_1080)
%onnx::Conv_1122 = Identity(%onnx::Conv_1080)
%onnx::Conv_1119 = Identity(%onnx::Conv_1092)
%onnx::Conv_1116 = Identity(%onnx::Conv_1092)
%onnx::Conv_1113 = Identity(%onnx::Conv_1092)
%onnx::Conv_1110 = Identity(%onnx::Conv_1080)
%onnx::Conv_1107 = Identity(%onnx::Conv_1080)
%onnx::Conv_1104 = Identity(%onnx::Conv_1080)
%onnx::Conv_1101 = Identity(%onnx::Conv_1080)
%onnx::Conv_1098 = Identity(%onnx::Conv_1092)
%onnx::Conv_1095 = Identity(%onnx::Conv_1092)
%onnx::Conv_1089 = Identity(%onnx::Conv_1080)
%onnx::Conv_1086 = Identity(%onnx::Conv_1080)
%onnx::Conv_1083 = Identity(%onnx::Conv_1080)
%onnx::Conv_1077 = Identity(%onnx::Conv_1035)
%onnx::Conv_1074 = Identity(%onnx::Conv_1017)
%onnx::Conv_1071 = Identity(%onnx::Conv_1017)
%onnx::Conv_1068 = Identity(%onnx::Conv_1017)
%onnx::Conv_1065 = Identity(%onnx::Conv_1017)
%onnx::Conv_1062 = Identity(%onnx::Conv_1017)
%onnx::Conv_1059 = Identity(%onnx::Conv_1017)
%onnx::Conv_1056 = Identity(%onnx::Conv_1035)
%onnx::Conv_1053 = Identity(%onnx::Conv_1017)
%onnx::Conv_1050 = Identity(%onnx::Conv_1017)
%onnx::Conv_1047 = Identity(%onnx::Conv_1017)
%onnx::Conv_1044 = Identity(%onnx::Conv_1017)
%onnx::Conv_1041 = Identity(%onnx::Conv_1017)
%onnx::Conv_1038 = Identity(%onnx::Conv_1017)
%onnx::Conv_1032 = Identity(%onnx::Conv_1017)
%onnx::Conv_1029 = Identity(%onnx::Conv_1017)
%onnx::Conv_1026 = Identity(%onnx::Conv_1017)
%onnx::Conv_1023 = Identity(%onnx::Conv_1017)
%onnx::Conv_1020 = Identity(%onnx::Conv_1017)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_6_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_7_output_0)
%/layers.1/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_8_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_6_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_7_output_0)
%/layers.2/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_8_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_6_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_7_output_0)
%/layers.3/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_8_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_4_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_7_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_8_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_4_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_7_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_8_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_4_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_7_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_8_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_6_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_7_output_0)
%/layers.9/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_8_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1169, %onnx::Conv_1170)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1172, %onnx::Conv_1173)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1175, %onnx::Conv_1176)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1178, %onnx::Conv_1179)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_6_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_7_output_0)
%/layers.10/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_8_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1181, %onnx::Conv_1182)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1184, %onnx::Conv_1185)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1187, %onnx::Conv_1188)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1190, %onnx::Conv_1191)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1193, %onnx::Conv_1194)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1196, %onnx::Conv_1197)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1199, %onnx::Conv_1200)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_6_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_7_output_0)
%/layers.11/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_8_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1202, %onnx::Conv_1203)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%1011 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %1011
}
|
val_accuracy
| 92.548078
| 1,444,198,912
| 4,848,869
|
{'zcp_epe_nas': 98.7109318155077, 'zcp_fisher': 50.160823822021484, 'zcp_flops': 23107182592.0, 'zcp_grad_norm': 144.237060546875, 'zcp_grasp': 16.24658203125, 'zcp_jacov': -16.060370547472253, 'zcp_l2_norm': 1008.3545532226562, 'zcp_nwot': 220.7732972740879, 'zcp_params': 4848869.0, 'zcp_plain': 0.047844164073467005, 'zcp_snip': 724.8134765625, 'zcp_synflow': 125.04169030024728, 'zcp_zen': 113.01172637939453, 'zcp_val_accuracy': 0.9227764606475831}
| |
NASBench101_344894
|
NASBench101
|
344894
|
d078162fd5905471a22105565f2631ef
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_797[FLOAT, 128x3x3x3]
%onnx::Conv_798[FLOAT, 128]
%onnx::Conv_800[FLOAT, 64x128x1x1]
%onnx::Conv_801[FLOAT, 64]
%onnx::Conv_803[FLOAT, 64x64x1x1]
%onnx::Conv_806[FLOAT, 64x64x1x1]
%onnx::Conv_809[FLOAT, 64x128x1x1]
%onnx::Conv_812[FLOAT, 64x64x3x3]
%onnx::Conv_815[FLOAT, 64x128x1x1]
%onnx::Conv_818[FLOAT, 64x64x1x1]
%onnx::Conv_821[FLOAT, 64x64x1x1]
%onnx::Conv_824[FLOAT, 64x128x1x1]
%onnx::Conv_827[FLOAT, 64x64x3x3]
%onnx::Conv_830[FLOAT, 64x128x1x1]
%onnx::Conv_833[FLOAT, 64x64x1x1]
%onnx::Conv_836[FLOAT, 64x64x1x1]
%onnx::Conv_839[FLOAT, 64x128x1x1]
%onnx::Conv_842[FLOAT, 64x64x3x3]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x1x1]
%onnx::Conv_851[FLOAT, 128x128x1x1]
%onnx::Conv_854[FLOAT, 128x128x1x1]
%onnx::Conv_857[FLOAT, 128x128x3x3]
%onnx::Conv_860[FLOAT, 128x256x1x1]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%onnx::Conv_866[FLOAT, 128x128x1x1]
%onnx::Conv_869[FLOAT, 128x256x1x1]
%onnx::Conv_872[FLOAT, 128x128x3x3]
%onnx::Conv_875[FLOAT, 128x256x1x1]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 128x128x1x1]
%onnx::Conv_884[FLOAT, 128x256x1x1]
%onnx::Conv_887[FLOAT, 128x128x3x3]
%onnx::Conv_890[FLOAT, 256x256x1x1]
%onnx::Conv_891[FLOAT, 256]
%onnx::Conv_893[FLOAT, 256x256x1x1]
%onnx::Conv_896[FLOAT, 256x256x1x1]
%onnx::Conv_899[FLOAT, 256x256x1x1]
%onnx::Conv_902[FLOAT, 256x256x3x3]
%onnx::Conv_905[FLOAT, 256x512x1x1]
%onnx::Conv_908[FLOAT, 256x256x1x1]
%onnx::Conv_911[FLOAT, 256x256x1x1]
%onnx::Conv_914[FLOAT, 256x512x1x1]
%onnx::Conv_917[FLOAT, 256x256x3x3]
%onnx::Conv_920[FLOAT, 256x512x1x1]
%onnx::Conv_923[FLOAT, 256x256x1x1]
%onnx::Conv_926[FLOAT, 256x256x1x1]
%onnx::Conv_929[FLOAT, 256x512x1x1]
%onnx::Conv_932[FLOAT, 256x256x3x3]
) {
%onnx::Conv_933 = Identity(%onnx::Conv_891)
%onnx::Conv_930 = Identity(%onnx::Conv_891)
%onnx::Conv_927 = Identity(%onnx::Conv_891)
%onnx::Conv_924 = Identity(%onnx::Conv_891)
%onnx::Conv_921 = Identity(%onnx::Conv_891)
%onnx::Conv_918 = Identity(%onnx::Conv_891)
%onnx::Conv_915 = Identity(%onnx::Conv_891)
%onnx::Conv_912 = Identity(%onnx::Conv_891)
%onnx::Conv_909 = Identity(%onnx::Conv_891)
%onnx::Conv_906 = Identity(%onnx::Conv_891)
%onnx::Conv_903 = Identity(%onnx::Conv_891)
%onnx::Conv_900 = Identity(%onnx::Conv_891)
%onnx::Conv_897 = Identity(%onnx::Conv_891)
%onnx::Conv_894 = Identity(%onnx::Conv_891)
%onnx::Conv_888 = Identity(%onnx::Conv_798)
%onnx::Conv_885 = Identity(%onnx::Conv_798)
%onnx::Conv_882 = Identity(%onnx::Conv_798)
%onnx::Conv_879 = Identity(%onnx::Conv_798)
%onnx::Conv_876 = Identity(%onnx::Conv_798)
%onnx::Conv_873 = Identity(%onnx::Conv_798)
%onnx::Conv_870 = Identity(%onnx::Conv_798)
%onnx::Conv_867 = Identity(%onnx::Conv_798)
%onnx::Conv_864 = Identity(%onnx::Conv_798)
%onnx::Conv_861 = Identity(%onnx::Conv_798)
%onnx::Conv_858 = Identity(%onnx::Conv_798)
%onnx::Conv_855 = Identity(%onnx::Conv_798)
%onnx::Conv_852 = Identity(%onnx::Conv_798)
%onnx::Conv_849 = Identity(%onnx::Conv_798)
%onnx::Conv_846 = Identity(%onnx::Conv_798)
%onnx::Conv_843 = Identity(%onnx::Conv_801)
%onnx::Conv_840 = Identity(%onnx::Conv_801)
%onnx::Conv_837 = Identity(%onnx::Conv_801)
%onnx::Conv_834 = Identity(%onnx::Conv_801)
%onnx::Conv_831 = Identity(%onnx::Conv_801)
%onnx::Conv_828 = Identity(%onnx::Conv_801)
%onnx::Conv_825 = Identity(%onnx::Conv_801)
%onnx::Conv_822 = Identity(%onnx::Conv_801)
%onnx::Conv_819 = Identity(%onnx::Conv_801)
%onnx::Conv_816 = Identity(%onnx::Conv_801)
%onnx::Conv_813 = Identity(%onnx::Conv_801)
%onnx::Conv_810 = Identity(%onnx::Conv_801)
%onnx::Conv_807 = Identity(%onnx::Conv_801)
%onnx::Conv_804 = Identity(%onnx::Conv_801)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_797, %onnx::Conv_798)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%795 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %795
}
|
val_accuracy
| 89.713544
| 1,120,806,912
| 3,729,162
|
{'zcp_epe_nas': 115.24836227374112, 'zcp_fisher': 39.65087890625, 'zcp_flops': 17932910592.0, 'zcp_grad_norm': 122.11173248291016, 'zcp_grasp': 10.432373046875, 'zcp_jacov': -16.043540224773267, 'zcp_l2_norm': 844.3543701171875, 'zcp_nwot': 221.84411061787202, 'zcp_params': 3729162.0, 'zcp_plain': 0.030166830867528003, 'zcp_snip': 700.3019409179688, 'zcp_synflow': 113.56396536163155, 'zcp_zen': 85.22705078125, 'zcp_val_accuracy': 0.9211738705635071}
| |
NASBench101_249081
|
NASBench101
|
249081
|
96c5e1c27c35d80c3303f93281e80a26
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_779[FLOAT, 128x3x3x3]
%onnx::Conv_780[FLOAT, 128]
%onnx::Conv_782[FLOAT, 64x128x1x1]
%onnx::Conv_783[FLOAT, 64]
%onnx::Conv_785[FLOAT, 64x64x1x1]
%onnx::Conv_788[FLOAT, 64x64x3x3]
%onnx::Conv_791[FLOAT, 64x128x1x1]
%onnx::Conv_794[FLOAT, 64x64x3x3]
%onnx::Conv_797[FLOAT, 64x128x1x1]
%onnx::Conv_800[FLOAT, 64x64x1x1]
%onnx::Conv_803[FLOAT, 64x64x3x3]
%onnx::Conv_806[FLOAT, 64x128x1x1]
%onnx::Conv_809[FLOAT, 64x64x3x3]
%onnx::Conv_812[FLOAT, 64x128x1x1]
%onnx::Conv_815[FLOAT, 64x64x1x1]
%onnx::Conv_818[FLOAT, 64x64x3x3]
%onnx::Conv_821[FLOAT, 64x128x1x1]
%onnx::Conv_824[FLOAT, 64x64x3x3]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 128x128x1x1]
%onnx::Conv_833[FLOAT, 128x128x3x3]
%onnx::Conv_836[FLOAT, 128x128x1x1]
%onnx::Conv_839[FLOAT, 128x128x3x3]
%onnx::Conv_842[FLOAT, 128x256x1x1]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x3x3]
%onnx::Conv_851[FLOAT, 128x256x1x1]
%onnx::Conv_854[FLOAT, 128x128x3x3]
%onnx::Conv_857[FLOAT, 128x256x1x1]
%onnx::Conv_860[FLOAT, 128x128x1x1]
%onnx::Conv_863[FLOAT, 128x128x3x3]
%onnx::Conv_866[FLOAT, 128x256x1x1]
%onnx::Conv_869[FLOAT, 128x128x3x3]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_873[FLOAT, 256]
%onnx::Conv_875[FLOAT, 256x256x1x1]
%onnx::Conv_878[FLOAT, 256x256x3x3]
%onnx::Conv_881[FLOAT, 256x256x1x1]
%onnx::Conv_884[FLOAT, 256x256x3x3]
%onnx::Conv_887[FLOAT, 256x512x1x1]
%onnx::Conv_890[FLOAT, 256x256x1x1]
%onnx::Conv_893[FLOAT, 256x256x3x3]
%onnx::Conv_896[FLOAT, 256x512x1x1]
%onnx::Conv_899[FLOAT, 256x256x3x3]
%onnx::Conv_902[FLOAT, 256x512x1x1]
%onnx::Conv_905[FLOAT, 256x256x1x1]
%onnx::Conv_908[FLOAT, 256x256x3x3]
%onnx::Conv_911[FLOAT, 256x512x1x1]
%onnx::Conv_914[FLOAT, 256x256x3x3]
) {
%onnx::Conv_915 = Identity(%onnx::Conv_873)
%onnx::Conv_912 = Identity(%onnx::Conv_873)
%onnx::Conv_909 = Identity(%onnx::Conv_873)
%onnx::Conv_906 = Identity(%onnx::Conv_873)
%onnx::Conv_903 = Identity(%onnx::Conv_873)
%onnx::Conv_900 = Identity(%onnx::Conv_873)
%onnx::Conv_897 = Identity(%onnx::Conv_873)
%onnx::Conv_894 = Identity(%onnx::Conv_873)
%onnx::Conv_891 = Identity(%onnx::Conv_873)
%onnx::Conv_888 = Identity(%onnx::Conv_873)
%onnx::Conv_885 = Identity(%onnx::Conv_873)
%onnx::Conv_882 = Identity(%onnx::Conv_873)
%onnx::Conv_879 = Identity(%onnx::Conv_873)
%onnx::Conv_876 = Identity(%onnx::Conv_873)
%onnx::Conv_870 = Identity(%onnx::Conv_780)
%onnx::Conv_867 = Identity(%onnx::Conv_780)
%onnx::Conv_864 = Identity(%onnx::Conv_780)
%onnx::Conv_861 = Identity(%onnx::Conv_780)
%onnx::Conv_858 = Identity(%onnx::Conv_780)
%onnx::Conv_855 = Identity(%onnx::Conv_780)
%onnx::Conv_852 = Identity(%onnx::Conv_780)
%onnx::Conv_849 = Identity(%onnx::Conv_780)
%onnx::Conv_846 = Identity(%onnx::Conv_780)
%onnx::Conv_843 = Identity(%onnx::Conv_780)
%onnx::Conv_840 = Identity(%onnx::Conv_780)
%onnx::Conv_837 = Identity(%onnx::Conv_780)
%onnx::Conv_834 = Identity(%onnx::Conv_780)
%onnx::Conv_831 = Identity(%onnx::Conv_780)
%onnx::Conv_828 = Identity(%onnx::Conv_780)
%onnx::Conv_825 = Identity(%onnx::Conv_783)
%onnx::Conv_822 = Identity(%onnx::Conv_783)
%onnx::Conv_819 = Identity(%onnx::Conv_783)
%onnx::Conv_816 = Identity(%onnx::Conv_783)
%onnx::Conv_813 = Identity(%onnx::Conv_783)
%onnx::Conv_810 = Identity(%onnx::Conv_783)
%onnx::Conv_807 = Identity(%onnx::Conv_783)
%onnx::Conv_804 = Identity(%onnx::Conv_783)
%onnx::Conv_801 = Identity(%onnx::Conv_783)
%onnx::Conv_798 = Identity(%onnx::Conv_783)
%onnx::Conv_795 = Identity(%onnx::Conv_783)
%onnx::Conv_792 = Identity(%onnx::Conv_783)
%onnx::Conv_789 = Identity(%onnx::Conv_783)
%onnx::Conv_786 = Identity(%onnx::Conv_783)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_779, %onnx::Conv_780)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%777 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %777
}
|
val_accuracy
| 90.564907
| 1,724,786,688
| 5,793,546
|
{'zcp_epe_nas': 92.74904216638902, 'zcp_fisher': 224.9163055419922, 'zcp_flops': 27596587008.0, 'zcp_grad_norm': 235.50631713867188, 'zcp_grasp': -37.75830078125, 'zcp_jacov': -16.046014311674828, 'zcp_l2_norm': 843.6663818359375, 'zcp_nwot': 221.57332831146815, 'zcp_params': 5793546.0, 'zcp_plain': 0.10602446645498201, 'zcp_snip': 1404.463134765625, 'zcp_synflow': 123.45857793446035, 'zcp_zen': 90.70398712158203, 'zcp_val_accuracy': 0.8832131624221801}
| |
NASBench101_408775
|
NASBench101
|
408775
|
f70858f3786a527d88dd9cf4b3a615ef
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_644[FLOAT, 128x3x3x3]
%onnx::Conv_645[FLOAT, 128]
%onnx::Conv_647[FLOAT, 128x128x1x1]
%onnx::Conv_650[FLOAT, 128x128x1x1]
%onnx::Conv_653[FLOAT, 128x128x1x1]
%onnx::Conv_656[FLOAT, 128x128x1x1]
%onnx::Conv_659[FLOAT, 128x128x1x1]
%onnx::Conv_662[FLOAT, 128x128x1x1]
%onnx::Conv_665[FLOAT, 128x128x1x1]
%onnx::Conv_668[FLOAT, 128x128x1x1]
%onnx::Conv_671[FLOAT, 128x128x1x1]
%onnx::Conv_674[FLOAT, 128x128x1x1]
%onnx::Conv_677[FLOAT, 128x128x1x1]
%onnx::Conv_680[FLOAT, 128x128x1x1]
%onnx::Conv_683[FLOAT, 256x128x1x1]
%onnx::Conv_684[FLOAT, 256]
%onnx::Conv_686[FLOAT, 256x128x1x1]
%onnx::Conv_689[FLOAT, 256x256x1x1]
%onnx::Conv_692[FLOAT, 256x128x1x1]
%onnx::Conv_695[FLOAT, 256x256x1x1]
%onnx::Conv_698[FLOAT, 256x256x1x1]
%onnx::Conv_701[FLOAT, 256x256x1x1]
%onnx::Conv_704[FLOAT, 256x256x1x1]
%onnx::Conv_707[FLOAT, 256x256x1x1]
%onnx::Conv_710[FLOAT, 256x256x1x1]
%onnx::Conv_713[FLOAT, 256x256x1x1]
%onnx::Conv_716[FLOAT, 256x256x1x1]
%onnx::Conv_719[FLOAT, 512x256x1x1]
%onnx::Conv_720[FLOAT, 512]
%onnx::Conv_722[FLOAT, 512x256x1x1]
%onnx::Conv_725[FLOAT, 512x512x1x1]
%onnx::Conv_728[FLOAT, 512x256x1x1]
%onnx::Conv_731[FLOAT, 512x512x1x1]
%onnx::Conv_734[FLOAT, 512x512x1x1]
%onnx::Conv_737[FLOAT, 512x512x1x1]
%onnx::Conv_740[FLOAT, 512x512x1x1]
%onnx::Conv_743[FLOAT, 512x512x1x1]
%onnx::Conv_746[FLOAT, 512x512x1x1]
%onnx::Conv_749[FLOAT, 512x512x1x1]
%onnx::Conv_752[FLOAT, 512x512x1x1]
) {
%onnx::Conv_753 = Identity(%onnx::Conv_720)
%onnx::Conv_750 = Identity(%onnx::Conv_720)
%onnx::Conv_747 = Identity(%onnx::Conv_720)
%onnx::Conv_744 = Identity(%onnx::Conv_720)
%onnx::Conv_741 = Identity(%onnx::Conv_720)
%onnx::Conv_738 = Identity(%onnx::Conv_720)
%onnx::Conv_735 = Identity(%onnx::Conv_720)
%onnx::Conv_732 = Identity(%onnx::Conv_720)
%onnx::Conv_729 = Identity(%onnx::Conv_720)
%onnx::Conv_726 = Identity(%onnx::Conv_720)
%onnx::Conv_723 = Identity(%onnx::Conv_720)
%onnx::Conv_717 = Identity(%onnx::Conv_684)
%onnx::Conv_714 = Identity(%onnx::Conv_684)
%onnx::Conv_711 = Identity(%onnx::Conv_684)
%onnx::Conv_708 = Identity(%onnx::Conv_684)
%onnx::Conv_705 = Identity(%onnx::Conv_684)
%onnx::Conv_702 = Identity(%onnx::Conv_684)
%onnx::Conv_699 = Identity(%onnx::Conv_684)
%onnx::Conv_696 = Identity(%onnx::Conv_684)
%onnx::Conv_693 = Identity(%onnx::Conv_684)
%onnx::Conv_690 = Identity(%onnx::Conv_684)
%onnx::Conv_687 = Identity(%onnx::Conv_684)
%onnx::Conv_681 = Identity(%onnx::Conv_645)
%onnx::Conv_678 = Identity(%onnx::Conv_645)
%onnx::Conv_675 = Identity(%onnx::Conv_645)
%onnx::Conv_672 = Identity(%onnx::Conv_645)
%onnx::Conv_669 = Identity(%onnx::Conv_645)
%onnx::Conv_666 = Identity(%onnx::Conv_645)
%onnx::Conv_663 = Identity(%onnx::Conv_645)
%onnx::Conv_660 = Identity(%onnx::Conv_645)
%onnx::Conv_657 = Identity(%onnx::Conv_645)
%onnx::Conv_654 = Identity(%onnx::Conv_645)
%onnx::Conv_651 = Identity(%onnx::Conv_645)
%onnx::Conv_648 = Identity(%onnx::Conv_645)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_644, %onnx::Conv_645)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_647, %onnx::Conv_648)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_650, %onnx::Conv_651)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_653, %onnx::Conv_654)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_656, %onnx::Conv_657)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_659, %onnx::Conv_660)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_662, %onnx::Conv_663)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%642 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %642
}
|
val_accuracy
| 89.172679
| 1,137,453,056
| 3,667,594
|
{'zcp_epe_nas': 86.94020073017842, 'zcp_fisher': 19.774362564086914, 'zcp_flops': 18199248896.0, 'zcp_grad_norm': 90.55517578125, 'zcp_grasp': -55.61151123046875, 'zcp_jacov': -16.07588273229922, 'zcp_l2_norm': 802.7783813476562, 'zcp_nwot': 228.38925870211932, 'zcp_params': 3667594.0, 'zcp_plain': 0.14145618677139202, 'zcp_snip': 627.8427734375, 'zcp_synflow': 64.22553785985163, 'zcp_zen': 80.48339080810547, 'zcp_val_accuracy': 0.9193710088729851}
| |
NASBench101_332060
|
NASBench101
|
332060
|
c8df96418dbd22bb3fe4dd5377670527
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_1040[FLOAT, 128x3x3x3]
%onnx::Conv_1041[FLOAT, 128]
%onnx::Conv_1043[FLOAT, 128x128x1x1]
%onnx::Conv_1046[FLOAT, 128x128x3x3]
%onnx::Conv_1049[FLOAT, 128x128x1x1]
%onnx::Conv_1052[FLOAT, 128x128x1x1]
%onnx::Conv_1055[FLOAT, 128x128x1x1]
%onnx::Conv_1058[FLOAT, 128x128x1x1]
%onnx::Conv_1061[FLOAT, 128x128x1x1]
%onnx::Conv_1064[FLOAT, 128x128x1x1]
%onnx::Conv_1067[FLOAT, 128x128x1x1]
%onnx::Conv_1070[FLOAT, 128x128x3x3]
%onnx::Conv_1073[FLOAT, 128x128x1x1]
%onnx::Conv_1076[FLOAT, 128x128x1x1]
%onnx::Conv_1079[FLOAT, 128x128x1x1]
%onnx::Conv_1082[FLOAT, 128x128x1x1]
%onnx::Conv_1085[FLOAT, 128x128x1x1]
%onnx::Conv_1088[FLOAT, 128x128x1x1]
%onnx::Conv_1091[FLOAT, 128x128x1x1]
%onnx::Conv_1094[FLOAT, 128x128x3x3]
%onnx::Conv_1097[FLOAT, 128x128x1x1]
%onnx::Conv_1100[FLOAT, 128x128x1x1]
%onnx::Conv_1103[FLOAT, 128x128x1x1]
%onnx::Conv_1106[FLOAT, 128x128x1x1]
%onnx::Conv_1109[FLOAT, 128x128x1x1]
%onnx::Conv_1112[FLOAT, 128x128x1x1]
%onnx::Conv_1115[FLOAT, 256x128x1x1]
%onnx::Conv_1116[FLOAT, 256]
%onnx::Conv_1118[FLOAT, 256x256x3x3]
%onnx::Conv_1121[FLOAT, 256x128x1x1]
%onnx::Conv_1124[FLOAT, 256x256x1x1]
%onnx::Conv_1127[FLOAT, 256x256x1x1]
%onnx::Conv_1130[FLOAT, 256x128x1x1]
%onnx::Conv_1133[FLOAT, 256x256x1x1]
%onnx::Conv_1136[FLOAT, 256x128x1x1]
%onnx::Conv_1139[FLOAT, 256x256x1x1]
%onnx::Conv_1142[FLOAT, 256x256x3x3]
%onnx::Conv_1145[FLOAT, 256x256x1x1]
%onnx::Conv_1148[FLOAT, 256x256x1x1]
%onnx::Conv_1151[FLOAT, 256x256x1x1]
%onnx::Conv_1154[FLOAT, 256x256x1x1]
%onnx::Conv_1157[FLOAT, 256x256x1x1]
%onnx::Conv_1160[FLOAT, 256x256x1x1]
%onnx::Conv_1163[FLOAT, 256x256x1x1]
%onnx::Conv_1166[FLOAT, 256x256x3x3]
%onnx::Conv_1169[FLOAT, 256x256x1x1]
%onnx::Conv_1172[FLOAT, 256x256x1x1]
%onnx::Conv_1175[FLOAT, 256x256x1x1]
%onnx::Conv_1178[FLOAT, 256x256x1x1]
%onnx::Conv_1181[FLOAT, 256x256x1x1]
%onnx::Conv_1184[FLOAT, 256x256x1x1]
%onnx::Conv_1187[FLOAT, 512x256x1x1]
%onnx::Conv_1188[FLOAT, 512]
%onnx::Conv_1190[FLOAT, 512x512x3x3]
%onnx::Conv_1193[FLOAT, 512x256x1x1]
%onnx::Conv_1196[FLOAT, 512x512x1x1]
%onnx::Conv_1199[FLOAT, 512x512x1x1]
%onnx::Conv_1202[FLOAT, 512x256x1x1]
%onnx::Conv_1205[FLOAT, 512x512x1x1]
%onnx::Conv_1208[FLOAT, 512x256x1x1]
%onnx::Conv_1211[FLOAT, 512x512x1x1]
%onnx::Conv_1214[FLOAT, 512x512x3x3]
%onnx::Conv_1217[FLOAT, 512x512x1x1]
%onnx::Conv_1220[FLOAT, 512x512x1x1]
%onnx::Conv_1223[FLOAT, 512x512x1x1]
%onnx::Conv_1226[FLOAT, 512x512x1x1]
%onnx::Conv_1229[FLOAT, 512x512x1x1]
%onnx::Conv_1232[FLOAT, 512x512x1x1]
%onnx::Conv_1235[FLOAT, 512x512x1x1]
%onnx::Conv_1238[FLOAT, 512x512x3x3]
%onnx::Conv_1241[FLOAT, 512x512x1x1]
%onnx::Conv_1244[FLOAT, 512x512x1x1]
%onnx::Conv_1247[FLOAT, 512x512x1x1]
%onnx::Conv_1250[FLOAT, 512x512x1x1]
%onnx::Conv_1253[FLOAT, 512x512x1x1]
%onnx::Conv_1256[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1257 = Identity(%onnx::Conv_1188)
%onnx::Conv_1254 = Identity(%onnx::Conv_1188)
%onnx::Conv_1251 = Identity(%onnx::Conv_1188)
%onnx::Conv_1248 = Identity(%onnx::Conv_1188)
%onnx::Conv_1245 = Identity(%onnx::Conv_1188)
%onnx::Conv_1242 = Identity(%onnx::Conv_1188)
%onnx::Conv_1239 = Identity(%onnx::Conv_1188)
%onnx::Conv_1236 = Identity(%onnx::Conv_1188)
%onnx::Conv_1233 = Identity(%onnx::Conv_1188)
%onnx::Conv_1230 = Identity(%onnx::Conv_1188)
%onnx::Conv_1227 = Identity(%onnx::Conv_1188)
%onnx::Conv_1224 = Identity(%onnx::Conv_1188)
%onnx::Conv_1221 = Identity(%onnx::Conv_1188)
%onnx::Conv_1218 = Identity(%onnx::Conv_1188)
%onnx::Conv_1215 = Identity(%onnx::Conv_1188)
%onnx::Conv_1212 = Identity(%onnx::Conv_1188)
%onnx::Conv_1209 = Identity(%onnx::Conv_1188)
%onnx::Conv_1206 = Identity(%onnx::Conv_1188)
%onnx::Conv_1203 = Identity(%onnx::Conv_1188)
%onnx::Conv_1200 = Identity(%onnx::Conv_1188)
%onnx::Conv_1197 = Identity(%onnx::Conv_1188)
%onnx::Conv_1194 = Identity(%onnx::Conv_1188)
%onnx::Conv_1191 = Identity(%onnx::Conv_1188)
%onnx::Conv_1185 = Identity(%onnx::Conv_1116)
%onnx::Conv_1182 = Identity(%onnx::Conv_1116)
%onnx::Conv_1179 = Identity(%onnx::Conv_1116)
%onnx::Conv_1176 = Identity(%onnx::Conv_1116)
%onnx::Conv_1173 = Identity(%onnx::Conv_1116)
%onnx::Conv_1170 = Identity(%onnx::Conv_1116)
%onnx::Conv_1167 = Identity(%onnx::Conv_1116)
%onnx::Conv_1164 = Identity(%onnx::Conv_1116)
%onnx::Conv_1161 = Identity(%onnx::Conv_1116)
%onnx::Conv_1158 = Identity(%onnx::Conv_1116)
%onnx::Conv_1155 = Identity(%onnx::Conv_1116)
%onnx::Conv_1152 = Identity(%onnx::Conv_1116)
%onnx::Conv_1149 = Identity(%onnx::Conv_1116)
%onnx::Conv_1146 = Identity(%onnx::Conv_1116)
%onnx::Conv_1143 = Identity(%onnx::Conv_1116)
%onnx::Conv_1140 = Identity(%onnx::Conv_1116)
%onnx::Conv_1137 = Identity(%onnx::Conv_1116)
%onnx::Conv_1134 = Identity(%onnx::Conv_1116)
%onnx::Conv_1131 = Identity(%onnx::Conv_1116)
%onnx::Conv_1128 = Identity(%onnx::Conv_1116)
%onnx::Conv_1125 = Identity(%onnx::Conv_1116)
%onnx::Conv_1122 = Identity(%onnx::Conv_1116)
%onnx::Conv_1119 = Identity(%onnx::Conv_1116)
%onnx::Conv_1113 = Identity(%onnx::Conv_1041)
%onnx::Conv_1110 = Identity(%onnx::Conv_1041)
%onnx::Conv_1107 = Identity(%onnx::Conv_1041)
%onnx::Conv_1104 = Identity(%onnx::Conv_1041)
%onnx::Conv_1101 = Identity(%onnx::Conv_1041)
%onnx::Conv_1098 = Identity(%onnx::Conv_1041)
%onnx::Conv_1095 = Identity(%onnx::Conv_1041)
%onnx::Conv_1092 = Identity(%onnx::Conv_1041)
%onnx::Conv_1089 = Identity(%onnx::Conv_1041)
%onnx::Conv_1086 = Identity(%onnx::Conv_1041)
%onnx::Conv_1083 = Identity(%onnx::Conv_1041)
%onnx::Conv_1080 = Identity(%onnx::Conv_1041)
%onnx::Conv_1077 = Identity(%onnx::Conv_1041)
%onnx::Conv_1074 = Identity(%onnx::Conv_1041)
%onnx::Conv_1071 = Identity(%onnx::Conv_1041)
%onnx::Conv_1068 = Identity(%onnx::Conv_1041)
%onnx::Conv_1065 = Identity(%onnx::Conv_1041)
%onnx::Conv_1062 = Identity(%onnx::Conv_1041)
%onnx::Conv_1059 = Identity(%onnx::Conv_1041)
%onnx::Conv_1056 = Identity(%onnx::Conv_1041)
%onnx::Conv_1053 = Identity(%onnx::Conv_1041)
%onnx::Conv_1050 = Identity(%onnx::Conv_1041)
%onnx::Conv_1047 = Identity(%onnx::Conv_1041)
%onnx::Conv_1044 = Identity(%onnx::Conv_1041)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_6_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1169, %onnx::Conv_1170)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1172, %onnx::Conv_1173)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1175, %onnx::Conv_1176)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1178, %onnx::Conv_1179)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1181, %onnx::Conv_1182)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1184, %onnx::Conv_1185)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_6_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1187, %onnx::Conv_1188)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1190, %onnx::Conv_1191)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1193, %onnx::Conv_1194)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1196, %onnx::Conv_1197)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1199, %onnx::Conv_1200)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1202, %onnx::Conv_1203)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1205, %onnx::Conv_1206)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1208, %onnx::Conv_1209)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1211, %onnx::Conv_1212)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1214, %onnx::Conv_1215)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1217, %onnx::Conv_1218)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1220, %onnx::Conv_1221)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1223, %onnx::Conv_1224)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1226, %onnx::Conv_1227)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1229, %onnx::Conv_1230)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1232, %onnx::Conv_1233)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1235, %onnx::Conv_1236)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1238, %onnx::Conv_1239)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1241, %onnx::Conv_1242)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1244, %onnx::Conv_1245)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1247, %onnx::Conv_1248)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1250, %onnx::Conv_1251)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1253, %onnx::Conv_1254)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1256, %onnx::Conv_1257)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_6_output_0)
%1038 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %1038
}
|
val_accuracy
| 93.960339
| 4,749,797,376
| 15,911,562
|
{'zcp_epe_nas': 88.63654316410125, 'zcp_fisher': 2.042495489120483, 'zcp_flops': 75996758016.0, 'zcp_grad_norm': 42.25706100463867, 'zcp_grasp': -0.96417236328125, 'zcp_jacov': -16.04833751175434, 'zcp_l2_norm': 1634.1436767578125, 'zcp_nwot': 240.0924861796609, 'zcp_params': 15911562.0, 'zcp_plain': 0.03217851370573, 'zcp_snip': 337.1332702636719, 'zcp_synflow': 122.0888241831034, 'zcp_zen': 134.9585723876953, 'zcp_val_accuracy': 0.897235572338104}
| |
NASBench101_320568
|
NASBench101
|
320568
|
c1f7198f2c6a783d9c60ba2a9af88953
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_851[FLOAT, 128x3x3x3]
%onnx::Conv_852[FLOAT, 128]
%onnx::Conv_854[FLOAT, 128x128x1x1]
%onnx::Conv_857[FLOAT, 128x128x3x3]
%onnx::Conv_860[FLOAT, 128x128x1x1]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%onnx::Conv_866[FLOAT, 128x128x1x1]
%onnx::Conv_869[FLOAT, 128x128x3x3]
%onnx::Conv_872[FLOAT, 128x128x1x1]
%onnx::Conv_875[FLOAT, 128x128x3x3]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 128x128x1x1]
%onnx::Conv_884[FLOAT, 128x128x1x1]
%onnx::Conv_887[FLOAT, 128x128x3x3]
%onnx::Conv_890[FLOAT, 128x128x1x1]
%onnx::Conv_893[FLOAT, 128x128x3x3]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%onnx::Conv_899[FLOAT, 128x128x1x1]
%onnx::Conv_902[FLOAT, 128x128x1x1]
%onnx::Conv_905[FLOAT, 128x128x3x3]
%onnx::Conv_908[FLOAT, 256x128x1x1]
%onnx::Conv_909[FLOAT, 256]
%onnx::Conv_911[FLOAT, 256x256x3x3]
%onnx::Conv_914[FLOAT, 256x128x1x1]
%onnx::Conv_917[FLOAT, 256x256x1x1]
%onnx::Conv_920[FLOAT, 256x256x1x1]
%onnx::Conv_923[FLOAT, 256x256x3x3]
%onnx::Conv_926[FLOAT, 256x256x1x1]
%onnx::Conv_929[FLOAT, 256x256x3x3]
%onnx::Conv_932[FLOAT, 256x256x1x1]
%onnx::Conv_935[FLOAT, 256x256x1x1]
%onnx::Conv_938[FLOAT, 256x256x1x1]
%onnx::Conv_941[FLOAT, 256x256x3x3]
%onnx::Conv_944[FLOAT, 256x256x1x1]
%onnx::Conv_947[FLOAT, 256x256x3x3]
%onnx::Conv_950[FLOAT, 256x256x1x1]
%onnx::Conv_953[FLOAT, 256x256x1x1]
%onnx::Conv_956[FLOAT, 256x256x1x1]
%onnx::Conv_959[FLOAT, 256x256x3x3]
%onnx::Conv_962[FLOAT, 512x256x1x1]
%onnx::Conv_963[FLOAT, 512]
%onnx::Conv_965[FLOAT, 512x512x3x3]
%onnx::Conv_968[FLOAT, 512x256x1x1]
%onnx::Conv_971[FLOAT, 512x512x1x1]
%onnx::Conv_974[FLOAT, 512x512x1x1]
%onnx::Conv_977[FLOAT, 512x512x3x3]
%onnx::Conv_980[FLOAT, 512x512x1x1]
%onnx::Conv_983[FLOAT, 512x512x3x3]
%onnx::Conv_986[FLOAT, 512x512x1x1]
%onnx::Conv_989[FLOAT, 512x512x1x1]
%onnx::Conv_992[FLOAT, 512x512x1x1]
%onnx::Conv_995[FLOAT, 512x512x3x3]
%onnx::Conv_998[FLOAT, 512x512x1x1]
%onnx::Conv_1001[FLOAT, 512x512x3x3]
%onnx::Conv_1004[FLOAT, 512x512x1x1]
%onnx::Conv_1007[FLOAT, 512x512x1x1]
%onnx::Conv_1010[FLOAT, 512x512x1x1]
%onnx::Conv_1013[FLOAT, 512x512x3x3]
) {
%onnx::Conv_1014 = Identity(%onnx::Conv_963)
%onnx::Conv_1011 = Identity(%onnx::Conv_963)
%onnx::Conv_1008 = Identity(%onnx::Conv_963)
%onnx::Conv_1005 = Identity(%onnx::Conv_963)
%onnx::Conv_1002 = Identity(%onnx::Conv_963)
%onnx::Conv_999 = Identity(%onnx::Conv_963)
%onnx::Conv_996 = Identity(%onnx::Conv_963)
%onnx::Conv_993 = Identity(%onnx::Conv_963)
%onnx::Conv_990 = Identity(%onnx::Conv_963)
%onnx::Conv_987 = Identity(%onnx::Conv_963)
%onnx::Conv_984 = Identity(%onnx::Conv_963)
%onnx::Conv_981 = Identity(%onnx::Conv_963)
%onnx::Conv_978 = Identity(%onnx::Conv_963)
%onnx::Conv_975 = Identity(%onnx::Conv_963)
%onnx::Conv_972 = Identity(%onnx::Conv_963)
%onnx::Conv_969 = Identity(%onnx::Conv_963)
%onnx::Conv_966 = Identity(%onnx::Conv_963)
%onnx::Conv_960 = Identity(%onnx::Conv_909)
%onnx::Conv_957 = Identity(%onnx::Conv_909)
%onnx::Conv_954 = Identity(%onnx::Conv_909)
%onnx::Conv_951 = Identity(%onnx::Conv_909)
%onnx::Conv_948 = Identity(%onnx::Conv_909)
%onnx::Conv_945 = Identity(%onnx::Conv_909)
%onnx::Conv_942 = Identity(%onnx::Conv_909)
%onnx::Conv_939 = Identity(%onnx::Conv_909)
%onnx::Conv_936 = Identity(%onnx::Conv_909)
%onnx::Conv_933 = Identity(%onnx::Conv_909)
%onnx::Conv_930 = Identity(%onnx::Conv_909)
%onnx::Conv_927 = Identity(%onnx::Conv_909)
%onnx::Conv_924 = Identity(%onnx::Conv_909)
%onnx::Conv_921 = Identity(%onnx::Conv_909)
%onnx::Conv_918 = Identity(%onnx::Conv_909)
%onnx::Conv_915 = Identity(%onnx::Conv_909)
%onnx::Conv_912 = Identity(%onnx::Conv_909)
%onnx::Conv_906 = Identity(%onnx::Conv_852)
%onnx::Conv_903 = Identity(%onnx::Conv_852)
%onnx::Conv_900 = Identity(%onnx::Conv_852)
%onnx::Conv_897 = Identity(%onnx::Conv_852)
%onnx::Conv_894 = Identity(%onnx::Conv_852)
%onnx::Conv_891 = Identity(%onnx::Conv_852)
%onnx::Conv_888 = Identity(%onnx::Conv_852)
%onnx::Conv_885 = Identity(%onnx::Conv_852)
%onnx::Conv_882 = Identity(%onnx::Conv_852)
%onnx::Conv_879 = Identity(%onnx::Conv_852)
%onnx::Conv_876 = Identity(%onnx::Conv_852)
%onnx::Conv_873 = Identity(%onnx::Conv_852)
%onnx::Conv_870 = Identity(%onnx::Conv_852)
%onnx::Conv_867 = Identity(%onnx::Conv_852)
%onnx::Conv_864 = Identity(%onnx::Conv_852)
%onnx::Conv_861 = Identity(%onnx::Conv_852)
%onnx::Conv_858 = Identity(%onnx::Conv_852)
%onnx::Conv_855 = Identity(%onnx::Conv_852)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_851, %onnx::Conv_852)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%849 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %849
}
|
val_accuracy
| 91.856968
| 6,617,835,520
| 22,421,642
|
{'zcp_epe_nas': 131.6223625932707, 'zcp_fisher': 215.4566650390625, 'zcp_flops': 105885368320.0, 'zcp_grad_norm': 236.54721069335938, 'zcp_grasp': -103.48388671875, 'zcp_jacov': -16.0591603502111, 'zcp_l2_norm': 1242.4326171875, 'zcp_nwot': 234.68414914011484, 'zcp_params': 22421642.0, 'zcp_plain': 0.05013451352715401, 'zcp_snip': 1968.967529296875, 'zcp_synflow': 136.1512729392406, 'zcp_zen': 116.94624328613281, 'zcp_val_accuracy': 0.8871194124221801}
| |
NASBench101_100074
|
NASBench101
|
100074
|
3c9327bab3ed37c786e29ccb593e0b30
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_788[FLOAT, 128x3x3x3]
%onnx::Conv_789[FLOAT, 128]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 128x128x1x1]
%onnx::Conv_797[FLOAT, 128x128x3x3]
%onnx::Conv_800[FLOAT, 128x128x3x3]
%onnx::Conv_803[FLOAT, 128x128x1x1]
%onnx::Conv_806[FLOAT, 128x128x1x1]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x3x3]
%onnx::Conv_815[FLOAT, 128x128x3x3]
%onnx::Conv_818[FLOAT, 128x128x1x1]
%onnx::Conv_821[FLOAT, 128x128x1x1]
%onnx::Conv_824[FLOAT, 128x128x1x1]
%onnx::Conv_827[FLOAT, 128x128x3x3]
%onnx::Conv_830[FLOAT, 128x128x3x3]
%onnx::Conv_833[FLOAT, 128x128x1x1]
%onnx::Conv_836[FLOAT, 256x128x1x1]
%onnx::Conv_837[FLOAT, 256]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x256x3x3]
%onnx::Conv_845[FLOAT, 256x256x3x3]
%onnx::Conv_848[FLOAT, 256x256x1x1]
%onnx::Conv_851[FLOAT, 256x256x1x1]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_857[FLOAT, 256x256x3x3]
%onnx::Conv_860[FLOAT, 256x256x3x3]
%onnx::Conv_863[FLOAT, 256x256x1x1]
%onnx::Conv_866[FLOAT, 256x256x1x1]
%onnx::Conv_869[FLOAT, 256x256x1x1]
%onnx::Conv_872[FLOAT, 256x256x3x3]
%onnx::Conv_875[FLOAT, 256x256x3x3]
%onnx::Conv_878[FLOAT, 256x256x1x1]
%onnx::Conv_881[FLOAT, 512x256x1x1]
%onnx::Conv_882[FLOAT, 512]
%onnx::Conv_884[FLOAT, 512x512x1x1]
%onnx::Conv_887[FLOAT, 512x512x3x3]
%onnx::Conv_890[FLOAT, 512x512x3x3]
%onnx::Conv_893[FLOAT, 512x512x1x1]
%onnx::Conv_896[FLOAT, 512x512x1x1]
%onnx::Conv_899[FLOAT, 512x512x1x1]
%onnx::Conv_902[FLOAT, 512x512x3x3]
%onnx::Conv_905[FLOAT, 512x512x3x3]
%onnx::Conv_908[FLOAT, 512x512x1x1]
%onnx::Conv_911[FLOAT, 512x512x1x1]
%onnx::Conv_914[FLOAT, 512x512x1x1]
%onnx::Conv_917[FLOAT, 512x512x3x3]
%onnx::Conv_920[FLOAT, 512x512x3x3]
%onnx::Conv_923[FLOAT, 512x512x1x1]
) {
%onnx::Conv_924 = Identity(%onnx::Conv_882)
%onnx::Conv_921 = Identity(%onnx::Conv_882)
%onnx::Conv_918 = Identity(%onnx::Conv_882)
%onnx::Conv_915 = Identity(%onnx::Conv_882)
%onnx::Conv_912 = Identity(%onnx::Conv_882)
%onnx::Conv_909 = Identity(%onnx::Conv_882)
%onnx::Conv_906 = Identity(%onnx::Conv_882)
%onnx::Conv_903 = Identity(%onnx::Conv_882)
%onnx::Conv_900 = Identity(%onnx::Conv_882)
%onnx::Conv_897 = Identity(%onnx::Conv_882)
%onnx::Conv_894 = Identity(%onnx::Conv_882)
%onnx::Conv_891 = Identity(%onnx::Conv_882)
%onnx::Conv_888 = Identity(%onnx::Conv_882)
%onnx::Conv_885 = Identity(%onnx::Conv_882)
%onnx::Conv_879 = Identity(%onnx::Conv_837)
%onnx::Conv_876 = Identity(%onnx::Conv_837)
%onnx::Conv_873 = Identity(%onnx::Conv_837)
%onnx::Conv_870 = Identity(%onnx::Conv_837)
%onnx::Conv_867 = Identity(%onnx::Conv_837)
%onnx::Conv_864 = Identity(%onnx::Conv_837)
%onnx::Conv_861 = Identity(%onnx::Conv_837)
%onnx::Conv_858 = Identity(%onnx::Conv_837)
%onnx::Conv_855 = Identity(%onnx::Conv_837)
%onnx::Conv_852 = Identity(%onnx::Conv_837)
%onnx::Conv_849 = Identity(%onnx::Conv_837)
%onnx::Conv_846 = Identity(%onnx::Conv_837)
%onnx::Conv_843 = Identity(%onnx::Conv_837)
%onnx::Conv_840 = Identity(%onnx::Conv_837)
%onnx::Conv_834 = Identity(%onnx::Conv_789)
%onnx::Conv_831 = Identity(%onnx::Conv_789)
%onnx::Conv_828 = Identity(%onnx::Conv_789)
%onnx::Conv_825 = Identity(%onnx::Conv_789)
%onnx::Conv_822 = Identity(%onnx::Conv_789)
%onnx::Conv_819 = Identity(%onnx::Conv_789)
%onnx::Conv_816 = Identity(%onnx::Conv_789)
%onnx::Conv_813 = Identity(%onnx::Conv_789)
%onnx::Conv_810 = Identity(%onnx::Conv_789)
%onnx::Conv_807 = Identity(%onnx::Conv_789)
%onnx::Conv_804 = Identity(%onnx::Conv_789)
%onnx::Conv_801 = Identity(%onnx::Conv_789)
%onnx::Conv_798 = Identity(%onnx::Conv_789)
%onnx::Conv_795 = Identity(%onnx::Conv_789)
%onnx::Conv_792 = Identity(%onnx::Conv_789)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_788, %onnx::Conv_789)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_7_output_0 = Add(%/layers.1/Add_6_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_7_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_7_output_0 = Add(%/layers.2/Add_6_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_7_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_7_output_0 = Add(%/layers.3/Add_6_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_7_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_7_output_0 = Add(%/layers.5/Add_6_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_7_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_7_output_0 = Add(%/layers.6/Add_6_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_7_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_7_output_0 = Add(%/layers.7/Add_6_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_7_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_7_output_0 = Add(%/layers.9/Add_6_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_7_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_7_output_0 = Add(%/layers.10/Add_6_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_7_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_7_output_0 = Add(%/layers.11/Add_6_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_7_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%786 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %786
}
|
val_accuracy
| 89.933896
| 6,343,895,040
| 21,547,914
|
{'zcp_epe_nas': 90.73836165980755, 'zcp_fisher': 429.49615478515625, 'zcp_flops': 101502320640.0, 'zcp_grad_norm': 333.21966552734375, 'zcp_grasp': -227.1337890625, 'zcp_jacov': -16.052497817484813, 'zcp_l2_norm': 1047.0498046875, 'zcp_nwot': 231.90455303221523, 'zcp_params': 21547914.0, 'zcp_plain': -0.008386176079511, 'zcp_snip': 2548.267822265625, 'zcp_synflow': 162.04549146860947, 'zcp_zen': 101.15521240234375, 'zcp_val_accuracy': 0.894230782985687}
| |
NASBench101_11714
|
NASBench101
|
11714
|
0707725a46382733787f42f43f34e835
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_752[FLOAT, 128x3x3x3]
%onnx::Conv_753[FLOAT, 128]
%onnx::Conv_755[FLOAT, 128x128x1x1]
%onnx::Conv_758[FLOAT, 128x128x3x3]
%onnx::Conv_761[FLOAT, 128x128x1x1]
%onnx::Conv_764[FLOAT, 128x128x1x1]
%onnx::Conv_767[FLOAT, 128x128x1x1]
%onnx::Conv_770[FLOAT, 128x128x1x1]
%onnx::Conv_773[FLOAT, 128x128x3x3]
%onnx::Conv_776[FLOAT, 128x128x1x1]
%onnx::Conv_779[FLOAT, 128x128x1x1]
%onnx::Conv_782[FLOAT, 128x128x1x1]
%onnx::Conv_785[FLOAT, 128x128x1x1]
%onnx::Conv_788[FLOAT, 128x128x3x3]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 128x128x1x1]
%onnx::Conv_797[FLOAT, 128x128x1x1]
%onnx::Conv_800[FLOAT, 256x128x1x1]
%onnx::Conv_801[FLOAT, 256]
%onnx::Conv_803[FLOAT, 256x256x3x3]
%onnx::Conv_806[FLOAT, 256x256x1x1]
%onnx::Conv_809[FLOAT, 256x128x1x1]
%onnx::Conv_812[FLOAT, 256x128x1x1]
%onnx::Conv_815[FLOAT, 256x256x1x1]
%onnx::Conv_818[FLOAT, 256x256x3x3]
%onnx::Conv_821[FLOAT, 256x256x1x1]
%onnx::Conv_824[FLOAT, 256x256x1x1]
%onnx::Conv_827[FLOAT, 256x256x1x1]
%onnx::Conv_830[FLOAT, 256x256x1x1]
%onnx::Conv_833[FLOAT, 256x256x3x3]
%onnx::Conv_836[FLOAT, 256x256x1x1]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x256x1x1]
%onnx::Conv_845[FLOAT, 512x256x1x1]
%onnx::Conv_846[FLOAT, 512]
%onnx::Conv_848[FLOAT, 512x512x3x3]
%onnx::Conv_851[FLOAT, 512x512x1x1]
%onnx::Conv_854[FLOAT, 512x256x1x1]
%onnx::Conv_857[FLOAT, 512x256x1x1]
%onnx::Conv_860[FLOAT, 512x512x1x1]
%onnx::Conv_863[FLOAT, 512x512x3x3]
%onnx::Conv_866[FLOAT, 512x512x1x1]
%onnx::Conv_869[FLOAT, 512x512x1x1]
%onnx::Conv_872[FLOAT, 512x512x1x1]
%onnx::Conv_875[FLOAT, 512x512x1x1]
%onnx::Conv_878[FLOAT, 512x512x3x3]
%onnx::Conv_881[FLOAT, 512x512x1x1]
%onnx::Conv_884[FLOAT, 512x512x1x1]
%onnx::Conv_887[FLOAT, 512x512x1x1]
) {
%onnx::Conv_888 = Identity(%onnx::Conv_846)
%onnx::Conv_885 = Identity(%onnx::Conv_846)
%onnx::Conv_882 = Identity(%onnx::Conv_846)
%onnx::Conv_879 = Identity(%onnx::Conv_846)
%onnx::Conv_876 = Identity(%onnx::Conv_846)
%onnx::Conv_873 = Identity(%onnx::Conv_846)
%onnx::Conv_870 = Identity(%onnx::Conv_846)
%onnx::Conv_867 = Identity(%onnx::Conv_846)
%onnx::Conv_864 = Identity(%onnx::Conv_846)
%onnx::Conv_861 = Identity(%onnx::Conv_846)
%onnx::Conv_858 = Identity(%onnx::Conv_846)
%onnx::Conv_855 = Identity(%onnx::Conv_846)
%onnx::Conv_852 = Identity(%onnx::Conv_846)
%onnx::Conv_849 = Identity(%onnx::Conv_846)
%onnx::Conv_843 = Identity(%onnx::Conv_801)
%onnx::Conv_840 = Identity(%onnx::Conv_801)
%onnx::Conv_837 = Identity(%onnx::Conv_801)
%onnx::Conv_834 = Identity(%onnx::Conv_801)
%onnx::Conv_831 = Identity(%onnx::Conv_801)
%onnx::Conv_828 = Identity(%onnx::Conv_801)
%onnx::Conv_825 = Identity(%onnx::Conv_801)
%onnx::Conv_822 = Identity(%onnx::Conv_801)
%onnx::Conv_819 = Identity(%onnx::Conv_801)
%onnx::Conv_816 = Identity(%onnx::Conv_801)
%onnx::Conv_813 = Identity(%onnx::Conv_801)
%onnx::Conv_810 = Identity(%onnx::Conv_801)
%onnx::Conv_807 = Identity(%onnx::Conv_801)
%onnx::Conv_804 = Identity(%onnx::Conv_801)
%onnx::Conv_798 = Identity(%onnx::Conv_753)
%onnx::Conv_795 = Identity(%onnx::Conv_753)
%onnx::Conv_792 = Identity(%onnx::Conv_753)
%onnx::Conv_789 = Identity(%onnx::Conv_753)
%onnx::Conv_786 = Identity(%onnx::Conv_753)
%onnx::Conv_783 = Identity(%onnx::Conv_753)
%onnx::Conv_780 = Identity(%onnx::Conv_753)
%onnx::Conv_777 = Identity(%onnx::Conv_753)
%onnx::Conv_774 = Identity(%onnx::Conv_753)
%onnx::Conv_771 = Identity(%onnx::Conv_753)
%onnx::Conv_768 = Identity(%onnx::Conv_753)
%onnx::Conv_765 = Identity(%onnx::Conv_753)
%onnx::Conv_762 = Identity(%onnx::Conv_753)
%onnx::Conv_759 = Identity(%onnx::Conv_753)
%onnx::Conv_756 = Identity(%onnx::Conv_753)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_752, %onnx::Conv_753)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.5/maxpool/MaxPool_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_4_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.5/maxpool/MaxPool_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_4_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.5/maxpool/MaxPool_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_4_output_0)
%750 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %750
}
|
val_accuracy
| 90.374601
| 3,860,867,072
| 12,962,698
|
{'zcp_epe_nas': 71.98214662760294, 'zcp_fisher': 13.213799476623535, 'zcp_flops': 61773873152.0, 'zcp_grad_norm': 71.66472625732422, 'zcp_grasp': 6.594512939453125, 'zcp_jacov': -16.053746135312913, 'zcp_l2_norm': 1014.2362060546875, 'zcp_nwot': 232.03261623549747, 'zcp_params': 12962698.0, 'zcp_plain': 0.026649501174688003, 'zcp_snip': 646.3283081054688, 'zcp_synflow': 93.79800772374549, 'zcp_zen': 100.67201232910156, 'zcp_val_accuracy': 0.9160656929016111}
| |
NASBench101_123447
|
NASBench101
|
123447
|
4a981952c7f06b5dd25a103614d9704c
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_686[FLOAT, 128x3x3x3]
%onnx::Conv_687[FLOAT, 128]
%onnx::Conv_689[FLOAT, 43x128x1x1]
%onnx::Conv_690[FLOAT, 43]
%onnx::Conv_692[FLOAT, 43x43x3x3]
%onnx::Conv_695[FLOAT, 43x43x1x1]
%onnx::Conv_698[FLOAT, 43x128x1x1]
%onnx::Conv_701[FLOAT, 43x43x3x3]
%onnx::Conv_704[FLOAT, 43x43x1x1]
%onnx::Conv_707[FLOAT, 43x128x1x1]
%onnx::Conv_710[FLOAT, 43x43x3x3]
%onnx::Conv_713[FLOAT, 43x43x1x1]
%onnx::Conv_716[FLOAT, 86x128x1x1]
%onnx::Conv_717[FLOAT, 86]
%onnx::Conv_719[FLOAT, 86x86x3x3]
%onnx::Conv_722[FLOAT, 85x85x1x1]
%onnx::Conv_723[FLOAT, 85]
%onnx::Conv_725[FLOAT, 86x256x1x1]
%onnx::Conv_728[FLOAT, 86x86x3x3]
%onnx::Conv_731[FLOAT, 85x85x1x1]
%onnx::Conv_734[FLOAT, 86x256x1x1]
%onnx::Conv_737[FLOAT, 86x86x3x3]
%onnx::Conv_740[FLOAT, 85x85x1x1]
%onnx::Conv_743[FLOAT, 171x256x1x1]
%onnx::Conv_744[FLOAT, 171]
%onnx::Conv_746[FLOAT, 171x171x3x3]
%onnx::Conv_749[FLOAT, 171x171x1x1]
%onnx::Conv_752[FLOAT, 171x512x1x1]
%onnx::Conv_755[FLOAT, 171x171x3x3]
%onnx::Conv_758[FLOAT, 171x171x1x1]
%onnx::Conv_761[FLOAT, 171x512x1x1]
%onnx::Conv_764[FLOAT, 171x171x3x3]
%onnx::Conv_767[FLOAT, 171x171x1x1]
) {
%onnx::Conv_768 = Identity(%onnx::Conv_744)
%onnx::Conv_765 = Identity(%onnx::Conv_744)
%onnx::Conv_762 = Identity(%onnx::Conv_744)
%onnx::Conv_759 = Identity(%onnx::Conv_744)
%onnx::Conv_756 = Identity(%onnx::Conv_744)
%onnx::Conv_753 = Identity(%onnx::Conv_744)
%onnx::Conv_750 = Identity(%onnx::Conv_744)
%onnx::Conv_747 = Identity(%onnx::Conv_744)
%onnx::Conv_741 = Identity(%onnx::Conv_723)
%onnx::Conv_738 = Identity(%onnx::Conv_717)
%onnx::Conv_735 = Identity(%onnx::Conv_717)
%onnx::Conv_732 = Identity(%onnx::Conv_723)
%onnx::Conv_729 = Identity(%onnx::Conv_717)
%onnx::Conv_726 = Identity(%onnx::Conv_717)
%onnx::Conv_720 = Identity(%onnx::Conv_717)
%onnx::Conv_714 = Identity(%onnx::Conv_690)
%onnx::Conv_711 = Identity(%onnx::Conv_690)
%onnx::Conv_708 = Identity(%onnx::Conv_690)
%onnx::Conv_705 = Identity(%onnx::Conv_690)
%onnx::Conv_702 = Identity(%onnx::Conv_690)
%onnx::Conv_699 = Identity(%onnx::Conv_690)
%onnx::Conv_696 = Identity(%onnx::Conv_690)
%onnx::Conv_693 = Identity(%onnx::Conv_690)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_686, %onnx::Conv_687)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_2_output_0, %/layers.1/Constant_5_output_0)
%/layers.1/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_6_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_1_output_0 = Slice(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_8_output_0, %/layers.1/Constant_9_output_0, %/layers.1/Constant_7_output_0, %/layers.1/Constant_10_output_0)
%/layers.1/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/Slice_1_output_0, %/layers.1/Constant_11_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_2_output_0, %/layers.2/Constant_5_output_0)
%/layers.2/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_6_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_1_output_0 = Slice(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_8_output_0, %/layers.2/Constant_9_output_0, %/layers.2/Constant_7_output_0, %/layers.2/Constant_10_output_0)
%/layers.2/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/Slice_1_output_0, %/layers.2/Constant_11_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_2_output_0, %/layers.3/Constant_5_output_0)
%/layers.3/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_6_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_1_output_0 = Slice(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_8_output_0, %/layers.3/Constant_9_output_0, %/layers.3/Constant_7_output_0, %/layers.3/Constant_10_output_0)
%/layers.3/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/Slice_1_output_0, %/layers.3/Constant_11_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_4_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Slice_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_1_output_0 = Slice(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_7_output_0, %/layers.5/Constant_8_output_0, %/layers.5/Constant_6_output_0, %/layers.5/Constant_9_output_0)
%/layers.5/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/Slice_1_output_0, %/layers.5/Constant_10_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_12_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_13_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_14_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_2_output_0 = Slice(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_12_output_0, %/layers.5/Constant_13_output_0, %/layers.5/Constant_11_output_0, %/layers.5/Constant_14_output_0)
%/layers.5/Constant_15_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/Slice_2_output_0, %/layers.5/Constant_15_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_4_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Slice_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_1_output_0 = Slice(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_7_output_0, %/layers.6/Constant_8_output_0, %/layers.6/Constant_6_output_0, %/layers.6/Constant_9_output_0)
%/layers.6/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/Slice_1_output_0, %/layers.6/Constant_10_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_12_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_13_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_14_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_2_output_0 = Slice(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_12_output_0, %/layers.6/Constant_13_output_0, %/layers.6/Constant_11_output_0, %/layers.6/Constant_14_output_0)
%/layers.6/Constant_15_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/Slice_2_output_0, %/layers.6/Constant_15_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_4_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Slice_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_1_output_0 = Slice(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_7_output_0, %/layers.7/Constant_8_output_0, %/layers.7/Constant_6_output_0, %/layers.7/Constant_9_output_0)
%/layers.7/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/Slice_1_output_0, %/layers.7/Constant_10_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_12_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_13_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_14_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_2_output_0 = Slice(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_12_output_0, %/layers.7/Constant_13_output_0, %/layers.7/Constant_11_output_0, %/layers.7/Constant_14_output_0)
%/layers.7/Constant_15_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/Slice_2_output_0, %/layers.7/Constant_15_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_2_output_0, %/layers.9/Constant_5_output_0)
%/layers.9/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_6_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_1_output_0 = Slice(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_8_output_0, %/layers.9/Constant_9_output_0, %/layers.9/Constant_7_output_0, %/layers.9/Constant_10_output_0)
%/layers.9/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/Slice_1_output_0, %/layers.9/Constant_11_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_2_output_0, %/layers.10/Constant_5_output_0)
%/layers.10/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_6_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_1_output_0 = Slice(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_8_output_0, %/layers.10/Constant_9_output_0, %/layers.10/Constant_7_output_0, %/layers.10/Constant_10_output_0)
%/layers.10/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/Slice_1_output_0, %/layers.10/Constant_11_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_2_output_0, %/layers.11/Constant_5_output_0)
%/layers.11/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_6_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_1_output_0 = Slice(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_8_output_0, %/layers.11/Constant_9_output_0, %/layers.11/Constant_7_output_0, %/layers.11/Constant_10_output_0)
%/layers.11/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/Slice_1_output_0, %/layers.11/Constant_11_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%684 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %684
}
|
val_accuracy
| 87.099361
| 442,915,584
| 1,458,735
|
{'zcp_epe_nas': 94.9354215717242, 'zcp_fisher': 49.07564163208008, 'zcp_flops': 7086649344.0, 'zcp_grad_norm': 101.99227905273438, 'zcp_grasp': -81.5987548828125, 'zcp_jacov': -16.04318904957078, 'zcp_l2_norm': 444.076904296875, 'zcp_nwot': 208.79902905710924, 'zcp_params': 1458735.0, 'zcp_plain': 0.15500164031982402, 'zcp_snip': 521.0479736328125, 'zcp_synflow': 80.98167969181303, 'zcp_zen': 51.65205383300781, 'zcp_val_accuracy': 0.933293282985687}
| |
NASBench101_227169
|
NASBench101
|
227169
|
899439e5a476f18f3aaf0ba3b5a6fe99
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_869[FLOAT, 128x3x3x3]
%onnx::Conv_870[FLOAT, 128]
%onnx::Conv_872[FLOAT, 43x128x1x1]
%onnx::Conv_873[FLOAT, 43]
%onnx::Conv_875[FLOAT, 43x43x1x1]
%onnx::Conv_878[FLOAT, 43x43x1x1]
%onnx::Conv_881[FLOAT, 43x43x3x3]
%onnx::Conv_884[FLOAT, 42x42x1x1]
%onnx::Conv_885[FLOAT, 42]
%onnx::Conv_887[FLOAT, 43x128x1x1]
%onnx::Conv_890[FLOAT, 43x43x1x1]
%onnx::Conv_893[FLOAT, 43x43x1x1]
%onnx::Conv_896[FLOAT, 43x43x3x3]
%onnx::Conv_899[FLOAT, 42x42x1x1]
%onnx::Conv_902[FLOAT, 43x128x1x1]
%onnx::Conv_905[FLOAT, 43x43x1x1]
%onnx::Conv_908[FLOAT, 43x43x1x1]
%onnx::Conv_911[FLOAT, 43x43x3x3]
%onnx::Conv_914[FLOAT, 42x42x1x1]
%onnx::Conv_917[FLOAT, 86x128x1x1]
%onnx::Conv_918[FLOAT, 86]
%onnx::Conv_920[FLOAT, 86x86x1x1]
%onnx::Conv_923[FLOAT, 86x86x1x1]
%onnx::Conv_926[FLOAT, 85x85x3x3]
%onnx::Conv_927[FLOAT, 85]
%onnx::Conv_929[FLOAT, 85x85x1x1]
%onnx::Conv_932[FLOAT, 86x256x1x1]
%onnx::Conv_935[FLOAT, 86x86x1x1]
%onnx::Conv_938[FLOAT, 86x86x1x1]
%onnx::Conv_941[FLOAT, 85x85x3x3]
%onnx::Conv_944[FLOAT, 85x85x1x1]
%onnx::Conv_947[FLOAT, 86x256x1x1]
%onnx::Conv_950[FLOAT, 86x86x1x1]
%onnx::Conv_953[FLOAT, 86x86x1x1]
%onnx::Conv_956[FLOAT, 85x85x3x3]
%onnx::Conv_959[FLOAT, 85x85x1x1]
%onnx::Conv_962[FLOAT, 171x256x1x1]
%onnx::Conv_963[FLOAT, 171]
%onnx::Conv_965[FLOAT, 171x171x1x1]
%onnx::Conv_968[FLOAT, 171x171x1x1]
%onnx::Conv_971[FLOAT, 171x171x3x3]
%onnx::Conv_974[FLOAT, 170x170x1x1]
%onnx::Conv_975[FLOAT, 170]
%onnx::Conv_977[FLOAT, 171x512x1x1]
%onnx::Conv_980[FLOAT, 171x171x1x1]
%onnx::Conv_983[FLOAT, 171x171x1x1]
%onnx::Conv_986[FLOAT, 171x171x3x3]
%onnx::Conv_989[FLOAT, 170x170x1x1]
%onnx::Conv_992[FLOAT, 171x512x1x1]
%onnx::Conv_995[FLOAT, 171x171x1x1]
%onnx::Conv_998[FLOAT, 171x171x1x1]
%onnx::Conv_1001[FLOAT, 171x171x3x3]
%onnx::Conv_1004[FLOAT, 170x170x1x1]
) {
%onnx::Conv_1005 = Identity(%onnx::Conv_975)
%onnx::Conv_1002 = Identity(%onnx::Conv_963)
%onnx::Conv_999 = Identity(%onnx::Conv_963)
%onnx::Conv_996 = Identity(%onnx::Conv_963)
%onnx::Conv_993 = Identity(%onnx::Conv_963)
%onnx::Conv_990 = Identity(%onnx::Conv_975)
%onnx::Conv_987 = Identity(%onnx::Conv_963)
%onnx::Conv_984 = Identity(%onnx::Conv_963)
%onnx::Conv_981 = Identity(%onnx::Conv_963)
%onnx::Conv_978 = Identity(%onnx::Conv_963)
%onnx::Conv_972 = Identity(%onnx::Conv_963)
%onnx::Conv_969 = Identity(%onnx::Conv_963)
%onnx::Conv_966 = Identity(%onnx::Conv_963)
%onnx::Conv_960 = Identity(%onnx::Conv_927)
%onnx::Conv_957 = Identity(%onnx::Conv_927)
%onnx::Conv_954 = Identity(%onnx::Conv_918)
%onnx::Conv_951 = Identity(%onnx::Conv_918)
%onnx::Conv_948 = Identity(%onnx::Conv_918)
%onnx::Conv_945 = Identity(%onnx::Conv_927)
%onnx::Conv_942 = Identity(%onnx::Conv_927)
%onnx::Conv_939 = Identity(%onnx::Conv_918)
%onnx::Conv_936 = Identity(%onnx::Conv_918)
%onnx::Conv_933 = Identity(%onnx::Conv_918)
%onnx::Conv_930 = Identity(%onnx::Conv_927)
%onnx::Conv_924 = Identity(%onnx::Conv_918)
%onnx::Conv_921 = Identity(%onnx::Conv_918)
%onnx::Conv_915 = Identity(%onnx::Conv_885)
%onnx::Conv_912 = Identity(%onnx::Conv_873)
%onnx::Conv_909 = Identity(%onnx::Conv_873)
%onnx::Conv_906 = Identity(%onnx::Conv_873)
%onnx::Conv_903 = Identity(%onnx::Conv_873)
%onnx::Conv_900 = Identity(%onnx::Conv_885)
%onnx::Conv_897 = Identity(%onnx::Conv_873)
%onnx::Conv_894 = Identity(%onnx::Conv_873)
%onnx::Conv_891 = Identity(%onnx::Conv_873)
%onnx::Conv_888 = Identity(%onnx::Conv_873)
%onnx::Conv_882 = Identity(%onnx::Conv_873)
%onnx::Conv_879 = Identity(%onnx::Conv_873)
%onnx::Conv_876 = Identity(%onnx::Conv_873)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_869, %onnx::Conv_870)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_6_output_0)
%/layers.1/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_7_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_1_output_0 = Slice(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_9_output_0, %/layers.1/Constant_10_output_0, %/layers.1/Constant_8_output_0, %/layers.1/Constant_11_output_0)
%/layers.1/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/Slice_1_output_0, %/layers.1/Constant_12_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_6_output_0)
%/layers.2/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_7_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_1_output_0 = Slice(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_9_output_0, %/layers.2/Constant_10_output_0, %/layers.2/Constant_8_output_0, %/layers.2/Constant_11_output_0)
%/layers.2/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/Slice_1_output_0, %/layers.2/Constant_12_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_6_output_0)
%/layers.3/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_7_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_1_output_0 = Slice(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_9_output_0, %/layers.3/Constant_10_output_0, %/layers.3/Constant_8_output_0, %/layers.3/Constant_11_output_0)
%/layers.3/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/Slice_1_output_0, %/layers.3/Constant_12_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_4_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_7_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_1_output_0 = Slice(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_9_output_0, %/layers.5/Constant_10_output_0, %/layers.5/Constant_8_output_0, %/layers.5/Constant_11_output_0)
%/layers.5/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/Slice_1_output_0, %/layers.5/Constant_12_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_4_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_7_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_1_output_0 = Slice(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_9_output_0, %/layers.6/Constant_10_output_0, %/layers.6/Constant_8_output_0, %/layers.6/Constant_11_output_0)
%/layers.6/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/Slice_1_output_0, %/layers.6/Constant_12_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_4_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_7_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_1_output_0 = Slice(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_9_output_0, %/layers.7/Constant_10_output_0, %/layers.7/Constant_8_output_0, %/layers.7/Constant_11_output_0)
%/layers.7/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/Slice_1_output_0, %/layers.7/Constant_12_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_6_output_0)
%/layers.9/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_7_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_1_output_0 = Slice(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_9_output_0, %/layers.9/Constant_10_output_0, %/layers.9/Constant_8_output_0, %/layers.9/Constant_11_output_0)
%/layers.9/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/Slice_1_output_0, %/layers.9/Constant_12_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_6_output_0)
%/layers.10/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_7_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_1_output_0 = Slice(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_9_output_0, %/layers.10/Constant_10_output_0, %/layers.10/Constant_8_output_0, %/layers.10/Constant_11_output_0)
%/layers.10/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/Slice_1_output_0, %/layers.10/Constant_12_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_6_output_0)
%/layers.11/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_7_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_1_output_0 = Slice(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_9_output_0, %/layers.11/Constant_10_output_0, %/layers.11/Constant_8_output_0, %/layers.11/Constant_11_output_0)
%/layers.11/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/Slice_1_output_0, %/layers.11/Constant_12_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%867 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %867
}
|
val_accuracy
| 87.570113
| 511,459,968
| 1,687,338
|
{'zcp_epe_nas': 226.56403774499023, 'zcp_fisher': 1710.76513671875, 'zcp_flops': 8183359488.0, 'zcp_grad_norm': 730.631591796875, 'zcp_grasp': -9874.609375, 'zcp_jacov': -16.042877718617916, 'zcp_l2_norm': 688.6099853515625, 'zcp_nwot': 216.16087659817606, 'zcp_params': 1687338.0, 'zcp_plain': 0.09376641362905501, 'zcp_snip': 2987.62548828125, 'zcp_synflow': 122.1666128039388, 'zcp_zen': 66.09222412109375, 'zcp_val_accuracy': 0.9258813858032221}
| |
NASBench101_140108
|
NASBench101
|
140108
|
54ba2870843f089cbb856275b88a2b45
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_968[FLOAT, 128x3x3x3]
%onnx::Conv_969[FLOAT, 128]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%onnx::Conv_974[FLOAT, 128x128x3x3]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 128x128x3x3]
%onnx::Conv_983[FLOAT, 128x128x3x3]
%onnx::Conv_986[FLOAT, 128x128x3x3]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x3x3]
%onnx::Conv_998[FLOAT, 128x128x1x1]
%onnx::Conv_1001[FLOAT, 128x128x3x3]
%onnx::Conv_1004[FLOAT, 128x128x3x3]
%onnx::Conv_1007[FLOAT, 128x128x3x3]
%onnx::Conv_1010[FLOAT, 128x128x1x1]
%onnx::Conv_1013[FLOAT, 128x128x1x1]
%onnx::Conv_1016[FLOAT, 128x128x3x3]
%onnx::Conv_1019[FLOAT, 128x128x1x1]
%onnx::Conv_1022[FLOAT, 128x128x3x3]
%onnx::Conv_1025[FLOAT, 128x128x3x3]
%onnx::Conv_1028[FLOAT, 128x128x3x3]
%onnx::Conv_1031[FLOAT, 128x128x1x1]
%onnx::Conv_1034[FLOAT, 256x128x1x1]
%onnx::Conv_1035[FLOAT, 256]
%onnx::Conv_1037[FLOAT, 256x256x3x3]
%onnx::Conv_1040[FLOAT, 256x128x1x1]
%onnx::Conv_1043[FLOAT, 256x256x3x3]
%onnx::Conv_1046[FLOAT, 256x256x3x3]
%onnx::Conv_1049[FLOAT, 256x256x3x3]
%onnx::Conv_1052[FLOAT, 256x128x1x1]
%onnx::Conv_1055[FLOAT, 256x256x1x1]
%onnx::Conv_1058[FLOAT, 256x256x3x3]
%onnx::Conv_1061[FLOAT, 256x256x1x1]
%onnx::Conv_1064[FLOAT, 256x256x3x3]
%onnx::Conv_1067[FLOAT, 256x256x3x3]
%onnx::Conv_1070[FLOAT, 256x256x3x3]
%onnx::Conv_1073[FLOAT, 256x256x1x1]
%onnx::Conv_1076[FLOAT, 256x256x1x1]
%onnx::Conv_1079[FLOAT, 256x256x3x3]
%onnx::Conv_1082[FLOAT, 256x256x1x1]
%onnx::Conv_1085[FLOAT, 256x256x3x3]
%onnx::Conv_1088[FLOAT, 256x256x3x3]
%onnx::Conv_1091[FLOAT, 256x256x3x3]
%onnx::Conv_1094[FLOAT, 256x256x1x1]
%onnx::Conv_1097[FLOAT, 512x256x1x1]
%onnx::Conv_1098[FLOAT, 512]
%onnx::Conv_1100[FLOAT, 512x512x3x3]
%onnx::Conv_1103[FLOAT, 512x256x1x1]
%onnx::Conv_1106[FLOAT, 512x512x3x3]
%onnx::Conv_1109[FLOAT, 512x512x3x3]
%onnx::Conv_1112[FLOAT, 512x512x3x3]
%onnx::Conv_1115[FLOAT, 512x256x1x1]
%onnx::Conv_1118[FLOAT, 512x512x1x1]
%onnx::Conv_1121[FLOAT, 512x512x3x3]
%onnx::Conv_1124[FLOAT, 512x512x1x1]
%onnx::Conv_1127[FLOAT, 512x512x3x3]
%onnx::Conv_1130[FLOAT, 512x512x3x3]
%onnx::Conv_1133[FLOAT, 512x512x3x3]
%onnx::Conv_1136[FLOAT, 512x512x1x1]
%onnx::Conv_1139[FLOAT, 512x512x1x1]
%onnx::Conv_1142[FLOAT, 512x512x3x3]
%onnx::Conv_1145[FLOAT, 512x512x1x1]
%onnx::Conv_1148[FLOAT, 512x512x3x3]
%onnx::Conv_1151[FLOAT, 512x512x3x3]
%onnx::Conv_1154[FLOAT, 512x512x3x3]
%onnx::Conv_1157[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1158 = Identity(%onnx::Conv_1098)
%onnx::Conv_1155 = Identity(%onnx::Conv_1098)
%onnx::Conv_1152 = Identity(%onnx::Conv_1098)
%onnx::Conv_1149 = Identity(%onnx::Conv_1098)
%onnx::Conv_1146 = Identity(%onnx::Conv_1098)
%onnx::Conv_1143 = Identity(%onnx::Conv_1098)
%onnx::Conv_1140 = Identity(%onnx::Conv_1098)
%onnx::Conv_1137 = Identity(%onnx::Conv_1098)
%onnx::Conv_1134 = Identity(%onnx::Conv_1098)
%onnx::Conv_1131 = Identity(%onnx::Conv_1098)
%onnx::Conv_1128 = Identity(%onnx::Conv_1098)
%onnx::Conv_1125 = Identity(%onnx::Conv_1098)
%onnx::Conv_1122 = Identity(%onnx::Conv_1098)
%onnx::Conv_1119 = Identity(%onnx::Conv_1098)
%onnx::Conv_1116 = Identity(%onnx::Conv_1098)
%onnx::Conv_1113 = Identity(%onnx::Conv_1098)
%onnx::Conv_1110 = Identity(%onnx::Conv_1098)
%onnx::Conv_1107 = Identity(%onnx::Conv_1098)
%onnx::Conv_1104 = Identity(%onnx::Conv_1098)
%onnx::Conv_1101 = Identity(%onnx::Conv_1098)
%onnx::Conv_1095 = Identity(%onnx::Conv_1035)
%onnx::Conv_1092 = Identity(%onnx::Conv_1035)
%onnx::Conv_1089 = Identity(%onnx::Conv_1035)
%onnx::Conv_1086 = Identity(%onnx::Conv_1035)
%onnx::Conv_1083 = Identity(%onnx::Conv_1035)
%onnx::Conv_1080 = Identity(%onnx::Conv_1035)
%onnx::Conv_1077 = Identity(%onnx::Conv_1035)
%onnx::Conv_1074 = Identity(%onnx::Conv_1035)
%onnx::Conv_1071 = Identity(%onnx::Conv_1035)
%onnx::Conv_1068 = Identity(%onnx::Conv_1035)
%onnx::Conv_1065 = Identity(%onnx::Conv_1035)
%onnx::Conv_1062 = Identity(%onnx::Conv_1035)
%onnx::Conv_1059 = Identity(%onnx::Conv_1035)
%onnx::Conv_1056 = Identity(%onnx::Conv_1035)
%onnx::Conv_1053 = Identity(%onnx::Conv_1035)
%onnx::Conv_1050 = Identity(%onnx::Conv_1035)
%onnx::Conv_1047 = Identity(%onnx::Conv_1035)
%onnx::Conv_1044 = Identity(%onnx::Conv_1035)
%onnx::Conv_1041 = Identity(%onnx::Conv_1035)
%onnx::Conv_1038 = Identity(%onnx::Conv_1035)
%onnx::Conv_1032 = Identity(%onnx::Conv_969)
%onnx::Conv_1029 = Identity(%onnx::Conv_969)
%onnx::Conv_1026 = Identity(%onnx::Conv_969)
%onnx::Conv_1023 = Identity(%onnx::Conv_969)
%onnx::Conv_1020 = Identity(%onnx::Conv_969)
%onnx::Conv_1017 = Identity(%onnx::Conv_969)
%onnx::Conv_1014 = Identity(%onnx::Conv_969)
%onnx::Conv_1011 = Identity(%onnx::Conv_969)
%onnx::Conv_1008 = Identity(%onnx::Conv_969)
%onnx::Conv_1005 = Identity(%onnx::Conv_969)
%onnx::Conv_1002 = Identity(%onnx::Conv_969)
%onnx::Conv_999 = Identity(%onnx::Conv_969)
%onnx::Conv_996 = Identity(%onnx::Conv_969)
%onnx::Conv_993 = Identity(%onnx::Conv_969)
%onnx::Conv_990 = Identity(%onnx::Conv_969)
%onnx::Conv_987 = Identity(%onnx::Conv_969)
%onnx::Conv_984 = Identity(%onnx::Conv_969)
%onnx::Conv_981 = Identity(%onnx::Conv_969)
%onnx::Conv_978 = Identity(%onnx::Conv_969)
%onnx::Conv_975 = Identity(%onnx::Conv_969)
%onnx::Conv_972 = Identity(%onnx::Conv_969)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_968, %onnx::Conv_969)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_6_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_6_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_6_output_0)
%966 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %966
}
|
val_accuracy
| 94.210738
| 11,723,614,208
| 39,810,442
|
{'zcp_epe_nas': 84.12434461605578, 'zcp_fisher': 297.7401123046875, 'zcp_flops': 187577827328.0, 'zcp_grad_norm': 292.6947326660156, 'zcp_grasp': -67.9990234375, 'zcp_jacov': -16.061527216199785, 'zcp_l2_norm': 1438.4031982421875, 'zcp_nwot': 236.95854223862946, 'zcp_params': 39810442.0, 'zcp_plain': 0.002568469382822, 'zcp_snip': 2536.870849609375, 'zcp_synflow': 175.5906683359558, 'zcp_zen': 149.86376953125, 'zcp_val_accuracy': 0.912660241127014}
| |
NASBench101_32446
|
NASBench101
|
32446
|
13a14c3fb59be997b4838508e0e4d8cc
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_761[FLOAT, 128x3x3x3]
%onnx::Conv_762[FLOAT, 128]
%onnx::Conv_764[FLOAT, 128x128x1x1]
%onnx::Conv_767[FLOAT, 128x128x3x3]
%onnx::Conv_770[FLOAT, 128x128x1x1]
%onnx::Conv_773[FLOAT, 128x128x1x1]
%onnx::Conv_776[FLOAT, 128x128x3x3]
%onnx::Conv_779[FLOAT, 128x128x1x1]
%onnx::Conv_782[FLOAT, 128x128x3x3]
%onnx::Conv_785[FLOAT, 128x128x1x1]
%onnx::Conv_788[FLOAT, 128x128x1x1]
%onnx::Conv_791[FLOAT, 128x128x3x3]
%onnx::Conv_794[FLOAT, 128x128x1x1]
%onnx::Conv_797[FLOAT, 128x128x3x3]
%onnx::Conv_800[FLOAT, 128x128x1x1]
%onnx::Conv_803[FLOAT, 128x128x1x1]
%onnx::Conv_806[FLOAT, 128x128x3x3]
%onnx::Conv_809[FLOAT, 256x128x1x1]
%onnx::Conv_810[FLOAT, 256]
%onnx::Conv_812[FLOAT, 256x256x3x3]
%onnx::Conv_815[FLOAT, 256x128x1x1]
%onnx::Conv_818[FLOAT, 256x128x1x1]
%onnx::Conv_821[FLOAT, 256x256x3x3]
%onnx::Conv_824[FLOAT, 256x256x1x1]
%onnx::Conv_827[FLOAT, 256x256x3x3]
%onnx::Conv_830[FLOAT, 256x256x1x1]
%onnx::Conv_833[FLOAT, 256x256x1x1]
%onnx::Conv_836[FLOAT, 256x256x3x3]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x256x3x3]
%onnx::Conv_845[FLOAT, 256x256x1x1]
%onnx::Conv_848[FLOAT, 256x256x1x1]
%onnx::Conv_851[FLOAT, 256x256x3x3]
%onnx::Conv_854[FLOAT, 512x256x1x1]
%onnx::Conv_855[FLOAT, 512]
%onnx::Conv_857[FLOAT, 512x512x3x3]
%onnx::Conv_860[FLOAT, 512x256x1x1]
%onnx::Conv_863[FLOAT, 512x256x1x1]
%onnx::Conv_866[FLOAT, 512x512x3x3]
%onnx::Conv_869[FLOAT, 512x512x1x1]
%onnx::Conv_872[FLOAT, 512x512x3x3]
%onnx::Conv_875[FLOAT, 512x512x1x1]
%onnx::Conv_878[FLOAT, 512x512x1x1]
%onnx::Conv_881[FLOAT, 512x512x3x3]
%onnx::Conv_884[FLOAT, 512x512x1x1]
%onnx::Conv_887[FLOAT, 512x512x3x3]
%onnx::Conv_890[FLOAT, 512x512x1x1]
%onnx::Conv_893[FLOAT, 512x512x1x1]
%onnx::Conv_896[FLOAT, 512x512x3x3]
) {
%onnx::Conv_897 = Identity(%onnx::Conv_855)
%onnx::Conv_894 = Identity(%onnx::Conv_855)
%onnx::Conv_891 = Identity(%onnx::Conv_855)
%onnx::Conv_888 = Identity(%onnx::Conv_855)
%onnx::Conv_885 = Identity(%onnx::Conv_855)
%onnx::Conv_882 = Identity(%onnx::Conv_855)
%onnx::Conv_879 = Identity(%onnx::Conv_855)
%onnx::Conv_876 = Identity(%onnx::Conv_855)
%onnx::Conv_873 = Identity(%onnx::Conv_855)
%onnx::Conv_870 = Identity(%onnx::Conv_855)
%onnx::Conv_867 = Identity(%onnx::Conv_855)
%onnx::Conv_864 = Identity(%onnx::Conv_855)
%onnx::Conv_861 = Identity(%onnx::Conv_855)
%onnx::Conv_858 = Identity(%onnx::Conv_855)
%onnx::Conv_852 = Identity(%onnx::Conv_810)
%onnx::Conv_849 = Identity(%onnx::Conv_810)
%onnx::Conv_846 = Identity(%onnx::Conv_810)
%onnx::Conv_843 = Identity(%onnx::Conv_810)
%onnx::Conv_840 = Identity(%onnx::Conv_810)
%onnx::Conv_837 = Identity(%onnx::Conv_810)
%onnx::Conv_834 = Identity(%onnx::Conv_810)
%onnx::Conv_831 = Identity(%onnx::Conv_810)
%onnx::Conv_828 = Identity(%onnx::Conv_810)
%onnx::Conv_825 = Identity(%onnx::Conv_810)
%onnx::Conv_822 = Identity(%onnx::Conv_810)
%onnx::Conv_819 = Identity(%onnx::Conv_810)
%onnx::Conv_816 = Identity(%onnx::Conv_810)
%onnx::Conv_813 = Identity(%onnx::Conv_810)
%onnx::Conv_807 = Identity(%onnx::Conv_762)
%onnx::Conv_804 = Identity(%onnx::Conv_762)
%onnx::Conv_801 = Identity(%onnx::Conv_762)
%onnx::Conv_798 = Identity(%onnx::Conv_762)
%onnx::Conv_795 = Identity(%onnx::Conv_762)
%onnx::Conv_792 = Identity(%onnx::Conv_762)
%onnx::Conv_789 = Identity(%onnx::Conv_762)
%onnx::Conv_786 = Identity(%onnx::Conv_762)
%onnx::Conv_783 = Identity(%onnx::Conv_762)
%onnx::Conv_780 = Identity(%onnx::Conv_762)
%onnx::Conv_777 = Identity(%onnx::Conv_762)
%onnx::Conv_774 = Identity(%onnx::Conv_762)
%onnx::Conv_771 = Identity(%onnx::Conv_762)
%onnx::Conv_768 = Identity(%onnx::Conv_762)
%onnx::Conv_765 = Identity(%onnx::Conv_762)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_761, %onnx::Conv_762)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%759 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %759
}
|
val_accuracy
| 90.014023
| 6,276,786,176
| 21,220,234
|
{'zcp_epe_nas': 94.97439083641483, 'zcp_fisher': 217.64341735839844, 'zcp_flops': 100428578816.0, 'zcp_grad_norm': 232.60317993164062, 'zcp_grasp': -76.168701171875, 'zcp_jacov': -16.049403082342245, 'zcp_l2_norm': 1013.9804077148438, 'zcp_nwot': 232.05215127914573, 'zcp_params': 21220234.0, 'zcp_plain': 0.30803906917572005, 'zcp_snip': 2039.8636474609375, 'zcp_synflow': 77.00196012140994, 'zcp_zen': 103.83198547363281, 'zcp_val_accuracy': 0.8656851053237911}
| |
NASBench101_298854
|
NASBench101
|
298854
|
b4dca0fbc0c3adc3b2761989f34d79c5
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_968[FLOAT, 128x3x3x3]
%onnx::Conv_969[FLOAT, 128]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 128x128x1x1]
%onnx::Conv_983[FLOAT, 128x128x3x3]
%onnx::Conv_986[FLOAT, 128x128x1x1]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x1x1]
%onnx::Conv_998[FLOAT, 128x128x1x1]
%onnx::Conv_1001[FLOAT, 128x128x1x1]
%onnx::Conv_1004[FLOAT, 128x128x3x3]
%onnx::Conv_1007[FLOAT, 128x128x1x1]
%onnx::Conv_1010[FLOAT, 128x128x1x1]
%onnx::Conv_1013[FLOAT, 128x128x1x1]
%onnx::Conv_1016[FLOAT, 128x128x1x1]
%onnx::Conv_1019[FLOAT, 128x128x1x1]
%onnx::Conv_1022[FLOAT, 128x128x1x1]
%onnx::Conv_1025[FLOAT, 128x128x3x3]
%onnx::Conv_1028[FLOAT, 128x128x1x1]
%onnx::Conv_1031[FLOAT, 128x128x1x1]
%onnx::Conv_1034[FLOAT, 256x128x1x1]
%onnx::Conv_1035[FLOAT, 256]
%onnx::Conv_1037[FLOAT, 256x128x1x1]
%onnx::Conv_1040[FLOAT, 256x256x1x1]
%onnx::Conv_1043[FLOAT, 256x256x1x1]
%onnx::Conv_1046[FLOAT, 256x256x3x3]
%onnx::Conv_1049[FLOAT, 256x256x1x1]
%onnx::Conv_1052[FLOAT, 256x128x1x1]
%onnx::Conv_1055[FLOAT, 256x256x1x1]
%onnx::Conv_1058[FLOAT, 256x256x1x1]
%onnx::Conv_1061[FLOAT, 256x256x1x1]
%onnx::Conv_1064[FLOAT, 256x256x1x1]
%onnx::Conv_1067[FLOAT, 256x256x3x3]
%onnx::Conv_1070[FLOAT, 256x256x1x1]
%onnx::Conv_1073[FLOAT, 256x256x1x1]
%onnx::Conv_1076[FLOAT, 256x256x1x1]
%onnx::Conv_1079[FLOAT, 256x256x1x1]
%onnx::Conv_1082[FLOAT, 256x256x1x1]
%onnx::Conv_1085[FLOAT, 256x256x1x1]
%onnx::Conv_1088[FLOAT, 256x256x3x3]
%onnx::Conv_1091[FLOAT, 256x256x1x1]
%onnx::Conv_1094[FLOAT, 256x256x1x1]
%onnx::Conv_1097[FLOAT, 512x256x1x1]
%onnx::Conv_1098[FLOAT, 512]
%onnx::Conv_1100[FLOAT, 512x256x1x1]
%onnx::Conv_1103[FLOAT, 512x512x1x1]
%onnx::Conv_1106[FLOAT, 512x512x1x1]
%onnx::Conv_1109[FLOAT, 512x512x3x3]
%onnx::Conv_1112[FLOAT, 512x512x1x1]
%onnx::Conv_1115[FLOAT, 512x256x1x1]
%onnx::Conv_1118[FLOAT, 512x512x1x1]
%onnx::Conv_1121[FLOAT, 512x512x1x1]
%onnx::Conv_1124[FLOAT, 512x512x1x1]
%onnx::Conv_1127[FLOAT, 512x512x1x1]
%onnx::Conv_1130[FLOAT, 512x512x3x3]
%onnx::Conv_1133[FLOAT, 512x512x1x1]
%onnx::Conv_1136[FLOAT, 512x512x1x1]
%onnx::Conv_1139[FLOAT, 512x512x1x1]
%onnx::Conv_1142[FLOAT, 512x512x1x1]
%onnx::Conv_1145[FLOAT, 512x512x1x1]
%onnx::Conv_1148[FLOAT, 512x512x1x1]
%onnx::Conv_1151[FLOAT, 512x512x3x3]
%onnx::Conv_1154[FLOAT, 512x512x1x1]
%onnx::Conv_1157[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1158 = Identity(%onnx::Conv_1098)
%onnx::Conv_1155 = Identity(%onnx::Conv_1098)
%onnx::Conv_1152 = Identity(%onnx::Conv_1098)
%onnx::Conv_1149 = Identity(%onnx::Conv_1098)
%onnx::Conv_1146 = Identity(%onnx::Conv_1098)
%onnx::Conv_1143 = Identity(%onnx::Conv_1098)
%onnx::Conv_1140 = Identity(%onnx::Conv_1098)
%onnx::Conv_1137 = Identity(%onnx::Conv_1098)
%onnx::Conv_1134 = Identity(%onnx::Conv_1098)
%onnx::Conv_1131 = Identity(%onnx::Conv_1098)
%onnx::Conv_1128 = Identity(%onnx::Conv_1098)
%onnx::Conv_1125 = Identity(%onnx::Conv_1098)
%onnx::Conv_1122 = Identity(%onnx::Conv_1098)
%onnx::Conv_1119 = Identity(%onnx::Conv_1098)
%onnx::Conv_1116 = Identity(%onnx::Conv_1098)
%onnx::Conv_1113 = Identity(%onnx::Conv_1098)
%onnx::Conv_1110 = Identity(%onnx::Conv_1098)
%onnx::Conv_1107 = Identity(%onnx::Conv_1098)
%onnx::Conv_1104 = Identity(%onnx::Conv_1098)
%onnx::Conv_1101 = Identity(%onnx::Conv_1098)
%onnx::Conv_1095 = Identity(%onnx::Conv_1035)
%onnx::Conv_1092 = Identity(%onnx::Conv_1035)
%onnx::Conv_1089 = Identity(%onnx::Conv_1035)
%onnx::Conv_1086 = Identity(%onnx::Conv_1035)
%onnx::Conv_1083 = Identity(%onnx::Conv_1035)
%onnx::Conv_1080 = Identity(%onnx::Conv_1035)
%onnx::Conv_1077 = Identity(%onnx::Conv_1035)
%onnx::Conv_1074 = Identity(%onnx::Conv_1035)
%onnx::Conv_1071 = Identity(%onnx::Conv_1035)
%onnx::Conv_1068 = Identity(%onnx::Conv_1035)
%onnx::Conv_1065 = Identity(%onnx::Conv_1035)
%onnx::Conv_1062 = Identity(%onnx::Conv_1035)
%onnx::Conv_1059 = Identity(%onnx::Conv_1035)
%onnx::Conv_1056 = Identity(%onnx::Conv_1035)
%onnx::Conv_1053 = Identity(%onnx::Conv_1035)
%onnx::Conv_1050 = Identity(%onnx::Conv_1035)
%onnx::Conv_1047 = Identity(%onnx::Conv_1035)
%onnx::Conv_1044 = Identity(%onnx::Conv_1035)
%onnx::Conv_1041 = Identity(%onnx::Conv_1035)
%onnx::Conv_1038 = Identity(%onnx::Conv_1035)
%onnx::Conv_1032 = Identity(%onnx::Conv_969)
%onnx::Conv_1029 = Identity(%onnx::Conv_969)
%onnx::Conv_1026 = Identity(%onnx::Conv_969)
%onnx::Conv_1023 = Identity(%onnx::Conv_969)
%onnx::Conv_1020 = Identity(%onnx::Conv_969)
%onnx::Conv_1017 = Identity(%onnx::Conv_969)
%onnx::Conv_1014 = Identity(%onnx::Conv_969)
%onnx::Conv_1011 = Identity(%onnx::Conv_969)
%onnx::Conv_1008 = Identity(%onnx::Conv_969)
%onnx::Conv_1005 = Identity(%onnx::Conv_969)
%onnx::Conv_1002 = Identity(%onnx::Conv_969)
%onnx::Conv_999 = Identity(%onnx::Conv_969)
%onnx::Conv_996 = Identity(%onnx::Conv_969)
%onnx::Conv_993 = Identity(%onnx::Conv_969)
%onnx::Conv_990 = Identity(%onnx::Conv_969)
%onnx::Conv_987 = Identity(%onnx::Conv_969)
%onnx::Conv_984 = Identity(%onnx::Conv_969)
%onnx::Conv_981 = Identity(%onnx::Conv_969)
%onnx::Conv_978 = Identity(%onnx::Conv_969)
%onnx::Conv_975 = Identity(%onnx::Conv_969)
%onnx::Conv_972 = Identity(%onnx::Conv_969)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_968, %onnx::Conv_969)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_6_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_6_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_6_output_0)
%966 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %966
}
|
val_accuracy
| 93.038863
| 4,475,856,896
| 15,037,834
|
{'zcp_epe_nas': 83.67366747765136, 'zcp_fisher': 71.7791976928711, 'zcp_flops': 71613710336.0, 'zcp_grad_norm': 194.1246337890625, 'zcp_grasp': -243.29296875, 'zcp_jacov': -16.04652175619109, 'zcp_l2_norm': 1438.1966552734375, 'zcp_nwot': 237.86989936286267, 'zcp_params': 15037834.0, 'zcp_plain': 0.136882200837135, 'zcp_snip': 1475.0362548828125, 'zcp_synflow': 152.11724316148337, 'zcp_zen': 121.98777770996094, 'zcp_val_accuracy': 0.912760436534881}
| |
NASBench101_233191
|
NASBench101
|
233191
|
8d2dd49ab6f842730df8bbea5b20818d
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_869[FLOAT, 128x3x3x3]
%onnx::Conv_870[FLOAT, 128]
%onnx::Conv_872[FLOAT, 128x128x1x1]
%onnx::Conv_875[FLOAT, 128x128x3x3]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 128x128x1x1]
%onnx::Conv_884[FLOAT, 128x128x1x1]
%onnx::Conv_887[FLOAT, 128x128x3x3]
%onnx::Conv_890[FLOAT, 128x128x1x1]
%onnx::Conv_893[FLOAT, 128x128x3x3]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%onnx::Conv_899[FLOAT, 128x128x1x1]
%onnx::Conv_902[FLOAT, 128x128x1x1]
%onnx::Conv_905[FLOAT, 128x128x3x3]
%onnx::Conv_908[FLOAT, 128x128x1x1]
%onnx::Conv_911[FLOAT, 128x128x3x3]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 128x128x1x1]
%onnx::Conv_920[FLOAT, 128x128x1x1]
%onnx::Conv_923[FLOAT, 128x128x3x3]
%onnx::Conv_926[FLOAT, 256x128x1x1]
%onnx::Conv_927[FLOAT, 256]
%onnx::Conv_929[FLOAT, 256x256x3x3]
%onnx::Conv_932[FLOAT, 256x128x1x1]
%onnx::Conv_935[FLOAT, 256x256x1x1]
%onnx::Conv_938[FLOAT, 256x256x1x1]
%onnx::Conv_941[FLOAT, 256x256x3x3]
%onnx::Conv_944[FLOAT, 256x256x1x1]
%onnx::Conv_947[FLOAT, 256x256x3x3]
%onnx::Conv_950[FLOAT, 256x256x1x1]
%onnx::Conv_953[FLOAT, 256x256x1x1]
%onnx::Conv_956[FLOAT, 256x256x1x1]
%onnx::Conv_959[FLOAT, 256x256x3x3]
%onnx::Conv_962[FLOAT, 256x256x1x1]
%onnx::Conv_965[FLOAT, 256x256x3x3]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 256x256x1x1]
%onnx::Conv_974[FLOAT, 256x256x1x1]
%onnx::Conv_977[FLOAT, 256x256x3x3]
%onnx::Conv_980[FLOAT, 512x256x1x1]
%onnx::Conv_981[FLOAT, 512]
%onnx::Conv_983[FLOAT, 512x512x3x3]
%onnx::Conv_986[FLOAT, 512x256x1x1]
%onnx::Conv_989[FLOAT, 512x512x1x1]
%onnx::Conv_992[FLOAT, 512x512x1x1]
%onnx::Conv_995[FLOAT, 512x512x3x3]
%onnx::Conv_998[FLOAT, 512x512x1x1]
%onnx::Conv_1001[FLOAT, 512x512x3x3]
%onnx::Conv_1004[FLOAT, 512x512x1x1]
%onnx::Conv_1007[FLOAT, 512x512x1x1]
%onnx::Conv_1010[FLOAT, 512x512x1x1]
%onnx::Conv_1013[FLOAT, 512x512x3x3]
%onnx::Conv_1016[FLOAT, 512x512x1x1]
%onnx::Conv_1019[FLOAT, 512x512x3x3]
%onnx::Conv_1022[FLOAT, 512x512x1x1]
%onnx::Conv_1025[FLOAT, 512x512x1x1]
%onnx::Conv_1028[FLOAT, 512x512x1x1]
%onnx::Conv_1031[FLOAT, 512x512x3x3]
) {
%onnx::Conv_1032 = Identity(%onnx::Conv_981)
%onnx::Conv_1029 = Identity(%onnx::Conv_981)
%onnx::Conv_1026 = Identity(%onnx::Conv_981)
%onnx::Conv_1023 = Identity(%onnx::Conv_981)
%onnx::Conv_1020 = Identity(%onnx::Conv_981)
%onnx::Conv_1017 = Identity(%onnx::Conv_981)
%onnx::Conv_1014 = Identity(%onnx::Conv_981)
%onnx::Conv_1011 = Identity(%onnx::Conv_981)
%onnx::Conv_1008 = Identity(%onnx::Conv_981)
%onnx::Conv_1005 = Identity(%onnx::Conv_981)
%onnx::Conv_1002 = Identity(%onnx::Conv_981)
%onnx::Conv_999 = Identity(%onnx::Conv_981)
%onnx::Conv_996 = Identity(%onnx::Conv_981)
%onnx::Conv_993 = Identity(%onnx::Conv_981)
%onnx::Conv_990 = Identity(%onnx::Conv_981)
%onnx::Conv_987 = Identity(%onnx::Conv_981)
%onnx::Conv_984 = Identity(%onnx::Conv_981)
%onnx::Conv_978 = Identity(%onnx::Conv_927)
%onnx::Conv_975 = Identity(%onnx::Conv_927)
%onnx::Conv_972 = Identity(%onnx::Conv_927)
%onnx::Conv_969 = Identity(%onnx::Conv_927)
%onnx::Conv_966 = Identity(%onnx::Conv_927)
%onnx::Conv_963 = Identity(%onnx::Conv_927)
%onnx::Conv_960 = Identity(%onnx::Conv_927)
%onnx::Conv_957 = Identity(%onnx::Conv_927)
%onnx::Conv_954 = Identity(%onnx::Conv_927)
%onnx::Conv_951 = Identity(%onnx::Conv_927)
%onnx::Conv_948 = Identity(%onnx::Conv_927)
%onnx::Conv_945 = Identity(%onnx::Conv_927)
%onnx::Conv_942 = Identity(%onnx::Conv_927)
%onnx::Conv_939 = Identity(%onnx::Conv_927)
%onnx::Conv_936 = Identity(%onnx::Conv_927)
%onnx::Conv_933 = Identity(%onnx::Conv_927)
%onnx::Conv_930 = Identity(%onnx::Conv_927)
%onnx::Conv_924 = Identity(%onnx::Conv_870)
%onnx::Conv_921 = Identity(%onnx::Conv_870)
%onnx::Conv_918 = Identity(%onnx::Conv_870)
%onnx::Conv_915 = Identity(%onnx::Conv_870)
%onnx::Conv_912 = Identity(%onnx::Conv_870)
%onnx::Conv_909 = Identity(%onnx::Conv_870)
%onnx::Conv_906 = Identity(%onnx::Conv_870)
%onnx::Conv_903 = Identity(%onnx::Conv_870)
%onnx::Conv_900 = Identity(%onnx::Conv_870)
%onnx::Conv_897 = Identity(%onnx::Conv_870)
%onnx::Conv_894 = Identity(%onnx::Conv_870)
%onnx::Conv_891 = Identity(%onnx::Conv_870)
%onnx::Conv_888 = Identity(%onnx::Conv_870)
%onnx::Conv_885 = Identity(%onnx::Conv_870)
%onnx::Conv_882 = Identity(%onnx::Conv_870)
%onnx::Conv_879 = Identity(%onnx::Conv_870)
%onnx::Conv_876 = Identity(%onnx::Conv_870)
%onnx::Conv_873 = Identity(%onnx::Conv_870)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_869, %onnx::Conv_870)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%867 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %867
}
|
val_accuracy
| 88.191104
| 6,617,835,520
| 22,421,642
|
{'zcp_epe_nas': 169.91811338859108, 'zcp_fisher': 3571.360595703125, 'zcp_flops': 105885368320.0, 'zcp_grad_norm': 1041.4476318359375, 'zcp_grasp': 2538.109375, 'zcp_jacov': -16.05980570644685, 'zcp_l2_norm': 1242.439697265625, 'zcp_nwot': 235.19266058125893, 'zcp_params': 22421642.0, 'zcp_plain': -0.019103256985545002, 'zcp_snip': 7847.36865234375, 'zcp_synflow': 155.39558684615855, 'zcp_zen': 108.09114837646484, 'zcp_val_accuracy': 0.9132612347602841}
| |
NASBench101_95336
|
NASBench101
|
95336
|
39a9de6604f6bfd08592e339352a3a0c
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_833[FLOAT, 128x3x3x3]
%onnx::Conv_834[FLOAT, 128]
%onnx::Conv_836[FLOAT, 32x128x1x1]
%onnx::Conv_837[FLOAT, 32]
%onnx::Conv_839[FLOAT, 32x32x1x1]
%onnx::Conv_842[FLOAT, 32x32x3x3]
%onnx::Conv_845[FLOAT, 32x32x3x3]
%onnx::Conv_848[FLOAT, 32x32x3x3]
%onnx::Conv_851[FLOAT, 128x128x1x1]
%onnx::Conv_854[FLOAT, 32x128x1x1]
%onnx::Conv_857[FLOAT, 32x32x1x1]
%onnx::Conv_860[FLOAT, 32x32x3x3]
%onnx::Conv_863[FLOAT, 32x32x3x3]
%onnx::Conv_866[FLOAT, 32x32x3x3]
%onnx::Conv_869[FLOAT, 128x128x1x1]
%onnx::Conv_872[FLOAT, 32x128x1x1]
%onnx::Conv_875[FLOAT, 32x32x1x1]
%onnx::Conv_878[FLOAT, 32x32x3x3]
%onnx::Conv_881[FLOAT, 32x32x3x3]
%onnx::Conv_884[FLOAT, 32x32x3x3]
%onnx::Conv_887[FLOAT, 128x128x1x1]
%onnx::Conv_890[FLOAT, 64x128x1x1]
%onnx::Conv_891[FLOAT, 64]
%onnx::Conv_893[FLOAT, 64x64x1x1]
%onnx::Conv_896[FLOAT, 64x64x3x3]
%onnx::Conv_899[FLOAT, 64x64x3x3]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 256x128x1x1]
%onnx::Conv_906[FLOAT, 256]
%onnx::Conv_908[FLOAT, 64x256x1x1]
%onnx::Conv_911[FLOAT, 64x64x1x1]
%onnx::Conv_914[FLOAT, 64x64x3x3]
%onnx::Conv_917[FLOAT, 64x64x3x3]
%onnx::Conv_920[FLOAT, 64x64x3x3]
%onnx::Conv_923[FLOAT, 256x256x1x1]
%onnx::Conv_926[FLOAT, 64x256x1x1]
%onnx::Conv_929[FLOAT, 64x64x1x1]
%onnx::Conv_932[FLOAT, 64x64x3x3]
%onnx::Conv_935[FLOAT, 64x64x3x3]
%onnx::Conv_938[FLOAT, 64x64x3x3]
%onnx::Conv_941[FLOAT, 256x256x1x1]
%onnx::Conv_944[FLOAT, 128x256x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x128x3x3]
%onnx::Conv_953[FLOAT, 128x128x3x3]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 512x256x1x1]
%onnx::Conv_960[FLOAT, 512]
%onnx::Conv_962[FLOAT, 128x512x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x128x3x3]
%onnx::Conv_971[FLOAT, 128x128x3x3]
%onnx::Conv_974[FLOAT, 128x128x3x3]
%onnx::Conv_977[FLOAT, 512x512x1x1]
%onnx::Conv_980[FLOAT, 128x512x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x128x3x3]
%onnx::Conv_989[FLOAT, 128x128x3x3]
%onnx::Conv_992[FLOAT, 128x128x3x3]
%onnx::Conv_995[FLOAT, 512x512x1x1]
) {
%onnx::Conv_996 = Identity(%onnx::Conv_960)
%onnx::Conv_993 = Identity(%onnx::Conv_834)
%onnx::Conv_990 = Identity(%onnx::Conv_834)
%onnx::Conv_987 = Identity(%onnx::Conv_834)
%onnx::Conv_984 = Identity(%onnx::Conv_834)
%onnx::Conv_981 = Identity(%onnx::Conv_834)
%onnx::Conv_978 = Identity(%onnx::Conv_960)
%onnx::Conv_975 = Identity(%onnx::Conv_834)
%onnx::Conv_972 = Identity(%onnx::Conv_834)
%onnx::Conv_969 = Identity(%onnx::Conv_834)
%onnx::Conv_966 = Identity(%onnx::Conv_834)
%onnx::Conv_963 = Identity(%onnx::Conv_834)
%onnx::Conv_957 = Identity(%onnx::Conv_834)
%onnx::Conv_954 = Identity(%onnx::Conv_834)
%onnx::Conv_951 = Identity(%onnx::Conv_834)
%onnx::Conv_948 = Identity(%onnx::Conv_834)
%onnx::Conv_945 = Identity(%onnx::Conv_834)
%onnx::Conv_942 = Identity(%onnx::Conv_906)
%onnx::Conv_939 = Identity(%onnx::Conv_891)
%onnx::Conv_936 = Identity(%onnx::Conv_891)
%onnx::Conv_933 = Identity(%onnx::Conv_891)
%onnx::Conv_930 = Identity(%onnx::Conv_891)
%onnx::Conv_927 = Identity(%onnx::Conv_891)
%onnx::Conv_924 = Identity(%onnx::Conv_906)
%onnx::Conv_921 = Identity(%onnx::Conv_891)
%onnx::Conv_918 = Identity(%onnx::Conv_891)
%onnx::Conv_915 = Identity(%onnx::Conv_891)
%onnx::Conv_912 = Identity(%onnx::Conv_891)
%onnx::Conv_909 = Identity(%onnx::Conv_891)
%onnx::Conv_903 = Identity(%onnx::Conv_891)
%onnx::Conv_900 = Identity(%onnx::Conv_891)
%onnx::Conv_897 = Identity(%onnx::Conv_891)
%onnx::Conv_894 = Identity(%onnx::Conv_891)
%onnx::Conv_888 = Identity(%onnx::Conv_834)
%onnx::Conv_885 = Identity(%onnx::Conv_837)
%onnx::Conv_882 = Identity(%onnx::Conv_837)
%onnx::Conv_879 = Identity(%onnx::Conv_837)
%onnx::Conv_876 = Identity(%onnx::Conv_837)
%onnx::Conv_873 = Identity(%onnx::Conv_837)
%onnx::Conv_870 = Identity(%onnx::Conv_834)
%onnx::Conv_867 = Identity(%onnx::Conv_837)
%onnx::Conv_864 = Identity(%onnx::Conv_837)
%onnx::Conv_861 = Identity(%onnx::Conv_837)
%onnx::Conv_858 = Identity(%onnx::Conv_837)
%onnx::Conv_855 = Identity(%onnx::Conv_837)
%onnx::Conv_852 = Identity(%onnx::Conv_834)
%onnx::Conv_849 = Identity(%onnx::Conv_837)
%onnx::Conv_846 = Identity(%onnx::Conv_837)
%onnx::Conv_843 = Identity(%onnx::Conv_837)
%onnx::Conv_840 = Identity(%onnx::Conv_837)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_833, %onnx::Conv_834)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_4_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_4_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_4_output_0)
%831 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %831
}
|
val_accuracy
| 93.118989
| 884,549,632
| 2,912,714
|
{'zcp_epe_nas': 51.09717800097904, 'zcp_fisher': 1.717111349105835, 'zcp_flops': 14152794112.0, 'zcp_grad_norm': 32.36526107788086, 'zcp_grasp': -2.224609375, 'zcp_jacov': -16.05364096559493, 'zcp_l2_norm': 819.4003295898438, 'zcp_nwot': 220.29125475746156, 'zcp_params': 2912714.0, 'zcp_plain': 0.025657471269369, 'zcp_snip': 161.47061157226562, 'zcp_synflow': 110.45237792639409, 'zcp_zen': 92.43630981445312, 'zcp_val_accuracy': 0.875}
| |
NASBench101_103373
|
NASBench101
|
103373
|
3e882419008fbd2809dac8925b008b1d
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_608[FLOAT, 128x3x3x3]
%onnx::Conv_609[FLOAT, 128]
%onnx::Conv_611[FLOAT, 64x128x1x1]
%onnx::Conv_612[FLOAT, 64]
%onnx::Conv_614[FLOAT, 64x64x3x3]
%onnx::Conv_617[FLOAT, 64x64x3x3]
%onnx::Conv_620[FLOAT, 64x128x1x1]
%onnx::Conv_623[FLOAT, 64x64x3x3]
%onnx::Conv_626[FLOAT, 64x64x3x3]
%onnx::Conv_629[FLOAT, 64x128x1x1]
%onnx::Conv_632[FLOAT, 64x64x3x3]
%onnx::Conv_635[FLOAT, 64x64x3x3]
%onnx::Conv_638[FLOAT, 128x128x1x1]
%onnx::Conv_641[FLOAT, 128x128x3x3]
%onnx::Conv_644[FLOAT, 128x128x3x3]
%onnx::Conv_647[FLOAT, 128x256x1x1]
%onnx::Conv_650[FLOAT, 128x128x3x3]
%onnx::Conv_653[FLOAT, 128x128x3x3]
%onnx::Conv_656[FLOAT, 128x256x1x1]
%onnx::Conv_659[FLOAT, 128x128x3x3]
%onnx::Conv_662[FLOAT, 128x128x3x3]
%onnx::Conv_665[FLOAT, 256x256x1x1]
%onnx::Conv_666[FLOAT, 256]
%onnx::Conv_668[FLOAT, 256x256x3x3]
%onnx::Conv_671[FLOAT, 256x256x3x3]
%onnx::Conv_674[FLOAT, 256x512x1x1]
%onnx::Conv_677[FLOAT, 256x256x3x3]
%onnx::Conv_680[FLOAT, 256x256x3x3]
%onnx::Conv_683[FLOAT, 256x512x1x1]
%onnx::Conv_686[FLOAT, 256x256x3x3]
%onnx::Conv_689[FLOAT, 256x256x3x3]
) {
%onnx::Conv_690 = Identity(%onnx::Conv_666)
%onnx::Conv_687 = Identity(%onnx::Conv_666)
%onnx::Conv_684 = Identity(%onnx::Conv_666)
%onnx::Conv_681 = Identity(%onnx::Conv_666)
%onnx::Conv_678 = Identity(%onnx::Conv_666)
%onnx::Conv_675 = Identity(%onnx::Conv_666)
%onnx::Conv_672 = Identity(%onnx::Conv_666)
%onnx::Conv_669 = Identity(%onnx::Conv_666)
%onnx::Conv_663 = Identity(%onnx::Conv_609)
%onnx::Conv_660 = Identity(%onnx::Conv_609)
%onnx::Conv_657 = Identity(%onnx::Conv_609)
%onnx::Conv_654 = Identity(%onnx::Conv_609)
%onnx::Conv_651 = Identity(%onnx::Conv_609)
%onnx::Conv_648 = Identity(%onnx::Conv_609)
%onnx::Conv_645 = Identity(%onnx::Conv_609)
%onnx::Conv_642 = Identity(%onnx::Conv_609)
%onnx::Conv_639 = Identity(%onnx::Conv_609)
%onnx::Conv_636 = Identity(%onnx::Conv_612)
%onnx::Conv_633 = Identity(%onnx::Conv_612)
%onnx::Conv_630 = Identity(%onnx::Conv_612)
%onnx::Conv_627 = Identity(%onnx::Conv_612)
%onnx::Conv_624 = Identity(%onnx::Conv_612)
%onnx::Conv_621 = Identity(%onnx::Conv_612)
%onnx::Conv_618 = Identity(%onnx::Conv_612)
%onnx::Conv_615 = Identity(%onnx::Conv_612)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_608, %onnx::Conv_609)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_611, %onnx::Conv_612)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_614, %onnx::Conv_615)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_617, %onnx::Conv_618)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_6_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_620, %onnx::Conv_621)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_623, %onnx::Conv_624)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_626, %onnx::Conv_627)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_6_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_629, %onnx::Conv_630)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_632, %onnx::Conv_633)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_635, %onnx::Conv_636)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_6_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_638, %onnx::Conv_639)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_641, %onnx::Conv_642)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_644, %onnx::Conv_645)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_6_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_647, %onnx::Conv_648)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_650, %onnx::Conv_651)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_653, %onnx::Conv_654)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_6_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_656, %onnx::Conv_657)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_659, %onnx::Conv_660)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_662, %onnx::Conv_663)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_6_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_6_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_6_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_6_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%606 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %606
}
|
val_accuracy
| 88.321316
| 1,509,566,464
| 5,095,946
|
{'zcp_epe_nas': 116.11441341701516, 'zcp_fisher': 357.463134765625, 'zcp_flops': 24153063424.0, 'zcp_grad_norm': 311.1882629394531, 'zcp_grasp': -743.5029296875, 'zcp_jacov': -16.051507159374086, 'zcp_l2_norm': 498.70977783203125, 'zcp_nwot': 213.84018693108487, 'zcp_params': 5095946.0, 'zcp_plain': 0.38567018508911105, 'zcp_snip': 1726.168212890625, 'zcp_synflow': 100.54978201088056, 'zcp_zen': 64.74905395507812, 'zcp_val_accuracy': 0.912960708141326}
| |
NASBench101_236115
|
NASBench101
|
236115
|
8ee207098ca20dc8fc5bbf0de1b3d8d4
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_770[FLOAT, 128x3x3x3]
%onnx::Conv_771[FLOAT, 128]
%onnx::Conv_773[FLOAT, 128x128x1x1]
%onnx::Conv_776[FLOAT, 128x128x1x1]
%onnx::Conv_779[FLOAT, 128x128x1x1]
%onnx::Conv_782[FLOAT, 128x128x1x1]
%onnx::Conv_785[FLOAT, 128x128x3x3]
%onnx::Conv_788[FLOAT, 128x128x1x1]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 128x128x1x1]
%onnx::Conv_797[FLOAT, 128x128x1x1]
%onnx::Conv_800[FLOAT, 128x128x3x3]
%onnx::Conv_803[FLOAT, 128x128x1x1]
%onnx::Conv_806[FLOAT, 128x128x1x1]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 128x128x3x3]
%onnx::Conv_818[FLOAT, 256x128x1x1]
%onnx::Conv_819[FLOAT, 256]
%onnx::Conv_821[FLOAT, 256x256x1x1]
%onnx::Conv_824[FLOAT, 256x128x1x1]
%onnx::Conv_827[FLOAT, 256x128x1x1]
%onnx::Conv_830[FLOAT, 256x256x3x3]
%onnx::Conv_833[FLOAT, 256x256x1x1]
%onnx::Conv_836[FLOAT, 256x256x1x1]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x256x1x1]
%onnx::Conv_845[FLOAT, 256x256x3x3]
%onnx::Conv_848[FLOAT, 256x256x1x1]
%onnx::Conv_851[FLOAT, 256x256x1x1]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_857[FLOAT, 256x256x1x1]
%onnx::Conv_860[FLOAT, 256x256x3x3]
%onnx::Conv_863[FLOAT, 512x256x1x1]
%onnx::Conv_864[FLOAT, 512]
%onnx::Conv_866[FLOAT, 512x512x1x1]
%onnx::Conv_869[FLOAT, 512x256x1x1]
%onnx::Conv_872[FLOAT, 512x256x1x1]
%onnx::Conv_875[FLOAT, 512x512x3x3]
%onnx::Conv_878[FLOAT, 512x512x1x1]
%onnx::Conv_881[FLOAT, 512x512x1x1]
%onnx::Conv_884[FLOAT, 512x512x1x1]
%onnx::Conv_887[FLOAT, 512x512x1x1]
%onnx::Conv_890[FLOAT, 512x512x3x3]
%onnx::Conv_893[FLOAT, 512x512x1x1]
%onnx::Conv_896[FLOAT, 512x512x1x1]
%onnx::Conv_899[FLOAT, 512x512x1x1]
%onnx::Conv_902[FLOAT, 512x512x1x1]
%onnx::Conv_905[FLOAT, 512x512x3x3]
) {
%onnx::Conv_906 = Identity(%onnx::Conv_864)
%onnx::Conv_903 = Identity(%onnx::Conv_864)
%onnx::Conv_900 = Identity(%onnx::Conv_864)
%onnx::Conv_897 = Identity(%onnx::Conv_864)
%onnx::Conv_894 = Identity(%onnx::Conv_864)
%onnx::Conv_891 = Identity(%onnx::Conv_864)
%onnx::Conv_888 = Identity(%onnx::Conv_864)
%onnx::Conv_885 = Identity(%onnx::Conv_864)
%onnx::Conv_882 = Identity(%onnx::Conv_864)
%onnx::Conv_879 = Identity(%onnx::Conv_864)
%onnx::Conv_876 = Identity(%onnx::Conv_864)
%onnx::Conv_873 = Identity(%onnx::Conv_864)
%onnx::Conv_870 = Identity(%onnx::Conv_864)
%onnx::Conv_867 = Identity(%onnx::Conv_864)
%onnx::Conv_861 = Identity(%onnx::Conv_819)
%onnx::Conv_858 = Identity(%onnx::Conv_819)
%onnx::Conv_855 = Identity(%onnx::Conv_819)
%onnx::Conv_852 = Identity(%onnx::Conv_819)
%onnx::Conv_849 = Identity(%onnx::Conv_819)
%onnx::Conv_846 = Identity(%onnx::Conv_819)
%onnx::Conv_843 = Identity(%onnx::Conv_819)
%onnx::Conv_840 = Identity(%onnx::Conv_819)
%onnx::Conv_837 = Identity(%onnx::Conv_819)
%onnx::Conv_834 = Identity(%onnx::Conv_819)
%onnx::Conv_831 = Identity(%onnx::Conv_819)
%onnx::Conv_828 = Identity(%onnx::Conv_819)
%onnx::Conv_825 = Identity(%onnx::Conv_819)
%onnx::Conv_822 = Identity(%onnx::Conv_819)
%onnx::Conv_816 = Identity(%onnx::Conv_771)
%onnx::Conv_813 = Identity(%onnx::Conv_771)
%onnx::Conv_810 = Identity(%onnx::Conv_771)
%onnx::Conv_807 = Identity(%onnx::Conv_771)
%onnx::Conv_804 = Identity(%onnx::Conv_771)
%onnx::Conv_801 = Identity(%onnx::Conv_771)
%onnx::Conv_798 = Identity(%onnx::Conv_771)
%onnx::Conv_795 = Identity(%onnx::Conv_771)
%onnx::Conv_792 = Identity(%onnx::Conv_771)
%onnx::Conv_789 = Identity(%onnx::Conv_771)
%onnx::Conv_786 = Identity(%onnx::Conv_771)
%onnx::Conv_783 = Identity(%onnx::Conv_771)
%onnx::Conv_780 = Identity(%onnx::Conv_771)
%onnx::Conv_777 = Identity(%onnx::Conv_771)
%onnx::Conv_774 = Identity(%onnx::Conv_771)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_770, %onnx::Conv_771)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%768 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %768
}
|
val_accuracy
| 89.653444
| 3,860,867,072
| 12,962,698
|
{'zcp_epe_nas': 77.04684996458157, 'zcp_fisher': 31.400863647460938, 'zcp_flops': 61773873152.0, 'zcp_grad_norm': 77.77468872070312, 'zcp_grasp': -2.47662353515625, 'zcp_jacov': -16.049365115313595, 'zcp_l2_norm': 1014.1078491210938, 'zcp_nwot': 230.71449115030856, 'zcp_params': 12962698.0, 'zcp_plain': 0.059040877968072, 'zcp_snip': 680.3833618164062, 'zcp_synflow': 100.097664633617, 'zcp_zen': 90.77262878417969, 'zcp_val_accuracy': 0.8870192170143121}
| |
NASBench101_340433
|
NASBench101
|
340433
|
cdda0ad5d12ebe07e2c14e13257e2fde
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_743[FLOAT, 128x3x3x3]
%onnx::Conv_744[FLOAT, 128]
%onnx::Conv_746[FLOAT, 64x128x1x1]
%onnx::Conv_747[FLOAT, 64]
%onnx::Conv_749[FLOAT, 64x64x1x1]
%onnx::Conv_752[FLOAT, 64x128x1x1]
%onnx::Conv_755[FLOAT, 64x64x3x3]
%onnx::Conv_758[FLOAT, 64x64x3x3]
%onnx::Conv_761[FLOAT, 64x128x1x1]
%onnx::Conv_764[FLOAT, 64x64x1x1]
%onnx::Conv_767[FLOAT, 64x128x1x1]
%onnx::Conv_770[FLOAT, 64x64x3x3]
%onnx::Conv_773[FLOAT, 64x64x3x3]
%onnx::Conv_776[FLOAT, 64x128x1x1]
%onnx::Conv_779[FLOAT, 64x64x1x1]
%onnx::Conv_782[FLOAT, 64x128x1x1]
%onnx::Conv_785[FLOAT, 64x64x3x3]
%onnx::Conv_788[FLOAT, 64x64x3x3]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 128x128x1x1]
%onnx::Conv_797[FLOAT, 128x128x1x1]
%onnx::Conv_800[FLOAT, 128x128x3x3]
%onnx::Conv_803[FLOAT, 128x128x3x3]
%onnx::Conv_806[FLOAT, 128x256x1x1]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x256x1x1]
%onnx::Conv_815[FLOAT, 128x128x3x3]
%onnx::Conv_818[FLOAT, 128x128x3x3]
%onnx::Conv_821[FLOAT, 128x256x1x1]
%onnx::Conv_824[FLOAT, 128x128x1x1]
%onnx::Conv_827[FLOAT, 128x256x1x1]
%onnx::Conv_830[FLOAT, 128x128x3x3]
%onnx::Conv_833[FLOAT, 128x128x3x3]
%onnx::Conv_836[FLOAT, 256x256x1x1]
%onnx::Conv_837[FLOAT, 256]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x256x1x1]
%onnx::Conv_845[FLOAT, 256x256x3x3]
%onnx::Conv_848[FLOAT, 256x256x3x3]
%onnx::Conv_851[FLOAT, 256x512x1x1]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_857[FLOAT, 256x512x1x1]
%onnx::Conv_860[FLOAT, 256x256x3x3]
%onnx::Conv_863[FLOAT, 256x256x3x3]
%onnx::Conv_866[FLOAT, 256x512x1x1]
%onnx::Conv_869[FLOAT, 256x256x1x1]
%onnx::Conv_872[FLOAT, 256x512x1x1]
%onnx::Conv_875[FLOAT, 256x256x3x3]
%onnx::Conv_878[FLOAT, 256x256x3x3]
) {
%onnx::Conv_879 = Identity(%onnx::Conv_837)
%onnx::Conv_876 = Identity(%onnx::Conv_837)
%onnx::Conv_873 = Identity(%onnx::Conv_837)
%onnx::Conv_870 = Identity(%onnx::Conv_837)
%onnx::Conv_867 = Identity(%onnx::Conv_837)
%onnx::Conv_864 = Identity(%onnx::Conv_837)
%onnx::Conv_861 = Identity(%onnx::Conv_837)
%onnx::Conv_858 = Identity(%onnx::Conv_837)
%onnx::Conv_855 = Identity(%onnx::Conv_837)
%onnx::Conv_852 = Identity(%onnx::Conv_837)
%onnx::Conv_849 = Identity(%onnx::Conv_837)
%onnx::Conv_846 = Identity(%onnx::Conv_837)
%onnx::Conv_843 = Identity(%onnx::Conv_837)
%onnx::Conv_840 = Identity(%onnx::Conv_837)
%onnx::Conv_834 = Identity(%onnx::Conv_744)
%onnx::Conv_831 = Identity(%onnx::Conv_744)
%onnx::Conv_828 = Identity(%onnx::Conv_744)
%onnx::Conv_825 = Identity(%onnx::Conv_744)
%onnx::Conv_822 = Identity(%onnx::Conv_744)
%onnx::Conv_819 = Identity(%onnx::Conv_744)
%onnx::Conv_816 = Identity(%onnx::Conv_744)
%onnx::Conv_813 = Identity(%onnx::Conv_744)
%onnx::Conv_810 = Identity(%onnx::Conv_744)
%onnx::Conv_807 = Identity(%onnx::Conv_744)
%onnx::Conv_804 = Identity(%onnx::Conv_744)
%onnx::Conv_801 = Identity(%onnx::Conv_744)
%onnx::Conv_798 = Identity(%onnx::Conv_744)
%onnx::Conv_795 = Identity(%onnx::Conv_744)
%onnx::Conv_792 = Identity(%onnx::Conv_744)
%onnx::Conv_789 = Identity(%onnx::Conv_747)
%onnx::Conv_786 = Identity(%onnx::Conv_747)
%onnx::Conv_783 = Identity(%onnx::Conv_747)
%onnx::Conv_780 = Identity(%onnx::Conv_747)
%onnx::Conv_777 = Identity(%onnx::Conv_747)
%onnx::Conv_774 = Identity(%onnx::Conv_747)
%onnx::Conv_771 = Identity(%onnx::Conv_747)
%onnx::Conv_768 = Identity(%onnx::Conv_747)
%onnx::Conv_765 = Identity(%onnx::Conv_747)
%onnx::Conv_762 = Identity(%onnx::Conv_747)
%onnx::Conv_759 = Identity(%onnx::Conv_747)
%onnx::Conv_756 = Identity(%onnx::Conv_747)
%onnx::Conv_753 = Identity(%onnx::Conv_747)
%onnx::Conv_750 = Identity(%onnx::Conv_747)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_743, %onnx::Conv_744)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%741 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %741
}
|
val_accuracy
| 91.035658
| 1,724,786,688
| 5,793,546
|
{'zcp_epe_nas': 86.30152981025668, 'zcp_fisher': 27.342260360717773, 'zcp_flops': 27596587008.0, 'zcp_grad_norm': 90.56918334960938, 'zcp_grasp': -4.160888671875, 'zcp_jacov': -16.05167315163437, 'zcp_l2_norm': 844.2401733398438, 'zcp_nwot': 221.37172374085898, 'zcp_params': 5793546.0, 'zcp_plain': 0.027166621759533, 'zcp_snip': 567.1798095703125, 'zcp_synflow': 103.60453673204333, 'zcp_zen': 91.66604614257812, 'zcp_val_accuracy': 0.914763629436492}
| |
NASBench101_96249
|
NASBench101
|
96249
|
3a3bb923c320fe96831e9ec2f514eb40
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_986[FLOAT, 128x3x3x3]
%onnx::Conv_987[FLOAT, 128]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x1x1]
%onnx::Conv_998[FLOAT, 128x128x1x1]
%onnx::Conv_1001[FLOAT, 128x128x1x1]
%onnx::Conv_1004[FLOAT, 128x128x3x3]
%onnx::Conv_1007[FLOAT, 128x128x1x1]
%onnx::Conv_1010[FLOAT, 128x128x1x1]
%onnx::Conv_1013[FLOAT, 128x128x1x1]
%onnx::Conv_1016[FLOAT, 128x128x1x1]
%onnx::Conv_1019[FLOAT, 128x128x1x1]
%onnx::Conv_1022[FLOAT, 128x128x1x1]
%onnx::Conv_1025[FLOAT, 128x128x3x3]
%onnx::Conv_1028[FLOAT, 128x128x1x1]
%onnx::Conv_1031[FLOAT, 128x128x1x1]
%onnx::Conv_1034[FLOAT, 128x128x1x1]
%onnx::Conv_1037[FLOAT, 128x128x1x1]
%onnx::Conv_1040[FLOAT, 128x128x1x1]
%onnx::Conv_1043[FLOAT, 128x128x1x1]
%onnx::Conv_1046[FLOAT, 128x128x3x3]
%onnx::Conv_1049[FLOAT, 128x128x1x1]
%onnx::Conv_1052[FLOAT, 256x128x1x1]
%onnx::Conv_1053[FLOAT, 256]
%onnx::Conv_1055[FLOAT, 256x256x1x1]
%onnx::Conv_1058[FLOAT, 256x256x1x1]
%onnx::Conv_1061[FLOAT, 256x256x1x1]
%onnx::Conv_1064[FLOAT, 256x128x1x1]
%onnx::Conv_1067[FLOAT, 256x256x3x3]
%onnx::Conv_1070[FLOAT, 256x128x1x1]
%onnx::Conv_1073[FLOAT, 256x256x1x1]
%onnx::Conv_1076[FLOAT, 256x256x1x1]
%onnx::Conv_1079[FLOAT, 256x256x1x1]
%onnx::Conv_1082[FLOAT, 256x256x1x1]
%onnx::Conv_1085[FLOAT, 256x256x1x1]
%onnx::Conv_1088[FLOAT, 256x256x3x3]
%onnx::Conv_1091[FLOAT, 256x256x1x1]
%onnx::Conv_1094[FLOAT, 256x256x1x1]
%onnx::Conv_1097[FLOAT, 256x256x1x1]
%onnx::Conv_1100[FLOAT, 256x256x1x1]
%onnx::Conv_1103[FLOAT, 256x256x1x1]
%onnx::Conv_1106[FLOAT, 256x256x1x1]
%onnx::Conv_1109[FLOAT, 256x256x3x3]
%onnx::Conv_1112[FLOAT, 256x256x1x1]
%onnx::Conv_1115[FLOAT, 512x256x1x1]
%onnx::Conv_1116[FLOAT, 512]
%onnx::Conv_1118[FLOAT, 512x512x1x1]
%onnx::Conv_1121[FLOAT, 512x512x1x1]
%onnx::Conv_1124[FLOAT, 512x512x1x1]
%onnx::Conv_1127[FLOAT, 512x256x1x1]
%onnx::Conv_1130[FLOAT, 512x512x3x3]
%onnx::Conv_1133[FLOAT, 512x256x1x1]
%onnx::Conv_1136[FLOAT, 512x512x1x1]
%onnx::Conv_1139[FLOAT, 512x512x1x1]
%onnx::Conv_1142[FLOAT, 512x512x1x1]
%onnx::Conv_1145[FLOAT, 512x512x1x1]
%onnx::Conv_1148[FLOAT, 512x512x1x1]
%onnx::Conv_1151[FLOAT, 512x512x3x3]
%onnx::Conv_1154[FLOAT, 512x512x1x1]
%onnx::Conv_1157[FLOAT, 512x512x1x1]
%onnx::Conv_1160[FLOAT, 512x512x1x1]
%onnx::Conv_1163[FLOAT, 512x512x1x1]
%onnx::Conv_1166[FLOAT, 512x512x1x1]
%onnx::Conv_1169[FLOAT, 512x512x1x1]
%onnx::Conv_1172[FLOAT, 512x512x3x3]
%onnx::Conv_1175[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1176 = Identity(%onnx::Conv_1116)
%onnx::Conv_1173 = Identity(%onnx::Conv_1116)
%onnx::Conv_1170 = Identity(%onnx::Conv_1116)
%onnx::Conv_1167 = Identity(%onnx::Conv_1116)
%onnx::Conv_1164 = Identity(%onnx::Conv_1116)
%onnx::Conv_1161 = Identity(%onnx::Conv_1116)
%onnx::Conv_1158 = Identity(%onnx::Conv_1116)
%onnx::Conv_1155 = Identity(%onnx::Conv_1116)
%onnx::Conv_1152 = Identity(%onnx::Conv_1116)
%onnx::Conv_1149 = Identity(%onnx::Conv_1116)
%onnx::Conv_1146 = Identity(%onnx::Conv_1116)
%onnx::Conv_1143 = Identity(%onnx::Conv_1116)
%onnx::Conv_1140 = Identity(%onnx::Conv_1116)
%onnx::Conv_1137 = Identity(%onnx::Conv_1116)
%onnx::Conv_1134 = Identity(%onnx::Conv_1116)
%onnx::Conv_1131 = Identity(%onnx::Conv_1116)
%onnx::Conv_1128 = Identity(%onnx::Conv_1116)
%onnx::Conv_1125 = Identity(%onnx::Conv_1116)
%onnx::Conv_1122 = Identity(%onnx::Conv_1116)
%onnx::Conv_1119 = Identity(%onnx::Conv_1116)
%onnx::Conv_1113 = Identity(%onnx::Conv_1053)
%onnx::Conv_1110 = Identity(%onnx::Conv_1053)
%onnx::Conv_1107 = Identity(%onnx::Conv_1053)
%onnx::Conv_1104 = Identity(%onnx::Conv_1053)
%onnx::Conv_1101 = Identity(%onnx::Conv_1053)
%onnx::Conv_1098 = Identity(%onnx::Conv_1053)
%onnx::Conv_1095 = Identity(%onnx::Conv_1053)
%onnx::Conv_1092 = Identity(%onnx::Conv_1053)
%onnx::Conv_1089 = Identity(%onnx::Conv_1053)
%onnx::Conv_1086 = Identity(%onnx::Conv_1053)
%onnx::Conv_1083 = Identity(%onnx::Conv_1053)
%onnx::Conv_1080 = Identity(%onnx::Conv_1053)
%onnx::Conv_1077 = Identity(%onnx::Conv_1053)
%onnx::Conv_1074 = Identity(%onnx::Conv_1053)
%onnx::Conv_1071 = Identity(%onnx::Conv_1053)
%onnx::Conv_1068 = Identity(%onnx::Conv_1053)
%onnx::Conv_1065 = Identity(%onnx::Conv_1053)
%onnx::Conv_1062 = Identity(%onnx::Conv_1053)
%onnx::Conv_1059 = Identity(%onnx::Conv_1053)
%onnx::Conv_1056 = Identity(%onnx::Conv_1053)
%onnx::Conv_1050 = Identity(%onnx::Conv_987)
%onnx::Conv_1047 = Identity(%onnx::Conv_987)
%onnx::Conv_1044 = Identity(%onnx::Conv_987)
%onnx::Conv_1041 = Identity(%onnx::Conv_987)
%onnx::Conv_1038 = Identity(%onnx::Conv_987)
%onnx::Conv_1035 = Identity(%onnx::Conv_987)
%onnx::Conv_1032 = Identity(%onnx::Conv_987)
%onnx::Conv_1029 = Identity(%onnx::Conv_987)
%onnx::Conv_1026 = Identity(%onnx::Conv_987)
%onnx::Conv_1023 = Identity(%onnx::Conv_987)
%onnx::Conv_1020 = Identity(%onnx::Conv_987)
%onnx::Conv_1017 = Identity(%onnx::Conv_987)
%onnx::Conv_1014 = Identity(%onnx::Conv_987)
%onnx::Conv_1011 = Identity(%onnx::Conv_987)
%onnx::Conv_1008 = Identity(%onnx::Conv_987)
%onnx::Conv_1005 = Identity(%onnx::Conv_987)
%onnx::Conv_1002 = Identity(%onnx::Conv_987)
%onnx::Conv_999 = Identity(%onnx::Conv_987)
%onnx::Conv_996 = Identity(%onnx::Conv_987)
%onnx::Conv_993 = Identity(%onnx::Conv_987)
%onnx::Conv_990 = Identity(%onnx::Conv_987)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_986, %onnx::Conv_987)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_7_output_0 = Add(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_7_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_7_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_7_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_7_output_0 = Add(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_7_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_7_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_7_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_7_output_0 = Add(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_7_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_7_output_0 = Add(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_7_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_7_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_7_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_7_output_0 = Add(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_7_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_7_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_7_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_7_output_0 = Add(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_7_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_7_output_0 = Add(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_7_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_7_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_7_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_7_output_0 = Add(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_7_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_7_output_0, %onnx::Conv_1169, %onnx::Conv_1170)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_1172, %onnx::Conv_1173)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_7_output_0, %onnx::Conv_1175, %onnx::Conv_1176)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_7_output_0 = Add(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_7_output_0)
%984 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %984
}
|
val_accuracy
| 91.997194
| 4,475,856,896
| 15,037,834
|
{'zcp_epe_nas': 163.7173101034644, 'zcp_fisher': 14.533599853515625, 'zcp_flops': 71613710336.0, 'zcp_grad_norm': 87.7364501953125, 'zcp_grasp': 0.5126953125, 'zcp_jacov': -16.05469881238527, 'zcp_l2_norm': 1438.560302734375, 'zcp_nwot': 237.67096633214607, 'zcp_params': 15037834.0, 'zcp_plain': 0.034490875899791, 'zcp_snip': 713.8153076171875, 'zcp_synflow': 152.13690719603346, 'zcp_zen': 121.83246612548828, 'zcp_val_accuracy': 0.920572936534881}
| |
NASBench101_64615
|
NASBench101
|
64615
|
2739103e9613fb97d973e505dc5a96b8
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_869[FLOAT, 128x3x3x3]
%onnx::Conv_870[FLOAT, 128]
%onnx::Conv_872[FLOAT, 64x128x1x1]
%onnx::Conv_873[FLOAT, 64]
%onnx::Conv_875[FLOAT, 64x64x3x3]
%onnx::Conv_878[FLOAT, 64x64x1x1]
%onnx::Conv_881[FLOAT, 64x64x3x3]
%onnx::Conv_884[FLOAT, 64x64x3x3]
%onnx::Conv_887[FLOAT, 64x64x3x3]
%onnx::Conv_890[FLOAT, 64x128x1x1]
%onnx::Conv_893[FLOAT, 64x64x3x3]
%onnx::Conv_896[FLOAT, 64x64x1x1]
%onnx::Conv_899[FLOAT, 64x64x3x3]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x64x3x3]
%onnx::Conv_908[FLOAT, 64x128x1x1]
%onnx::Conv_911[FLOAT, 64x64x3x3]
%onnx::Conv_914[FLOAT, 64x64x1x1]
%onnx::Conv_917[FLOAT, 64x64x3x3]
%onnx::Conv_920[FLOAT, 64x64x3x3]
%onnx::Conv_923[FLOAT, 64x64x3x3]
%onnx::Conv_926[FLOAT, 128x128x1x1]
%onnx::Conv_929[FLOAT, 128x128x3x3]
%onnx::Conv_932[FLOAT, 128x128x1x1]
%onnx::Conv_935[FLOAT, 128x128x3x3]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 128x128x3x3]
%onnx::Conv_944[FLOAT, 128x256x1x1]
%onnx::Conv_947[FLOAT, 128x128x3x3]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%onnx::Conv_953[FLOAT, 128x128x3x3]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x128x3x3]
%onnx::Conv_962[FLOAT, 128x256x1x1]
%onnx::Conv_965[FLOAT, 128x128x3x3]
%onnx::Conv_968[FLOAT, 128x128x1x1]
%onnx::Conv_971[FLOAT, 128x128x3x3]
%onnx::Conv_974[FLOAT, 128x128x3x3]
%onnx::Conv_977[FLOAT, 128x128x3x3]
%onnx::Conv_980[FLOAT, 256x256x1x1]
%onnx::Conv_981[FLOAT, 256]
%onnx::Conv_983[FLOAT, 256x256x3x3]
%onnx::Conv_986[FLOAT, 256x256x1x1]
%onnx::Conv_989[FLOAT, 256x256x3x3]
%onnx::Conv_992[FLOAT, 256x256x3x3]
%onnx::Conv_995[FLOAT, 256x256x3x3]
%onnx::Conv_998[FLOAT, 256x512x1x1]
%onnx::Conv_1001[FLOAT, 256x256x3x3]
%onnx::Conv_1004[FLOAT, 256x256x1x1]
%onnx::Conv_1007[FLOAT, 256x256x3x3]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x256x3x3]
%onnx::Conv_1016[FLOAT, 256x512x1x1]
%onnx::Conv_1019[FLOAT, 256x256x3x3]
%onnx::Conv_1022[FLOAT, 256x256x1x1]
%onnx::Conv_1025[FLOAT, 256x256x3x3]
%onnx::Conv_1028[FLOAT, 256x256x3x3]
%onnx::Conv_1031[FLOAT, 256x256x3x3]
) {
%onnx::Conv_1032 = Identity(%onnx::Conv_981)
%onnx::Conv_1029 = Identity(%onnx::Conv_981)
%onnx::Conv_1026 = Identity(%onnx::Conv_981)
%onnx::Conv_1023 = Identity(%onnx::Conv_981)
%onnx::Conv_1020 = Identity(%onnx::Conv_981)
%onnx::Conv_1017 = Identity(%onnx::Conv_981)
%onnx::Conv_1014 = Identity(%onnx::Conv_981)
%onnx::Conv_1011 = Identity(%onnx::Conv_981)
%onnx::Conv_1008 = Identity(%onnx::Conv_981)
%onnx::Conv_1005 = Identity(%onnx::Conv_981)
%onnx::Conv_1002 = Identity(%onnx::Conv_981)
%onnx::Conv_999 = Identity(%onnx::Conv_981)
%onnx::Conv_996 = Identity(%onnx::Conv_981)
%onnx::Conv_993 = Identity(%onnx::Conv_981)
%onnx::Conv_990 = Identity(%onnx::Conv_981)
%onnx::Conv_987 = Identity(%onnx::Conv_981)
%onnx::Conv_984 = Identity(%onnx::Conv_981)
%onnx::Conv_978 = Identity(%onnx::Conv_870)
%onnx::Conv_975 = Identity(%onnx::Conv_870)
%onnx::Conv_972 = Identity(%onnx::Conv_870)
%onnx::Conv_969 = Identity(%onnx::Conv_870)
%onnx::Conv_966 = Identity(%onnx::Conv_870)
%onnx::Conv_963 = Identity(%onnx::Conv_870)
%onnx::Conv_960 = Identity(%onnx::Conv_870)
%onnx::Conv_957 = Identity(%onnx::Conv_870)
%onnx::Conv_954 = Identity(%onnx::Conv_870)
%onnx::Conv_951 = Identity(%onnx::Conv_870)
%onnx::Conv_948 = Identity(%onnx::Conv_870)
%onnx::Conv_945 = Identity(%onnx::Conv_870)
%onnx::Conv_942 = Identity(%onnx::Conv_870)
%onnx::Conv_939 = Identity(%onnx::Conv_870)
%onnx::Conv_936 = Identity(%onnx::Conv_870)
%onnx::Conv_933 = Identity(%onnx::Conv_870)
%onnx::Conv_930 = Identity(%onnx::Conv_870)
%onnx::Conv_927 = Identity(%onnx::Conv_870)
%onnx::Conv_924 = Identity(%onnx::Conv_873)
%onnx::Conv_921 = Identity(%onnx::Conv_873)
%onnx::Conv_918 = Identity(%onnx::Conv_873)
%onnx::Conv_915 = Identity(%onnx::Conv_873)
%onnx::Conv_912 = Identity(%onnx::Conv_873)
%onnx::Conv_909 = Identity(%onnx::Conv_873)
%onnx::Conv_906 = Identity(%onnx::Conv_873)
%onnx::Conv_903 = Identity(%onnx::Conv_873)
%onnx::Conv_900 = Identity(%onnx::Conv_873)
%onnx::Conv_897 = Identity(%onnx::Conv_873)
%onnx::Conv_894 = Identity(%onnx::Conv_873)
%onnx::Conv_891 = Identity(%onnx::Conv_873)
%onnx::Conv_888 = Identity(%onnx::Conv_873)
%onnx::Conv_885 = Identity(%onnx::Conv_873)
%onnx::Conv_882 = Identity(%onnx::Conv_873)
%onnx::Conv_879 = Identity(%onnx::Conv_873)
%onnx::Conv_876 = Identity(%onnx::Conv_873)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_869, %onnx::Conv_870)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%867 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %867
}
|
val_accuracy
| 90.104169
| 2,952,275,968
| 10,006,922
|
{'zcp_epe_nas': 83.15567906464841, 'zcp_fisher': 1040.12255859375, 'zcp_flops': 47236415488.0, 'zcp_grad_norm': 650.982421875, 'zcp_grasp': -2326.4921875, 'zcp_jacov': -16.041529573346285, 'zcp_l2_norm': 948.9301147460938, 'zcp_nwot': 224.4618298331374, 'zcp_params': 10006922.0, 'zcp_plain': -0.027963012456893, 'zcp_snip': 3370.93359375, 'zcp_synflow': 181.8667994368503, 'zcp_zen': 109.95274353027344, 'zcp_val_accuracy': 0.925580918788909}
| |
NASBench101_239005
|
NASBench101
|
239005
|
90a46758d169175ecbd4078715a23c3b
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_752[FLOAT, 128x3x3x3]
%onnx::Conv_753[FLOAT, 128]
%onnx::Conv_755[FLOAT, 64x128x1x1]
%onnx::Conv_756[FLOAT, 64]
%onnx::Conv_758[FLOAT, 64x64x3x3]
%onnx::Conv_761[FLOAT, 64x64x3x3]
%onnx::Conv_764[FLOAT, 64x64x3x3]
%onnx::Conv_767[FLOAT, 64x64x3x3]
%onnx::Conv_770[FLOAT, 64x128x1x1]
%onnx::Conv_773[FLOAT, 64x64x3x3]
%onnx::Conv_776[FLOAT, 64x64x3x3]
%onnx::Conv_779[FLOAT, 64x64x3x3]
%onnx::Conv_782[FLOAT, 64x64x3x3]
%onnx::Conv_785[FLOAT, 64x128x1x1]
%onnx::Conv_788[FLOAT, 64x64x3x3]
%onnx::Conv_791[FLOAT, 64x64x3x3]
%onnx::Conv_794[FLOAT, 64x64x3x3]
%onnx::Conv_797[FLOAT, 64x64x3x3]
%onnx::Conv_800[FLOAT, 128x128x1x1]
%onnx::Conv_803[FLOAT, 128x128x3x3]
%onnx::Conv_806[FLOAT, 128x128x3x3]
%onnx::Conv_809[FLOAT, 128x128x3x3]
%onnx::Conv_812[FLOAT, 128x128x3x3]
%onnx::Conv_815[FLOAT, 128x256x1x1]
%onnx::Conv_818[FLOAT, 128x128x3x3]
%onnx::Conv_821[FLOAT, 128x128x3x3]
%onnx::Conv_824[FLOAT, 128x128x3x3]
%onnx::Conv_827[FLOAT, 128x128x3x3]
%onnx::Conv_830[FLOAT, 128x256x1x1]
%onnx::Conv_833[FLOAT, 128x128x3x3]
%onnx::Conv_836[FLOAT, 128x128x3x3]
%onnx::Conv_839[FLOAT, 128x128x3x3]
%onnx::Conv_842[FLOAT, 128x128x3x3]
%onnx::Conv_845[FLOAT, 256x256x1x1]
%onnx::Conv_846[FLOAT, 256]
%onnx::Conv_848[FLOAT, 256x256x3x3]
%onnx::Conv_851[FLOAT, 256x256x3x3]
%onnx::Conv_854[FLOAT, 256x256x3x3]
%onnx::Conv_857[FLOAT, 256x256x3x3]
%onnx::Conv_860[FLOAT, 256x512x1x1]
%onnx::Conv_863[FLOAT, 256x256x3x3]
%onnx::Conv_866[FLOAT, 256x256x3x3]
%onnx::Conv_869[FLOAT, 256x256x3x3]
%onnx::Conv_872[FLOAT, 256x256x3x3]
%onnx::Conv_875[FLOAT, 256x512x1x1]
%onnx::Conv_878[FLOAT, 256x256x3x3]
%onnx::Conv_881[FLOAT, 256x256x3x3]
%onnx::Conv_884[FLOAT, 256x256x3x3]
%onnx::Conv_887[FLOAT, 256x256x3x3]
) {
%onnx::Conv_888 = Identity(%onnx::Conv_846)
%onnx::Conv_885 = Identity(%onnx::Conv_846)
%onnx::Conv_882 = Identity(%onnx::Conv_846)
%onnx::Conv_879 = Identity(%onnx::Conv_846)
%onnx::Conv_876 = Identity(%onnx::Conv_846)
%onnx::Conv_873 = Identity(%onnx::Conv_846)
%onnx::Conv_870 = Identity(%onnx::Conv_846)
%onnx::Conv_867 = Identity(%onnx::Conv_846)
%onnx::Conv_864 = Identity(%onnx::Conv_846)
%onnx::Conv_861 = Identity(%onnx::Conv_846)
%onnx::Conv_858 = Identity(%onnx::Conv_846)
%onnx::Conv_855 = Identity(%onnx::Conv_846)
%onnx::Conv_852 = Identity(%onnx::Conv_846)
%onnx::Conv_849 = Identity(%onnx::Conv_846)
%onnx::Conv_843 = Identity(%onnx::Conv_753)
%onnx::Conv_840 = Identity(%onnx::Conv_753)
%onnx::Conv_837 = Identity(%onnx::Conv_753)
%onnx::Conv_834 = Identity(%onnx::Conv_753)
%onnx::Conv_831 = Identity(%onnx::Conv_753)
%onnx::Conv_828 = Identity(%onnx::Conv_753)
%onnx::Conv_825 = Identity(%onnx::Conv_753)
%onnx::Conv_822 = Identity(%onnx::Conv_753)
%onnx::Conv_819 = Identity(%onnx::Conv_753)
%onnx::Conv_816 = Identity(%onnx::Conv_753)
%onnx::Conv_813 = Identity(%onnx::Conv_753)
%onnx::Conv_810 = Identity(%onnx::Conv_753)
%onnx::Conv_807 = Identity(%onnx::Conv_753)
%onnx::Conv_804 = Identity(%onnx::Conv_753)
%onnx::Conv_801 = Identity(%onnx::Conv_753)
%onnx::Conv_798 = Identity(%onnx::Conv_756)
%onnx::Conv_795 = Identity(%onnx::Conv_756)
%onnx::Conv_792 = Identity(%onnx::Conv_756)
%onnx::Conv_789 = Identity(%onnx::Conv_756)
%onnx::Conv_786 = Identity(%onnx::Conv_756)
%onnx::Conv_783 = Identity(%onnx::Conv_756)
%onnx::Conv_780 = Identity(%onnx::Conv_756)
%onnx::Conv_777 = Identity(%onnx::Conv_756)
%onnx::Conv_774 = Identity(%onnx::Conv_756)
%onnx::Conv_771 = Identity(%onnx::Conv_756)
%onnx::Conv_768 = Identity(%onnx::Conv_756)
%onnx::Conv_765 = Identity(%onnx::Conv_756)
%onnx::Conv_762 = Identity(%onnx::Conv_756)
%onnx::Conv_759 = Identity(%onnx::Conv_756)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_752, %onnx::Conv_753)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%750 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %750
}
|
val_accuracy
| 90.294468
| 2,874,025,984
| 9,746,186
|
{'zcp_epe_nas': 123.37444094128767, 'zcp_fisher': 279.75543212890625, 'zcp_flops': 45984415744.0, 'zcp_grad_norm': 290.49859619140625, 'zcp_grasp': -292.6298828125, 'zcp_jacov': -16.05127725440974, 'zcp_l2_norm': 798.4322509765625, 'zcp_nwot': 221.10130783545273, 'zcp_params': 9746186.0, 'zcp_plain': 0.0019335565157230002, 'zcp_snip': 1710.6649169921875, 'zcp_synflow': 159.7723156317077, 'zcp_zen': 107.88858032226562, 'zcp_val_accuracy': 0.8850160241127011}
| |
NASBench101_342561
|
NASBench101
|
342561
|
cf1318f143b122695830e54c92ac8823
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_851[FLOAT, 128x3x3x3]
%onnx::Conv_852[FLOAT, 128]
%onnx::Conv_854[FLOAT, 128x128x1x1]
%onnx::Conv_857[FLOAT, 128x128x1x1]
%onnx::Conv_860[FLOAT, 128x128x1x1]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%onnx::Conv_866[FLOAT, 128x128x3x3]
%onnx::Conv_869[FLOAT, 128x128x1x1]
%onnx::Conv_872[FLOAT, 128x128x1x1]
%onnx::Conv_875[FLOAT, 128x128x1x1]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 128x128x1x1]
%onnx::Conv_884[FLOAT, 128x128x3x3]
%onnx::Conv_887[FLOAT, 128x128x1x1]
%onnx::Conv_890[FLOAT, 128x128x1x1]
%onnx::Conv_893[FLOAT, 128x128x1x1]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%onnx::Conv_899[FLOAT, 128x128x1x1]
%onnx::Conv_902[FLOAT, 128x128x3x3]
%onnx::Conv_905[FLOAT, 128x128x1x1]
%onnx::Conv_908[FLOAT, 256x128x1x1]
%onnx::Conv_909[FLOAT, 256]
%onnx::Conv_911[FLOAT, 256x256x1x1]
%onnx::Conv_914[FLOAT, 256x256x1x1]
%onnx::Conv_917[FLOAT, 256x128x1x1]
%onnx::Conv_920[FLOAT, 256x256x3x3]
%onnx::Conv_923[FLOAT, 256x256x1x1]
%onnx::Conv_926[FLOAT, 256x256x1x1]
%onnx::Conv_929[FLOAT, 256x256x1x1]
%onnx::Conv_932[FLOAT, 256x256x1x1]
%onnx::Conv_935[FLOAT, 256x256x1x1]
%onnx::Conv_938[FLOAT, 256x256x3x3]
%onnx::Conv_941[FLOAT, 256x256x1x1]
%onnx::Conv_944[FLOAT, 256x256x1x1]
%onnx::Conv_947[FLOAT, 256x256x1x1]
%onnx::Conv_950[FLOAT, 256x256x1x1]
%onnx::Conv_953[FLOAT, 256x256x1x1]
%onnx::Conv_956[FLOAT, 256x256x3x3]
%onnx::Conv_959[FLOAT, 256x256x1x1]
%onnx::Conv_962[FLOAT, 512x256x1x1]
%onnx::Conv_963[FLOAT, 512]
%onnx::Conv_965[FLOAT, 512x512x1x1]
%onnx::Conv_968[FLOAT, 512x512x1x1]
%onnx::Conv_971[FLOAT, 512x256x1x1]
%onnx::Conv_974[FLOAT, 512x512x3x3]
%onnx::Conv_977[FLOAT, 512x512x1x1]
%onnx::Conv_980[FLOAT, 512x512x1x1]
%onnx::Conv_983[FLOAT, 512x512x1x1]
%onnx::Conv_986[FLOAT, 512x512x1x1]
%onnx::Conv_989[FLOAT, 512x512x1x1]
%onnx::Conv_992[FLOAT, 512x512x3x3]
%onnx::Conv_995[FLOAT, 512x512x1x1]
%onnx::Conv_998[FLOAT, 512x512x1x1]
%onnx::Conv_1001[FLOAT, 512x512x1x1]
%onnx::Conv_1004[FLOAT, 512x512x1x1]
%onnx::Conv_1007[FLOAT, 512x512x1x1]
%onnx::Conv_1010[FLOAT, 512x512x3x3]
%onnx::Conv_1013[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1014 = Identity(%onnx::Conv_963)
%onnx::Conv_1011 = Identity(%onnx::Conv_963)
%onnx::Conv_1008 = Identity(%onnx::Conv_963)
%onnx::Conv_1005 = Identity(%onnx::Conv_963)
%onnx::Conv_1002 = Identity(%onnx::Conv_963)
%onnx::Conv_999 = Identity(%onnx::Conv_963)
%onnx::Conv_996 = Identity(%onnx::Conv_963)
%onnx::Conv_993 = Identity(%onnx::Conv_963)
%onnx::Conv_990 = Identity(%onnx::Conv_963)
%onnx::Conv_987 = Identity(%onnx::Conv_963)
%onnx::Conv_984 = Identity(%onnx::Conv_963)
%onnx::Conv_981 = Identity(%onnx::Conv_963)
%onnx::Conv_978 = Identity(%onnx::Conv_963)
%onnx::Conv_975 = Identity(%onnx::Conv_963)
%onnx::Conv_972 = Identity(%onnx::Conv_963)
%onnx::Conv_969 = Identity(%onnx::Conv_963)
%onnx::Conv_966 = Identity(%onnx::Conv_963)
%onnx::Conv_960 = Identity(%onnx::Conv_909)
%onnx::Conv_957 = Identity(%onnx::Conv_909)
%onnx::Conv_954 = Identity(%onnx::Conv_909)
%onnx::Conv_951 = Identity(%onnx::Conv_909)
%onnx::Conv_948 = Identity(%onnx::Conv_909)
%onnx::Conv_945 = Identity(%onnx::Conv_909)
%onnx::Conv_942 = Identity(%onnx::Conv_909)
%onnx::Conv_939 = Identity(%onnx::Conv_909)
%onnx::Conv_936 = Identity(%onnx::Conv_909)
%onnx::Conv_933 = Identity(%onnx::Conv_909)
%onnx::Conv_930 = Identity(%onnx::Conv_909)
%onnx::Conv_927 = Identity(%onnx::Conv_909)
%onnx::Conv_924 = Identity(%onnx::Conv_909)
%onnx::Conv_921 = Identity(%onnx::Conv_909)
%onnx::Conv_918 = Identity(%onnx::Conv_909)
%onnx::Conv_915 = Identity(%onnx::Conv_909)
%onnx::Conv_912 = Identity(%onnx::Conv_909)
%onnx::Conv_906 = Identity(%onnx::Conv_852)
%onnx::Conv_903 = Identity(%onnx::Conv_852)
%onnx::Conv_900 = Identity(%onnx::Conv_852)
%onnx::Conv_897 = Identity(%onnx::Conv_852)
%onnx::Conv_894 = Identity(%onnx::Conv_852)
%onnx::Conv_891 = Identity(%onnx::Conv_852)
%onnx::Conv_888 = Identity(%onnx::Conv_852)
%onnx::Conv_885 = Identity(%onnx::Conv_852)
%onnx::Conv_882 = Identity(%onnx::Conv_852)
%onnx::Conv_879 = Identity(%onnx::Conv_852)
%onnx::Conv_876 = Identity(%onnx::Conv_852)
%onnx::Conv_873 = Identity(%onnx::Conv_852)
%onnx::Conv_870 = Identity(%onnx::Conv_852)
%onnx::Conv_867 = Identity(%onnx::Conv_852)
%onnx::Conv_864 = Identity(%onnx::Conv_852)
%onnx::Conv_861 = Identity(%onnx::Conv_852)
%onnx::Conv_858 = Identity(%onnx::Conv_852)
%onnx::Conv_855 = Identity(%onnx::Conv_852)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_851, %onnx::Conv_852)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%849 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %849
}
|
val_accuracy
| 89.002407
| 4,201,916,416
| 14,164,106
|
{'zcp_epe_nas': 102.95214675870473, 'zcp_fisher': 1150.08154296875, 'zcp_flops': 67230662656.0, 'zcp_grad_norm': 557.2409057617188, 'zcp_grasp': -541.546875, 'zcp_jacov': -16.05158926297117, 'zcp_l2_norm': 1243.1900634765625, 'zcp_nwot': 234.95670689148676, 'zcp_params': 14164106.0, 'zcp_plain': 0.019761756062507, 'zcp_snip': 4022.76953125, 'zcp_synflow': 146.68756981327726, 'zcp_zen': 105.2568588256836, 'zcp_val_accuracy': 0.9278846383094781}
| |
NASBench101_383321
|
NASBench101
|
383321
|
e7bd7f873ec3bff7bc5e1424553ed993
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_860[FLOAT, 128x3x3x3]
%onnx::Conv_861[FLOAT, 128]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%onnx::Conv_866[FLOAT, 128x128x1x1]
%onnx::Conv_869[FLOAT, 128x128x1x1]
%onnx::Conv_872[FLOAT, 128x128x1x1]
%onnx::Conv_875[FLOAT, 128x128x1x1]
%onnx::Conv_878[FLOAT, 128x128x3x3]
%onnx::Conv_881[FLOAT, 128x128x1x1]
%onnx::Conv_884[FLOAT, 128x128x1x1]
%onnx::Conv_887[FLOAT, 128x128x1x1]
%onnx::Conv_890[FLOAT, 128x128x1x1]
%onnx::Conv_893[FLOAT, 128x128x1x1]
%onnx::Conv_896[FLOAT, 128x128x3x3]
%onnx::Conv_899[FLOAT, 128x128x1x1]
%onnx::Conv_902[FLOAT, 128x128x1x1]
%onnx::Conv_905[FLOAT, 128x128x1x1]
%onnx::Conv_908[FLOAT, 128x128x1x1]
%onnx::Conv_911[FLOAT, 128x128x1x1]
%onnx::Conv_914[FLOAT, 128x128x3x3]
%onnx::Conv_917[FLOAT, 256x128x1x1]
%onnx::Conv_918[FLOAT, 256]
%onnx::Conv_920[FLOAT, 256x256x1x1]
%onnx::Conv_923[FLOAT, 256x256x1x1]
%onnx::Conv_926[FLOAT, 256x128x1x1]
%onnx::Conv_929[FLOAT, 256x128x1x1]
%onnx::Conv_932[FLOAT, 256x256x3x3]
%onnx::Conv_935[FLOAT, 256x256x1x1]
%onnx::Conv_938[FLOAT, 256x256x1x1]
%onnx::Conv_941[FLOAT, 256x256x1x1]
%onnx::Conv_944[FLOAT, 256x256x1x1]
%onnx::Conv_947[FLOAT, 256x256x1x1]
%onnx::Conv_950[FLOAT, 256x256x3x3]
%onnx::Conv_953[FLOAT, 256x256x1x1]
%onnx::Conv_956[FLOAT, 256x256x1x1]
%onnx::Conv_959[FLOAT, 256x256x1x1]
%onnx::Conv_962[FLOAT, 256x256x1x1]
%onnx::Conv_965[FLOAT, 256x256x1x1]
%onnx::Conv_968[FLOAT, 256x256x3x3]
%onnx::Conv_971[FLOAT, 512x256x1x1]
%onnx::Conv_972[FLOAT, 512]
%onnx::Conv_974[FLOAT, 512x512x1x1]
%onnx::Conv_977[FLOAT, 512x512x1x1]
%onnx::Conv_980[FLOAT, 512x256x1x1]
%onnx::Conv_983[FLOAT, 512x256x1x1]
%onnx::Conv_986[FLOAT, 512x512x3x3]
%onnx::Conv_989[FLOAT, 512x512x1x1]
%onnx::Conv_992[FLOAT, 512x512x1x1]
%onnx::Conv_995[FLOAT, 512x512x1x1]
%onnx::Conv_998[FLOAT, 512x512x1x1]
%onnx::Conv_1001[FLOAT, 512x512x1x1]
%onnx::Conv_1004[FLOAT, 512x512x3x3]
%onnx::Conv_1007[FLOAT, 512x512x1x1]
%onnx::Conv_1010[FLOAT, 512x512x1x1]
%onnx::Conv_1013[FLOAT, 512x512x1x1]
%onnx::Conv_1016[FLOAT, 512x512x1x1]
%onnx::Conv_1019[FLOAT, 512x512x1x1]
%onnx::Conv_1022[FLOAT, 512x512x3x3]
) {
%onnx::Conv_1023 = Identity(%onnx::Conv_972)
%onnx::Conv_1020 = Identity(%onnx::Conv_972)
%onnx::Conv_1017 = Identity(%onnx::Conv_972)
%onnx::Conv_1014 = Identity(%onnx::Conv_972)
%onnx::Conv_1011 = Identity(%onnx::Conv_972)
%onnx::Conv_1008 = Identity(%onnx::Conv_972)
%onnx::Conv_1005 = Identity(%onnx::Conv_972)
%onnx::Conv_1002 = Identity(%onnx::Conv_972)
%onnx::Conv_999 = Identity(%onnx::Conv_972)
%onnx::Conv_996 = Identity(%onnx::Conv_972)
%onnx::Conv_993 = Identity(%onnx::Conv_972)
%onnx::Conv_990 = Identity(%onnx::Conv_972)
%onnx::Conv_987 = Identity(%onnx::Conv_972)
%onnx::Conv_984 = Identity(%onnx::Conv_972)
%onnx::Conv_981 = Identity(%onnx::Conv_972)
%onnx::Conv_978 = Identity(%onnx::Conv_972)
%onnx::Conv_975 = Identity(%onnx::Conv_972)
%onnx::Conv_969 = Identity(%onnx::Conv_918)
%onnx::Conv_966 = Identity(%onnx::Conv_918)
%onnx::Conv_963 = Identity(%onnx::Conv_918)
%onnx::Conv_960 = Identity(%onnx::Conv_918)
%onnx::Conv_957 = Identity(%onnx::Conv_918)
%onnx::Conv_954 = Identity(%onnx::Conv_918)
%onnx::Conv_951 = Identity(%onnx::Conv_918)
%onnx::Conv_948 = Identity(%onnx::Conv_918)
%onnx::Conv_945 = Identity(%onnx::Conv_918)
%onnx::Conv_942 = Identity(%onnx::Conv_918)
%onnx::Conv_939 = Identity(%onnx::Conv_918)
%onnx::Conv_936 = Identity(%onnx::Conv_918)
%onnx::Conv_933 = Identity(%onnx::Conv_918)
%onnx::Conv_930 = Identity(%onnx::Conv_918)
%onnx::Conv_927 = Identity(%onnx::Conv_918)
%onnx::Conv_924 = Identity(%onnx::Conv_918)
%onnx::Conv_921 = Identity(%onnx::Conv_918)
%onnx::Conv_915 = Identity(%onnx::Conv_861)
%onnx::Conv_912 = Identity(%onnx::Conv_861)
%onnx::Conv_909 = Identity(%onnx::Conv_861)
%onnx::Conv_906 = Identity(%onnx::Conv_861)
%onnx::Conv_903 = Identity(%onnx::Conv_861)
%onnx::Conv_900 = Identity(%onnx::Conv_861)
%onnx::Conv_897 = Identity(%onnx::Conv_861)
%onnx::Conv_894 = Identity(%onnx::Conv_861)
%onnx::Conv_891 = Identity(%onnx::Conv_861)
%onnx::Conv_888 = Identity(%onnx::Conv_861)
%onnx::Conv_885 = Identity(%onnx::Conv_861)
%onnx::Conv_882 = Identity(%onnx::Conv_861)
%onnx::Conv_879 = Identity(%onnx::Conv_861)
%onnx::Conv_876 = Identity(%onnx::Conv_861)
%onnx::Conv_873 = Identity(%onnx::Conv_861)
%onnx::Conv_870 = Identity(%onnx::Conv_861)
%onnx::Conv_867 = Identity(%onnx::Conv_861)
%onnx::Conv_864 = Identity(%onnx::Conv_861)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_860, %onnx::Conv_861)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%858 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %858
}
|
val_accuracy
| 91.957134
| 4,168,361,984
| 14,000,266
|
{'zcp_epe_nas': 144.37297050654354, 'zcp_fisher': 15.085017204284668, 'zcp_flops': 66693791744.0, 'zcp_grad_norm': 61.6700439453125, 'zcp_grasp': -0.44149780273437506, 'zcp_jacov': -16.047917183117207, 'zcp_l2_norm': 1226.322265625, 'zcp_nwot': 233.93256499679492, 'zcp_params': 14000266.0, 'zcp_plain': 0.014785350300371002, 'zcp_snip': 525.4090576171875, 'zcp_synflow': 120.27729793282245, 'zcp_zen': 103.96998596191406, 'zcp_val_accuracy': 0.924378991127014}
| |
NASBench101_78328
|
NASBench101
|
78328
|
2f8101a369da4d726242b0aa202fcb32
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_977[FLOAT, 128x3x3x3]
%onnx::Conv_978[FLOAT, 128]
%onnx::Conv_980[FLOAT, 64x128x1x1]
%onnx::Conv_981[FLOAT, 64]
%onnx::Conv_983[FLOAT, 64x64x3x3]
%onnx::Conv_986[FLOAT, 64x128x1x1]
%onnx::Conv_989[FLOAT, 64x64x1x1]
%onnx::Conv_992[FLOAT, 64x64x1x1]
%onnx::Conv_995[FLOAT, 64x128x1x1]
%onnx::Conv_998[FLOAT, 64x64x1x1]
%onnx::Conv_1001[FLOAT, 64x128x1x1]
%onnx::Conv_1004[FLOAT, 64x64x3x3]
%onnx::Conv_1007[FLOAT, 64x128x1x1]
%onnx::Conv_1010[FLOAT, 64x64x1x1]
%onnx::Conv_1013[FLOAT, 64x64x1x1]
%onnx::Conv_1016[FLOAT, 64x128x1x1]
%onnx::Conv_1019[FLOAT, 64x64x1x1]
%onnx::Conv_1022[FLOAT, 64x128x1x1]
%onnx::Conv_1025[FLOAT, 64x64x3x3]
%onnx::Conv_1028[FLOAT, 64x128x1x1]
%onnx::Conv_1031[FLOAT, 64x64x1x1]
%onnx::Conv_1034[FLOAT, 64x64x1x1]
%onnx::Conv_1037[FLOAT, 64x128x1x1]
%onnx::Conv_1040[FLOAT, 64x64x1x1]
%onnx::Conv_1043[FLOAT, 128x128x1x1]
%onnx::Conv_1046[FLOAT, 128x128x3x3]
%onnx::Conv_1049[FLOAT, 128x128x1x1]
%onnx::Conv_1052[FLOAT, 128x128x1x1]
%onnx::Conv_1055[FLOAT, 128x128x1x1]
%onnx::Conv_1058[FLOAT, 128x128x1x1]
%onnx::Conv_1061[FLOAT, 128x128x1x1]
%onnx::Conv_1064[FLOAT, 128x256x1x1]
%onnx::Conv_1067[FLOAT, 128x128x3x3]
%onnx::Conv_1070[FLOAT, 128x256x1x1]
%onnx::Conv_1073[FLOAT, 128x128x1x1]
%onnx::Conv_1076[FLOAT, 128x128x1x1]
%onnx::Conv_1079[FLOAT, 128x256x1x1]
%onnx::Conv_1082[FLOAT, 128x128x1x1]
%onnx::Conv_1085[FLOAT, 128x256x1x1]
%onnx::Conv_1088[FLOAT, 128x128x3x3]
%onnx::Conv_1091[FLOAT, 128x256x1x1]
%onnx::Conv_1094[FLOAT, 128x128x1x1]
%onnx::Conv_1097[FLOAT, 128x128x1x1]
%onnx::Conv_1100[FLOAT, 128x256x1x1]
%onnx::Conv_1103[FLOAT, 128x128x1x1]
%onnx::Conv_1106[FLOAT, 256x256x1x1]
%onnx::Conv_1107[FLOAT, 256]
%onnx::Conv_1109[FLOAT, 256x256x3x3]
%onnx::Conv_1112[FLOAT, 256x256x1x1]
%onnx::Conv_1115[FLOAT, 256x256x1x1]
%onnx::Conv_1118[FLOAT, 256x256x1x1]
%onnx::Conv_1121[FLOAT, 256x256x1x1]
%onnx::Conv_1124[FLOAT, 256x256x1x1]
%onnx::Conv_1127[FLOAT, 256x512x1x1]
%onnx::Conv_1130[FLOAT, 256x256x3x3]
%onnx::Conv_1133[FLOAT, 256x512x1x1]
%onnx::Conv_1136[FLOAT, 256x256x1x1]
%onnx::Conv_1139[FLOAT, 256x256x1x1]
%onnx::Conv_1142[FLOAT, 256x512x1x1]
%onnx::Conv_1145[FLOAT, 256x256x1x1]
%onnx::Conv_1148[FLOAT, 256x512x1x1]
%onnx::Conv_1151[FLOAT, 256x256x3x3]
%onnx::Conv_1154[FLOAT, 256x512x1x1]
%onnx::Conv_1157[FLOAT, 256x256x1x1]
%onnx::Conv_1160[FLOAT, 256x256x1x1]
%onnx::Conv_1163[FLOAT, 256x512x1x1]
%onnx::Conv_1166[FLOAT, 256x256x1x1]
) {
%onnx::Conv_1167 = Identity(%onnx::Conv_1107)
%onnx::Conv_1164 = Identity(%onnx::Conv_1107)
%onnx::Conv_1161 = Identity(%onnx::Conv_1107)
%onnx::Conv_1158 = Identity(%onnx::Conv_1107)
%onnx::Conv_1155 = Identity(%onnx::Conv_1107)
%onnx::Conv_1152 = Identity(%onnx::Conv_1107)
%onnx::Conv_1149 = Identity(%onnx::Conv_1107)
%onnx::Conv_1146 = Identity(%onnx::Conv_1107)
%onnx::Conv_1143 = Identity(%onnx::Conv_1107)
%onnx::Conv_1140 = Identity(%onnx::Conv_1107)
%onnx::Conv_1137 = Identity(%onnx::Conv_1107)
%onnx::Conv_1134 = Identity(%onnx::Conv_1107)
%onnx::Conv_1131 = Identity(%onnx::Conv_1107)
%onnx::Conv_1128 = Identity(%onnx::Conv_1107)
%onnx::Conv_1125 = Identity(%onnx::Conv_1107)
%onnx::Conv_1122 = Identity(%onnx::Conv_1107)
%onnx::Conv_1119 = Identity(%onnx::Conv_1107)
%onnx::Conv_1116 = Identity(%onnx::Conv_1107)
%onnx::Conv_1113 = Identity(%onnx::Conv_1107)
%onnx::Conv_1110 = Identity(%onnx::Conv_1107)
%onnx::Conv_1104 = Identity(%onnx::Conv_978)
%onnx::Conv_1101 = Identity(%onnx::Conv_978)
%onnx::Conv_1098 = Identity(%onnx::Conv_978)
%onnx::Conv_1095 = Identity(%onnx::Conv_978)
%onnx::Conv_1092 = Identity(%onnx::Conv_978)
%onnx::Conv_1089 = Identity(%onnx::Conv_978)
%onnx::Conv_1086 = Identity(%onnx::Conv_978)
%onnx::Conv_1083 = Identity(%onnx::Conv_978)
%onnx::Conv_1080 = Identity(%onnx::Conv_978)
%onnx::Conv_1077 = Identity(%onnx::Conv_978)
%onnx::Conv_1074 = Identity(%onnx::Conv_978)
%onnx::Conv_1071 = Identity(%onnx::Conv_978)
%onnx::Conv_1068 = Identity(%onnx::Conv_978)
%onnx::Conv_1065 = Identity(%onnx::Conv_978)
%onnx::Conv_1062 = Identity(%onnx::Conv_978)
%onnx::Conv_1059 = Identity(%onnx::Conv_978)
%onnx::Conv_1056 = Identity(%onnx::Conv_978)
%onnx::Conv_1053 = Identity(%onnx::Conv_978)
%onnx::Conv_1050 = Identity(%onnx::Conv_978)
%onnx::Conv_1047 = Identity(%onnx::Conv_978)
%onnx::Conv_1044 = Identity(%onnx::Conv_978)
%onnx::Conv_1041 = Identity(%onnx::Conv_981)
%onnx::Conv_1038 = Identity(%onnx::Conv_981)
%onnx::Conv_1035 = Identity(%onnx::Conv_981)
%onnx::Conv_1032 = Identity(%onnx::Conv_981)
%onnx::Conv_1029 = Identity(%onnx::Conv_981)
%onnx::Conv_1026 = Identity(%onnx::Conv_981)
%onnx::Conv_1023 = Identity(%onnx::Conv_981)
%onnx::Conv_1020 = Identity(%onnx::Conv_981)
%onnx::Conv_1017 = Identity(%onnx::Conv_981)
%onnx::Conv_1014 = Identity(%onnx::Conv_981)
%onnx::Conv_1011 = Identity(%onnx::Conv_981)
%onnx::Conv_1008 = Identity(%onnx::Conv_981)
%onnx::Conv_1005 = Identity(%onnx::Conv_981)
%onnx::Conv_1002 = Identity(%onnx::Conv_981)
%onnx::Conv_999 = Identity(%onnx::Conv_981)
%onnx::Conv_996 = Identity(%onnx::Conv_981)
%onnx::Conv_993 = Identity(%onnx::Conv_981)
%onnx::Conv_990 = Identity(%onnx::Conv_981)
%onnx::Conv_987 = Identity(%onnx::Conv_981)
%onnx::Conv_984 = Identity(%onnx::Conv_981)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_977, %onnx::Conv_978)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%975 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %975
}
|
val_accuracy
| 92.197514
| 1,336,027,136
| 4,426,762
|
{'zcp_epe_nas': 90.6821754873416, 'zcp_fisher': 49.40003967285156, 'zcp_flops': 21376434176.0, 'zcp_grad_norm': 174.90313720703125, 'zcp_grasp': -160.1650390625, 'zcp_jacov': -16.05031199315055, 'zcp_l2_norm': 1190.801025390625, 'zcp_nwot': 227.2030698275614, 'zcp_params': 4426762.0, 'zcp_plain': 0.08593413978815001, 'zcp_snip': 982.139404296875, 'zcp_synflow': 97.74994034172309, 'zcp_zen': 99.66305541992188, 'zcp_val_accuracy': 0.9324919581413261}
| |
NASBench101_162067
|
NASBench101
|
162067
|
62254ab2db208584ffba3b8d924c57f8
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_1085[FLOAT, 128x3x3x3]
%onnx::Conv_1086[FLOAT, 128]
%onnx::Conv_1088[FLOAT, 128x128x1x1]
%onnx::Conv_1091[FLOAT, 128x128x1x1]
%onnx::Conv_1094[FLOAT, 128x128x1x1]
%onnx::Conv_1097[FLOAT, 128x128x3x3]
%onnx::Conv_1100[FLOAT, 128x128x1x1]
%onnx::Conv_1103[FLOAT, 128x128x1x1]
%onnx::Conv_1106[FLOAT, 128x128x3x3]
%onnx::Conv_1109[FLOAT, 128x128x1x1]
%onnx::Conv_1112[FLOAT, 128x128x1x1]
%onnx::Conv_1115[FLOAT, 128x128x1x1]
%onnx::Conv_1118[FLOAT, 128x128x1x1]
%onnx::Conv_1121[FLOAT, 128x128x3x3]
%onnx::Conv_1124[FLOAT, 128x128x1x1]
%onnx::Conv_1127[FLOAT, 128x128x1x1]
%onnx::Conv_1130[FLOAT, 128x128x3x3]
%onnx::Conv_1133[FLOAT, 128x128x1x1]
%onnx::Conv_1136[FLOAT, 128x128x1x1]
%onnx::Conv_1139[FLOAT, 128x128x1x1]
%onnx::Conv_1142[FLOAT, 128x128x1x1]
%onnx::Conv_1145[FLOAT, 128x128x3x3]
%onnx::Conv_1148[FLOAT, 128x128x1x1]
%onnx::Conv_1151[FLOAT, 128x128x1x1]
%onnx::Conv_1154[FLOAT, 128x128x3x3]
%onnx::Conv_1157[FLOAT, 128x128x1x1]
%onnx::Conv_1160[FLOAT, 256x128x1x1]
%onnx::Conv_1161[FLOAT, 256]
%onnx::Conv_1163[FLOAT, 256x256x1x1]
%onnx::Conv_1166[FLOAT, 256x128x1x1]
%onnx::Conv_1169[FLOAT, 256x256x3x3]
%onnx::Conv_1172[FLOAT, 256x128x1x1]
%onnx::Conv_1175[FLOAT, 256x256x1x1]
%onnx::Conv_1178[FLOAT, 256x256x3x3]
%onnx::Conv_1181[FLOAT, 256x128x1x1]
%onnx::Conv_1184[FLOAT, 256x256x1x1]
%onnx::Conv_1187[FLOAT, 256x256x1x1]
%onnx::Conv_1190[FLOAT, 256x256x1x1]
%onnx::Conv_1193[FLOAT, 256x256x3x3]
%onnx::Conv_1196[FLOAT, 256x256x1x1]
%onnx::Conv_1199[FLOAT, 256x256x1x1]
%onnx::Conv_1202[FLOAT, 256x256x3x3]
%onnx::Conv_1205[FLOAT, 256x256x1x1]
%onnx::Conv_1208[FLOAT, 256x256x1x1]
%onnx::Conv_1211[FLOAT, 256x256x1x1]
%onnx::Conv_1214[FLOAT, 256x256x1x1]
%onnx::Conv_1217[FLOAT, 256x256x3x3]
%onnx::Conv_1220[FLOAT, 256x256x1x1]
%onnx::Conv_1223[FLOAT, 256x256x1x1]
%onnx::Conv_1226[FLOAT, 256x256x3x3]
%onnx::Conv_1229[FLOAT, 256x256x1x1]
%onnx::Conv_1232[FLOAT, 512x256x1x1]
%onnx::Conv_1233[FLOAT, 512]
%onnx::Conv_1235[FLOAT, 512x512x1x1]
%onnx::Conv_1238[FLOAT, 512x256x1x1]
%onnx::Conv_1241[FLOAT, 512x512x3x3]
%onnx::Conv_1244[FLOAT, 512x256x1x1]
%onnx::Conv_1247[FLOAT, 512x512x1x1]
%onnx::Conv_1250[FLOAT, 512x512x3x3]
%onnx::Conv_1253[FLOAT, 512x256x1x1]
%onnx::Conv_1256[FLOAT, 512x512x1x1]
%onnx::Conv_1259[FLOAT, 512x512x1x1]
%onnx::Conv_1262[FLOAT, 512x512x1x1]
%onnx::Conv_1265[FLOAT, 512x512x3x3]
%onnx::Conv_1268[FLOAT, 512x512x1x1]
%onnx::Conv_1271[FLOAT, 512x512x1x1]
%onnx::Conv_1274[FLOAT, 512x512x3x3]
%onnx::Conv_1277[FLOAT, 512x512x1x1]
%onnx::Conv_1280[FLOAT, 512x512x1x1]
%onnx::Conv_1283[FLOAT, 512x512x1x1]
%onnx::Conv_1286[FLOAT, 512x512x1x1]
%onnx::Conv_1289[FLOAT, 512x512x3x3]
%onnx::Conv_1292[FLOAT, 512x512x1x1]
%onnx::Conv_1295[FLOAT, 512x512x1x1]
%onnx::Conv_1298[FLOAT, 512x512x3x3]
%onnx::Conv_1301[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1302 = Identity(%onnx::Conv_1233)
%onnx::Conv_1299 = Identity(%onnx::Conv_1233)
%onnx::Conv_1296 = Identity(%onnx::Conv_1233)
%onnx::Conv_1293 = Identity(%onnx::Conv_1233)
%onnx::Conv_1290 = Identity(%onnx::Conv_1233)
%onnx::Conv_1287 = Identity(%onnx::Conv_1233)
%onnx::Conv_1284 = Identity(%onnx::Conv_1233)
%onnx::Conv_1281 = Identity(%onnx::Conv_1233)
%onnx::Conv_1278 = Identity(%onnx::Conv_1233)
%onnx::Conv_1275 = Identity(%onnx::Conv_1233)
%onnx::Conv_1272 = Identity(%onnx::Conv_1233)
%onnx::Conv_1269 = Identity(%onnx::Conv_1233)
%onnx::Conv_1266 = Identity(%onnx::Conv_1233)
%onnx::Conv_1263 = Identity(%onnx::Conv_1233)
%onnx::Conv_1260 = Identity(%onnx::Conv_1233)
%onnx::Conv_1257 = Identity(%onnx::Conv_1233)
%onnx::Conv_1254 = Identity(%onnx::Conv_1233)
%onnx::Conv_1251 = Identity(%onnx::Conv_1233)
%onnx::Conv_1248 = Identity(%onnx::Conv_1233)
%onnx::Conv_1245 = Identity(%onnx::Conv_1233)
%onnx::Conv_1242 = Identity(%onnx::Conv_1233)
%onnx::Conv_1239 = Identity(%onnx::Conv_1233)
%onnx::Conv_1236 = Identity(%onnx::Conv_1233)
%onnx::Conv_1230 = Identity(%onnx::Conv_1161)
%onnx::Conv_1227 = Identity(%onnx::Conv_1161)
%onnx::Conv_1224 = Identity(%onnx::Conv_1161)
%onnx::Conv_1221 = Identity(%onnx::Conv_1161)
%onnx::Conv_1218 = Identity(%onnx::Conv_1161)
%onnx::Conv_1215 = Identity(%onnx::Conv_1161)
%onnx::Conv_1212 = Identity(%onnx::Conv_1161)
%onnx::Conv_1209 = Identity(%onnx::Conv_1161)
%onnx::Conv_1206 = Identity(%onnx::Conv_1161)
%onnx::Conv_1203 = Identity(%onnx::Conv_1161)
%onnx::Conv_1200 = Identity(%onnx::Conv_1161)
%onnx::Conv_1197 = Identity(%onnx::Conv_1161)
%onnx::Conv_1194 = Identity(%onnx::Conv_1161)
%onnx::Conv_1191 = Identity(%onnx::Conv_1161)
%onnx::Conv_1188 = Identity(%onnx::Conv_1161)
%onnx::Conv_1185 = Identity(%onnx::Conv_1161)
%onnx::Conv_1182 = Identity(%onnx::Conv_1161)
%onnx::Conv_1179 = Identity(%onnx::Conv_1161)
%onnx::Conv_1176 = Identity(%onnx::Conv_1161)
%onnx::Conv_1173 = Identity(%onnx::Conv_1161)
%onnx::Conv_1170 = Identity(%onnx::Conv_1161)
%onnx::Conv_1167 = Identity(%onnx::Conv_1161)
%onnx::Conv_1164 = Identity(%onnx::Conv_1161)
%onnx::Conv_1158 = Identity(%onnx::Conv_1086)
%onnx::Conv_1155 = Identity(%onnx::Conv_1086)
%onnx::Conv_1152 = Identity(%onnx::Conv_1086)
%onnx::Conv_1149 = Identity(%onnx::Conv_1086)
%onnx::Conv_1146 = Identity(%onnx::Conv_1086)
%onnx::Conv_1143 = Identity(%onnx::Conv_1086)
%onnx::Conv_1140 = Identity(%onnx::Conv_1086)
%onnx::Conv_1137 = Identity(%onnx::Conv_1086)
%onnx::Conv_1134 = Identity(%onnx::Conv_1086)
%onnx::Conv_1131 = Identity(%onnx::Conv_1086)
%onnx::Conv_1128 = Identity(%onnx::Conv_1086)
%onnx::Conv_1125 = Identity(%onnx::Conv_1086)
%onnx::Conv_1122 = Identity(%onnx::Conv_1086)
%onnx::Conv_1119 = Identity(%onnx::Conv_1086)
%onnx::Conv_1116 = Identity(%onnx::Conv_1086)
%onnx::Conv_1113 = Identity(%onnx::Conv_1086)
%onnx::Conv_1110 = Identity(%onnx::Conv_1086)
%onnx::Conv_1107 = Identity(%onnx::Conv_1086)
%onnx::Conv_1104 = Identity(%onnx::Conv_1086)
%onnx::Conv_1101 = Identity(%onnx::Conv_1086)
%onnx::Conv_1098 = Identity(%onnx::Conv_1086)
%onnx::Conv_1095 = Identity(%onnx::Conv_1086)
%onnx::Conv_1092 = Identity(%onnx::Conv_1086)
%onnx::Conv_1089 = Identity(%onnx::Conv_1086)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_7_output_0 = Add(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_7_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_7_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_7_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_7_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_7_output_0 = Add(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_7_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_7_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_7_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_7_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_7_output_0 = Add(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_7_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1169, %onnx::Conv_1170)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1172, %onnx::Conv_1173)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1175, %onnx::Conv_1176)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1178, %onnx::Conv_1179)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1181, %onnx::Conv_1182)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_7_output_0 = Add(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_7_output_0, %onnx::Conv_1184, %onnx::Conv_1185)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1187, %onnx::Conv_1188)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_7_output_0, %onnx::Conv_1190, %onnx::Conv_1191)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1193, %onnx::Conv_1194)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_7_output_0, %onnx::Conv_1196, %onnx::Conv_1197)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1199, %onnx::Conv_1200)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1202, %onnx::Conv_1203)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_7_output_0, %onnx::Conv_1205, %onnx::Conv_1206)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_7_output_0 = Add(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_7_output_0, %onnx::Conv_1208, %onnx::Conv_1209)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1211, %onnx::Conv_1212)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_7_output_0, %onnx::Conv_1214, %onnx::Conv_1215)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1217, %onnx::Conv_1218)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_7_output_0, %onnx::Conv_1220, %onnx::Conv_1221)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1223, %onnx::Conv_1224)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_1226, %onnx::Conv_1227)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_7_output_0, %onnx::Conv_1229, %onnx::Conv_1230)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_7_output_0 = Add(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_7_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1232, %onnx::Conv_1233)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1235, %onnx::Conv_1236)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1238, %onnx::Conv_1239)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1241, %onnx::Conv_1242)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1244, %onnx::Conv_1245)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1247, %onnx::Conv_1248)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1250, %onnx::Conv_1251)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1253, %onnx::Conv_1254)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_7_output_0 = Add(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_7_output_0, %onnx::Conv_1256, %onnx::Conv_1257)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1259, %onnx::Conv_1260)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_7_output_0, %onnx::Conv_1262, %onnx::Conv_1263)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1265, %onnx::Conv_1266)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_7_output_0, %onnx::Conv_1268, %onnx::Conv_1269)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1271, %onnx::Conv_1272)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1274, %onnx::Conv_1275)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_7_output_0, %onnx::Conv_1277, %onnx::Conv_1278)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_7_output_0 = Add(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_7_output_0, %onnx::Conv_1280, %onnx::Conv_1281)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1283, %onnx::Conv_1284)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_7_output_0, %onnx::Conv_1286, %onnx::Conv_1287)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1289, %onnx::Conv_1290)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_7_output_0, %onnx::Conv_1292, %onnx::Conv_1293)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1295, %onnx::Conv_1296)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_1298, %onnx::Conv_1299)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_7_output_0, %onnx::Conv_1301, %onnx::Conv_1302)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_7_output_0 = Add(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_7_output_0)
%1083 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %1083
}
|
val_accuracy
| 93.940306
| 7,165,716,480
| 24,169,098
|
{'zcp_epe_nas': 132.2920969301219, 'zcp_fisher': 7.085025310516357, 'zcp_flops': 114651463680.0, 'zcp_grad_norm': 56.51588821411133, 'zcp_grasp': 0.7715606689453121, 'zcp_jacov': -16.059085074579606, 'zcp_l2_norm': 1634.02001953125, 'zcp_nwot': 239.2457020774912, 'zcp_params': 24169098.0, 'zcp_plain': -0.031621843576431004, 'zcp_snip': 491.3900451660156, 'zcp_synflow': 107.85172760776831, 'zcp_zen': 143.85556030273438, 'zcp_val_accuracy': 0.909855782985687}
| |
NASBench101_101299
|
NASBench101
|
101299
|
3d4e9a7ecf11809ee0f9c360ce9ea932
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_944[FLOAT, 128x3x3x3]
%onnx::Conv_945[FLOAT, 128]
%onnx::Conv_947[FLOAT, 43x128x1x1]
%onnx::Conv_948[FLOAT, 43]
%onnx::Conv_950[FLOAT, 43x43x1x1]
%onnx::Conv_953[FLOAT, 43x43x3x3]
%onnx::Conv_956[FLOAT, 43x43x1x1]
%onnx::Conv_959[FLOAT, 42x42x3x3]
%onnx::Conv_960[FLOAT, 42]
%onnx::Conv_962[FLOAT, 42x42x1x1]
%onnx::Conv_965[FLOAT, 43x128x1x1]
%onnx::Conv_968[FLOAT, 43x43x1x1]
%onnx::Conv_971[FLOAT, 43x43x3x3]
%onnx::Conv_974[FLOAT, 43x43x1x1]
%onnx::Conv_977[FLOAT, 42x42x3x3]
%onnx::Conv_980[FLOAT, 42x42x1x1]
%onnx::Conv_983[FLOAT, 43x128x1x1]
%onnx::Conv_986[FLOAT, 43x43x1x1]
%onnx::Conv_989[FLOAT, 43x43x3x3]
%onnx::Conv_992[FLOAT, 43x43x1x1]
%onnx::Conv_995[FLOAT, 42x42x3x3]
%onnx::Conv_998[FLOAT, 42x42x1x1]
%onnx::Conv_1001[FLOAT, 86x128x1x1]
%onnx::Conv_1002[FLOAT, 86]
%onnx::Conv_1004[FLOAT, 86x86x1x1]
%onnx::Conv_1007[FLOAT, 86x86x3x3]
%onnx::Conv_1010[FLOAT, 85x85x1x1]
%onnx::Conv_1011[FLOAT, 85]
%onnx::Conv_1013[FLOAT, 85x85x3x3]
%onnx::Conv_1016[FLOAT, 85x85x1x1]
%onnx::Conv_1019[FLOAT, 86x256x1x1]
%onnx::Conv_1022[FLOAT, 86x86x1x1]
%onnx::Conv_1025[FLOAT, 86x86x3x3]
%onnx::Conv_1028[FLOAT, 85x85x1x1]
%onnx::Conv_1031[FLOAT, 85x85x3x3]
%onnx::Conv_1034[FLOAT, 85x85x1x1]
%onnx::Conv_1037[FLOAT, 86x256x1x1]
%onnx::Conv_1040[FLOAT, 86x86x1x1]
%onnx::Conv_1043[FLOAT, 86x86x3x3]
%onnx::Conv_1046[FLOAT, 85x85x1x1]
%onnx::Conv_1049[FLOAT, 85x85x3x3]
%onnx::Conv_1052[FLOAT, 85x85x1x1]
%onnx::Conv_1055[FLOAT, 171x256x1x1]
%onnx::Conv_1056[FLOAT, 171]
%onnx::Conv_1058[FLOAT, 171x171x1x1]
%onnx::Conv_1061[FLOAT, 171x171x3x3]
%onnx::Conv_1064[FLOAT, 171x171x1x1]
%onnx::Conv_1067[FLOAT, 170x170x3x3]
%onnx::Conv_1068[FLOAT, 170]
%onnx::Conv_1070[FLOAT, 170x170x1x1]
%onnx::Conv_1073[FLOAT, 171x512x1x1]
%onnx::Conv_1076[FLOAT, 171x171x1x1]
%onnx::Conv_1079[FLOAT, 171x171x3x3]
%onnx::Conv_1082[FLOAT, 171x171x1x1]
%onnx::Conv_1085[FLOAT, 170x170x3x3]
%onnx::Conv_1088[FLOAT, 170x170x1x1]
%onnx::Conv_1091[FLOAT, 171x512x1x1]
%onnx::Conv_1094[FLOAT, 171x171x1x1]
%onnx::Conv_1097[FLOAT, 171x171x3x3]
%onnx::Conv_1100[FLOAT, 171x171x1x1]
%onnx::Conv_1103[FLOAT, 170x170x3x3]
%onnx::Conv_1106[FLOAT, 170x170x1x1]
) {
%onnx::Conv_1107 = Identity(%onnx::Conv_1068)
%onnx::Conv_1104 = Identity(%onnx::Conv_1068)
%onnx::Conv_1101 = Identity(%onnx::Conv_1056)
%onnx::Conv_1098 = Identity(%onnx::Conv_1056)
%onnx::Conv_1095 = Identity(%onnx::Conv_1056)
%onnx::Conv_1092 = Identity(%onnx::Conv_1056)
%onnx::Conv_1089 = Identity(%onnx::Conv_1068)
%onnx::Conv_1086 = Identity(%onnx::Conv_1068)
%onnx::Conv_1083 = Identity(%onnx::Conv_1056)
%onnx::Conv_1080 = Identity(%onnx::Conv_1056)
%onnx::Conv_1077 = Identity(%onnx::Conv_1056)
%onnx::Conv_1074 = Identity(%onnx::Conv_1056)
%onnx::Conv_1071 = Identity(%onnx::Conv_1068)
%onnx::Conv_1065 = Identity(%onnx::Conv_1056)
%onnx::Conv_1062 = Identity(%onnx::Conv_1056)
%onnx::Conv_1059 = Identity(%onnx::Conv_1056)
%onnx::Conv_1053 = Identity(%onnx::Conv_1011)
%onnx::Conv_1050 = Identity(%onnx::Conv_1011)
%onnx::Conv_1047 = Identity(%onnx::Conv_1011)
%onnx::Conv_1044 = Identity(%onnx::Conv_1002)
%onnx::Conv_1041 = Identity(%onnx::Conv_1002)
%onnx::Conv_1038 = Identity(%onnx::Conv_1002)
%onnx::Conv_1035 = Identity(%onnx::Conv_1011)
%onnx::Conv_1032 = Identity(%onnx::Conv_1011)
%onnx::Conv_1029 = Identity(%onnx::Conv_1011)
%onnx::Conv_1026 = Identity(%onnx::Conv_1002)
%onnx::Conv_1023 = Identity(%onnx::Conv_1002)
%onnx::Conv_1020 = Identity(%onnx::Conv_1002)
%onnx::Conv_1017 = Identity(%onnx::Conv_1011)
%onnx::Conv_1014 = Identity(%onnx::Conv_1011)
%onnx::Conv_1008 = Identity(%onnx::Conv_1002)
%onnx::Conv_1005 = Identity(%onnx::Conv_1002)
%onnx::Conv_999 = Identity(%onnx::Conv_960)
%onnx::Conv_996 = Identity(%onnx::Conv_960)
%onnx::Conv_993 = Identity(%onnx::Conv_948)
%onnx::Conv_990 = Identity(%onnx::Conv_948)
%onnx::Conv_987 = Identity(%onnx::Conv_948)
%onnx::Conv_984 = Identity(%onnx::Conv_948)
%onnx::Conv_981 = Identity(%onnx::Conv_960)
%onnx::Conv_978 = Identity(%onnx::Conv_960)
%onnx::Conv_975 = Identity(%onnx::Conv_948)
%onnx::Conv_972 = Identity(%onnx::Conv_948)
%onnx::Conv_969 = Identity(%onnx::Conv_948)
%onnx::Conv_966 = Identity(%onnx::Conv_948)
%onnx::Conv_963 = Identity(%onnx::Conv_960)
%onnx::Conv_957 = Identity(%onnx::Conv_948)
%onnx::Conv_954 = Identity(%onnx::Conv_948)
%onnx::Conv_951 = Identity(%onnx::Conv_948)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_944, %onnx::Conv_945)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_6_output_0)
%/layers.1/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_7_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_1_output_0 = Slice(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_9_output_0, %/layers.1/Constant_10_output_0, %/layers.1/Constant_8_output_0, %/layers.1/Constant_11_output_0)
%/layers.1/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/Slice_1_output_0, %/layers.1/Constant_12_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_6_output_0)
%/layers.2/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_7_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_1_output_0 = Slice(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_9_output_0, %/layers.2/Constant_10_output_0, %/layers.2/Constant_8_output_0, %/layers.2/Constant_11_output_0)
%/layers.2/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/Slice_1_output_0, %/layers.2/Constant_12_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_6_output_0)
%/layers.3/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_7_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_1_output_0 = Slice(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_9_output_0, %/layers.3/Constant_10_output_0, %/layers.3/Constant_8_output_0, %/layers.3/Constant_11_output_0)
%/layers.3/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/Slice_1_output_0, %/layers.3/Constant_12_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_4_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_7_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_8_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_4_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_7_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_8_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_4_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_7_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_8_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_6_output_0)
%/layers.9/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_7_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_1_output_0 = Slice(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_9_output_0, %/layers.9/Constant_10_output_0, %/layers.9/Constant_8_output_0, %/layers.9/Constant_11_output_0)
%/layers.9/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/Slice_1_output_0, %/layers.9/Constant_12_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_6_output_0)
%/layers.10/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_7_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_1_output_0 = Slice(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_9_output_0, %/layers.10/Constant_10_output_0, %/layers.10/Constant_8_output_0, %/layers.10/Constant_11_output_0)
%/layers.10/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/Slice_1_output_0, %/layers.10/Constant_12_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_6_output_0)
%/layers.11/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_7_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_1_output_0 = Slice(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_9_output_0, %/layers.11/Constant_10_output_0, %/layers.11/Constant_8_output_0, %/layers.11/Constant_11_output_0)
%/layers.11/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/Slice_1_output_0, %/layers.11/Constant_12_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%942 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %942
}
|
val_accuracy
| 90.925479
| 812,675,712
| 2,716,227
|
{'zcp_epe_nas': 80.49108552434932, 'zcp_fisher': 431.3636474609375, 'zcp_flops': 13002811392.0, 'zcp_grad_norm': 414.671630859375, 'zcp_grasp': -1000.9375, 'zcp_jacov': -16.07754877082074, 'zcp_l2_norm': 810.8551635742188, 'zcp_nwot': 218.79452870701766, 'zcp_params': 2716227.0, 'zcp_plain': 0.0009858608245840001, 'zcp_snip': 1702.2515869140625, 'zcp_synflow': 152.0127780918586, 'zcp_zen': 82.76740264892578, 'zcp_val_accuracy': 0.909054458141326}
| |
NASBench101_134517
|
NASBench101
|
134517
|
5157ef72d438e690c26f05ca6c3d7834
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_671[FLOAT, 128x3x3x3]
%onnx::Conv_672[FLOAT, 128]
%onnx::Conv_674[FLOAT, 64x128x1x1]
%onnx::Conv_675[FLOAT, 64]
%onnx::Conv_677[FLOAT, 64x64x1x1]
%onnx::Conv_680[FLOAT, 64x64x1x1]
%onnx::Conv_683[FLOAT, 64x64x1x1]
%onnx::Conv_686[FLOAT, 64x128x1x1]
%onnx::Conv_689[FLOAT, 64x64x1x1]
%onnx::Conv_692[FLOAT, 64x64x1x1]
%onnx::Conv_695[FLOAT, 64x64x1x1]
%onnx::Conv_698[FLOAT, 64x128x1x1]
%onnx::Conv_701[FLOAT, 64x64x1x1]
%onnx::Conv_704[FLOAT, 64x64x1x1]
%onnx::Conv_707[FLOAT, 64x64x1x1]
%onnx::Conv_710[FLOAT, 128x128x1x1]
%onnx::Conv_713[FLOAT, 128x128x1x1]
%onnx::Conv_716[FLOAT, 128x128x1x1]
%onnx::Conv_719[FLOAT, 128x128x1x1]
%onnx::Conv_722[FLOAT, 128x256x1x1]
%onnx::Conv_725[FLOAT, 128x128x1x1]
%onnx::Conv_728[FLOAT, 128x128x1x1]
%onnx::Conv_731[FLOAT, 128x128x1x1]
%onnx::Conv_734[FLOAT, 128x256x1x1]
%onnx::Conv_737[FLOAT, 128x128x1x1]
%onnx::Conv_740[FLOAT, 128x128x1x1]
%onnx::Conv_743[FLOAT, 128x128x1x1]
%onnx::Conv_746[FLOAT, 256x256x1x1]
%onnx::Conv_747[FLOAT, 256]
%onnx::Conv_749[FLOAT, 256x256x1x1]
%onnx::Conv_752[FLOAT, 256x256x1x1]
%onnx::Conv_755[FLOAT, 256x256x1x1]
%onnx::Conv_758[FLOAT, 256x512x1x1]
%onnx::Conv_761[FLOAT, 256x256x1x1]
%onnx::Conv_764[FLOAT, 256x256x1x1]
%onnx::Conv_767[FLOAT, 256x256x1x1]
%onnx::Conv_770[FLOAT, 256x512x1x1]
%onnx::Conv_773[FLOAT, 256x256x1x1]
%onnx::Conv_776[FLOAT, 256x256x1x1]
%onnx::Conv_779[FLOAT, 256x256x1x1]
) {
%onnx::Conv_780 = Identity(%onnx::Conv_747)
%onnx::Conv_777 = Identity(%onnx::Conv_747)
%onnx::Conv_774 = Identity(%onnx::Conv_747)
%onnx::Conv_771 = Identity(%onnx::Conv_747)
%onnx::Conv_768 = Identity(%onnx::Conv_747)
%onnx::Conv_765 = Identity(%onnx::Conv_747)
%onnx::Conv_762 = Identity(%onnx::Conv_747)
%onnx::Conv_759 = Identity(%onnx::Conv_747)
%onnx::Conv_756 = Identity(%onnx::Conv_747)
%onnx::Conv_753 = Identity(%onnx::Conv_747)
%onnx::Conv_750 = Identity(%onnx::Conv_747)
%onnx::Conv_744 = Identity(%onnx::Conv_672)
%onnx::Conv_741 = Identity(%onnx::Conv_672)
%onnx::Conv_738 = Identity(%onnx::Conv_672)
%onnx::Conv_735 = Identity(%onnx::Conv_672)
%onnx::Conv_732 = Identity(%onnx::Conv_672)
%onnx::Conv_729 = Identity(%onnx::Conv_672)
%onnx::Conv_726 = Identity(%onnx::Conv_672)
%onnx::Conv_723 = Identity(%onnx::Conv_672)
%onnx::Conv_720 = Identity(%onnx::Conv_672)
%onnx::Conv_717 = Identity(%onnx::Conv_672)
%onnx::Conv_714 = Identity(%onnx::Conv_672)
%onnx::Conv_711 = Identity(%onnx::Conv_672)
%onnx::Conv_708 = Identity(%onnx::Conv_675)
%onnx::Conv_705 = Identity(%onnx::Conv_675)
%onnx::Conv_702 = Identity(%onnx::Conv_675)
%onnx::Conv_699 = Identity(%onnx::Conv_675)
%onnx::Conv_696 = Identity(%onnx::Conv_675)
%onnx::Conv_693 = Identity(%onnx::Conv_675)
%onnx::Conv_690 = Identity(%onnx::Conv_675)
%onnx::Conv_687 = Identity(%onnx::Conv_675)
%onnx::Conv_684 = Identity(%onnx::Conv_675)
%onnx::Conv_681 = Identity(%onnx::Conv_675)
%onnx::Conv_678 = Identity(%onnx::Conv_675)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_671, %onnx::Conv_672)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%669 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %669
}
|
val_accuracy
| 76.091748
| 379,856,896
| 1,227,914
|
{'zcp_epe_nas': 116.21608303398767, 'zcp_fisher': 3387.126708984375, 'zcp_flops': 6077710336.0, 'zcp_grad_norm': 1094.9932861328125, 'zcp_grasp': 17059.25, 'zcp_jacov': -16.05614060712403, 'zcp_l2_norm': 648.2716064453125, 'zcp_nwot': 218.74014632691933, 'zcp_params': 1227914.0, 'zcp_plain': -0.038588356226682004, 'zcp_snip': 4872.97705078125, 'zcp_synflow': 104.09623165661641, 'zcp_zen': 54.3421516418457, 'zcp_val_accuracy': 0.8901242017745971}
| |
NASBench101_251814
|
NASBench101
|
251814
|
9875a6e11ac9253bab2e5fda83472d93
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_869[FLOAT, 128x3x3x3]
%onnx::Conv_870[FLOAT, 128]
%onnx::Conv_872[FLOAT, 43x128x1x1]
%onnx::Conv_873[FLOAT, 43]
%onnx::Conv_875[FLOAT, 43x43x3x3]
%onnx::Conv_878[FLOAT, 43x43x3x3]
%onnx::Conv_881[FLOAT, 43x43x1x1]
%onnx::Conv_884[FLOAT, 42x42x1x1]
%onnx::Conv_885[FLOAT, 42]
%onnx::Conv_887[FLOAT, 43x128x1x1]
%onnx::Conv_890[FLOAT, 43x43x3x3]
%onnx::Conv_893[FLOAT, 43x43x3x3]
%onnx::Conv_896[FLOAT, 43x43x1x1]
%onnx::Conv_899[FLOAT, 42x42x1x1]
%onnx::Conv_902[FLOAT, 43x128x1x1]
%onnx::Conv_905[FLOAT, 43x43x3x3]
%onnx::Conv_908[FLOAT, 43x43x3x3]
%onnx::Conv_911[FLOAT, 43x43x1x1]
%onnx::Conv_914[FLOAT, 42x42x1x1]
%onnx::Conv_917[FLOAT, 86x128x1x1]
%onnx::Conv_918[FLOAT, 86]
%onnx::Conv_920[FLOAT, 86x86x3x3]
%onnx::Conv_923[FLOAT, 85x85x3x3]
%onnx::Conv_924[FLOAT, 85]
%onnx::Conv_926[FLOAT, 85x85x1x1]
%onnx::Conv_929[FLOAT, 85x85x1x1]
%onnx::Conv_932[FLOAT, 86x256x1x1]
%onnx::Conv_935[FLOAT, 86x86x3x3]
%onnx::Conv_938[FLOAT, 85x85x3x3]
%onnx::Conv_941[FLOAT, 85x85x1x1]
%onnx::Conv_944[FLOAT, 85x85x1x1]
%onnx::Conv_947[FLOAT, 86x256x1x1]
%onnx::Conv_950[FLOAT, 86x86x3x3]
%onnx::Conv_953[FLOAT, 85x85x3x3]
%onnx::Conv_956[FLOAT, 85x85x1x1]
%onnx::Conv_959[FLOAT, 85x85x1x1]
%onnx::Conv_962[FLOAT, 171x256x1x1]
%onnx::Conv_963[FLOAT, 171]
%onnx::Conv_965[FLOAT, 171x171x3x3]
%onnx::Conv_968[FLOAT, 171x171x3x3]
%onnx::Conv_971[FLOAT, 171x171x1x1]
%onnx::Conv_974[FLOAT, 170x170x1x1]
%onnx::Conv_975[FLOAT, 170]
%onnx::Conv_977[FLOAT, 171x512x1x1]
%onnx::Conv_980[FLOAT, 171x171x3x3]
%onnx::Conv_983[FLOAT, 171x171x3x3]
%onnx::Conv_986[FLOAT, 171x171x1x1]
%onnx::Conv_989[FLOAT, 170x170x1x1]
%onnx::Conv_992[FLOAT, 171x512x1x1]
%onnx::Conv_995[FLOAT, 171x171x3x3]
%onnx::Conv_998[FLOAT, 171x171x3x3]
%onnx::Conv_1001[FLOAT, 171x171x1x1]
%onnx::Conv_1004[FLOAT, 170x170x1x1]
) {
%onnx::Conv_1005 = Identity(%onnx::Conv_975)
%onnx::Conv_1002 = Identity(%onnx::Conv_963)
%onnx::Conv_999 = Identity(%onnx::Conv_963)
%onnx::Conv_996 = Identity(%onnx::Conv_963)
%onnx::Conv_993 = Identity(%onnx::Conv_963)
%onnx::Conv_990 = Identity(%onnx::Conv_975)
%onnx::Conv_987 = Identity(%onnx::Conv_963)
%onnx::Conv_984 = Identity(%onnx::Conv_963)
%onnx::Conv_981 = Identity(%onnx::Conv_963)
%onnx::Conv_978 = Identity(%onnx::Conv_963)
%onnx::Conv_972 = Identity(%onnx::Conv_963)
%onnx::Conv_969 = Identity(%onnx::Conv_963)
%onnx::Conv_966 = Identity(%onnx::Conv_963)
%onnx::Conv_960 = Identity(%onnx::Conv_924)
%onnx::Conv_957 = Identity(%onnx::Conv_924)
%onnx::Conv_954 = Identity(%onnx::Conv_924)
%onnx::Conv_951 = Identity(%onnx::Conv_918)
%onnx::Conv_948 = Identity(%onnx::Conv_918)
%onnx::Conv_945 = Identity(%onnx::Conv_924)
%onnx::Conv_942 = Identity(%onnx::Conv_924)
%onnx::Conv_939 = Identity(%onnx::Conv_924)
%onnx::Conv_936 = Identity(%onnx::Conv_918)
%onnx::Conv_933 = Identity(%onnx::Conv_918)
%onnx::Conv_930 = Identity(%onnx::Conv_924)
%onnx::Conv_927 = Identity(%onnx::Conv_924)
%onnx::Conv_921 = Identity(%onnx::Conv_918)
%onnx::Conv_915 = Identity(%onnx::Conv_885)
%onnx::Conv_912 = Identity(%onnx::Conv_873)
%onnx::Conv_909 = Identity(%onnx::Conv_873)
%onnx::Conv_906 = Identity(%onnx::Conv_873)
%onnx::Conv_903 = Identity(%onnx::Conv_873)
%onnx::Conv_900 = Identity(%onnx::Conv_885)
%onnx::Conv_897 = Identity(%onnx::Conv_873)
%onnx::Conv_894 = Identity(%onnx::Conv_873)
%onnx::Conv_891 = Identity(%onnx::Conv_873)
%onnx::Conv_888 = Identity(%onnx::Conv_873)
%onnx::Conv_882 = Identity(%onnx::Conv_873)
%onnx::Conv_879 = Identity(%onnx::Conv_873)
%onnx::Conv_876 = Identity(%onnx::Conv_873)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_869, %onnx::Conv_870)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_6_output_0)
%/layers.1/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_7_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_1_output_0 = Slice(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_9_output_0, %/layers.1/Constant_10_output_0, %/layers.1/Constant_8_output_0, %/layers.1/Constant_11_output_0)
%/layers.1/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/Slice_1_output_0, %/layers.1/Constant_12_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_6_output_0)
%/layers.2/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_7_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_1_output_0 = Slice(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_9_output_0, %/layers.2/Constant_10_output_0, %/layers.2/Constant_8_output_0, %/layers.2/Constant_11_output_0)
%/layers.2/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/Slice_1_output_0, %/layers.2/Constant_12_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_6_output_0)
%/layers.3/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_7_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_1_output_0 = Slice(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_9_output_0, %/layers.3/Constant_10_output_0, %/layers.3/Constant_8_output_0, %/layers.3/Constant_11_output_0)
%/layers.3/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/Slice_1_output_0, %/layers.3/Constant_12_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_1_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_1_output_0 = Slice(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_8_output_0, %/layers.5/Constant_9_output_0, %/layers.5/Constant_7_output_0, %/layers.5/Constant_10_output_0)
%/layers.5/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/Slice_1_output_0, %/layers.5/Constant_11_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_12_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_1_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_1_output_0 = Slice(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_8_output_0, %/layers.6/Constant_9_output_0, %/layers.6/Constant_7_output_0, %/layers.6/Constant_10_output_0)
%/layers.6/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/Slice_1_output_0, %/layers.6/Constant_11_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_12_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_1_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_1_output_0 = Slice(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_8_output_0, %/layers.7/Constant_9_output_0, %/layers.7/Constant_7_output_0, %/layers.7/Constant_10_output_0)
%/layers.7/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/Slice_1_output_0, %/layers.7/Constant_11_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_12_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_6_output_0)
%/layers.9/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_7_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_1_output_0 = Slice(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_9_output_0, %/layers.9/Constant_10_output_0, %/layers.9/Constant_8_output_0, %/layers.9/Constant_11_output_0)
%/layers.9/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/Slice_1_output_0, %/layers.9/Constant_12_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_6_output_0)
%/layers.10/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_7_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_1_output_0 = Slice(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_9_output_0, %/layers.10/Constant_10_output_0, %/layers.10/Constant_8_output_0, %/layers.10/Constant_11_output_0)
%/layers.10/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/Slice_1_output_0, %/layers.10/Constant_12_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_6_output_0)
%/layers.11/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_7_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_1_output_0 = Slice(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_9_output_0, %/layers.11/Constant_10_output_0, %/layers.11/Constant_8_output_0, %/layers.11/Constant_11_output_0)
%/layers.11/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/Slice_1_output_0, %/layers.11/Constant_12_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%867 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %867
}
|
val_accuracy
| 92.23758
| 782,783,616
| 2,610,483
|
{'zcp_epe_nas': 130.19907620376176, 'zcp_fisher': 47.36227798461914, 'zcp_flops': 12524537856.0, 'zcp_grad_norm': 131.84523010253906, 'zcp_grasp': -48.27392578125, 'zcp_jacov': -16.048109129225523, 'zcp_l2_norm': 687.6275024414062, 'zcp_nwot': 215.96394994873685, 'zcp_params': 2610483.0, 'zcp_plain': 0.0010841044131660001, 'zcp_snip': 622.6886596679688, 'zcp_synflow': 131.19682184547705, 'zcp_zen': 75.02478790283203, 'zcp_val_accuracy': 0.902944684028625}
| |
NASBench101_108380
|
NASBench101
|
108380
|
417a1f8942ef795758b760533f62c894
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_770[FLOAT, 128x3x3x3]
%onnx::Conv_771[FLOAT, 128]
%onnx::Conv_773[FLOAT, 64x128x1x1]
%onnx::Conv_774[FLOAT, 64]
%onnx::Conv_776[FLOAT, 64x64x3x3]
%onnx::Conv_779[FLOAT, 64x128x1x1]
%onnx::Conv_782[FLOAT, 64x64x3x3]
%onnx::Conv_785[FLOAT, 64x64x3x3]
%onnx::Conv_788[FLOAT, 64x128x1x1]
%onnx::Conv_791[FLOAT, 64x64x3x3]
%onnx::Conv_794[FLOAT, 64x128x1x1]
%onnx::Conv_797[FLOAT, 64x64x3x3]
%onnx::Conv_800[FLOAT, 64x64x3x3]
%onnx::Conv_803[FLOAT, 64x128x1x1]
%onnx::Conv_806[FLOAT, 64x64x3x3]
%onnx::Conv_809[FLOAT, 64x128x1x1]
%onnx::Conv_812[FLOAT, 64x64x3x3]
%onnx::Conv_815[FLOAT, 64x64x3x3]
%onnx::Conv_818[FLOAT, 128x128x1x1]
%onnx::Conv_821[FLOAT, 128x128x3x3]
%onnx::Conv_824[FLOAT, 128x128x1x1]
%onnx::Conv_827[FLOAT, 128x128x3x3]
%onnx::Conv_830[FLOAT, 128x128x3x3]
%onnx::Conv_833[FLOAT, 128x256x1x1]
%onnx::Conv_836[FLOAT, 128x128x3x3]
%onnx::Conv_839[FLOAT, 128x256x1x1]
%onnx::Conv_842[FLOAT, 128x128x3x3]
%onnx::Conv_845[FLOAT, 128x128x3x3]
%onnx::Conv_848[FLOAT, 128x256x1x1]
%onnx::Conv_851[FLOAT, 128x128x3x3]
%onnx::Conv_854[FLOAT, 128x256x1x1]
%onnx::Conv_857[FLOAT, 128x128x3x3]
%onnx::Conv_860[FLOAT, 128x128x3x3]
%onnx::Conv_863[FLOAT, 256x256x1x1]
%onnx::Conv_864[FLOAT, 256]
%onnx::Conv_866[FLOAT, 256x256x3x3]
%onnx::Conv_869[FLOAT, 256x256x1x1]
%onnx::Conv_872[FLOAT, 256x256x3x3]
%onnx::Conv_875[FLOAT, 256x256x3x3]
%onnx::Conv_878[FLOAT, 256x512x1x1]
%onnx::Conv_881[FLOAT, 256x256x3x3]
%onnx::Conv_884[FLOAT, 256x512x1x1]
%onnx::Conv_887[FLOAT, 256x256x3x3]
%onnx::Conv_890[FLOAT, 256x256x3x3]
%onnx::Conv_893[FLOAT, 256x512x1x1]
%onnx::Conv_896[FLOAT, 256x256x3x3]
%onnx::Conv_899[FLOAT, 256x512x1x1]
%onnx::Conv_902[FLOAT, 256x256x3x3]
%onnx::Conv_905[FLOAT, 256x256x3x3]
) {
%onnx::Conv_906 = Identity(%onnx::Conv_864)
%onnx::Conv_903 = Identity(%onnx::Conv_864)
%onnx::Conv_900 = Identity(%onnx::Conv_864)
%onnx::Conv_897 = Identity(%onnx::Conv_864)
%onnx::Conv_894 = Identity(%onnx::Conv_864)
%onnx::Conv_891 = Identity(%onnx::Conv_864)
%onnx::Conv_888 = Identity(%onnx::Conv_864)
%onnx::Conv_885 = Identity(%onnx::Conv_864)
%onnx::Conv_882 = Identity(%onnx::Conv_864)
%onnx::Conv_879 = Identity(%onnx::Conv_864)
%onnx::Conv_876 = Identity(%onnx::Conv_864)
%onnx::Conv_873 = Identity(%onnx::Conv_864)
%onnx::Conv_870 = Identity(%onnx::Conv_864)
%onnx::Conv_867 = Identity(%onnx::Conv_864)
%onnx::Conv_861 = Identity(%onnx::Conv_771)
%onnx::Conv_858 = Identity(%onnx::Conv_771)
%onnx::Conv_855 = Identity(%onnx::Conv_771)
%onnx::Conv_852 = Identity(%onnx::Conv_771)
%onnx::Conv_849 = Identity(%onnx::Conv_771)
%onnx::Conv_846 = Identity(%onnx::Conv_771)
%onnx::Conv_843 = Identity(%onnx::Conv_771)
%onnx::Conv_840 = Identity(%onnx::Conv_771)
%onnx::Conv_837 = Identity(%onnx::Conv_771)
%onnx::Conv_834 = Identity(%onnx::Conv_771)
%onnx::Conv_831 = Identity(%onnx::Conv_771)
%onnx::Conv_828 = Identity(%onnx::Conv_771)
%onnx::Conv_825 = Identity(%onnx::Conv_771)
%onnx::Conv_822 = Identity(%onnx::Conv_771)
%onnx::Conv_819 = Identity(%onnx::Conv_771)
%onnx::Conv_816 = Identity(%onnx::Conv_774)
%onnx::Conv_813 = Identity(%onnx::Conv_774)
%onnx::Conv_810 = Identity(%onnx::Conv_774)
%onnx::Conv_807 = Identity(%onnx::Conv_774)
%onnx::Conv_804 = Identity(%onnx::Conv_774)
%onnx::Conv_801 = Identity(%onnx::Conv_774)
%onnx::Conv_798 = Identity(%onnx::Conv_774)
%onnx::Conv_795 = Identity(%onnx::Conv_774)
%onnx::Conv_792 = Identity(%onnx::Conv_774)
%onnx::Conv_789 = Identity(%onnx::Conv_774)
%onnx::Conv_786 = Identity(%onnx::Conv_774)
%onnx::Conv_783 = Identity(%onnx::Conv_774)
%onnx::Conv_780 = Identity(%onnx::Conv_774)
%onnx::Conv_777 = Identity(%onnx::Conv_774)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_770, %onnx::Conv_771)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%768 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %768
}
|
val_accuracy
| 91.015625
| 2,328,766,464
| 7,857,930
|
{'zcp_epe_nas': 74.83831924397742, 'zcp_fisher': 54.25736618041992, 'zcp_flops': 37260263424.0, 'zcp_grad_norm': 139.6841278076172, 'zcp_grasp': -2.88916015625, 'zcp_jacov': -16.06017879672553, 'zcp_l2_norm': 844.7086181640625, 'zcp_nwot': 221.47731381986515, 'zcp_params': 7857930.0, 'zcp_plain': 0.106791615486145, 'zcp_snip': 891.7329711914062, 'zcp_synflow': 126.92549142572113, 'zcp_zen': 96.68187713623047, 'zcp_val_accuracy': 0.923577725887298}
| |
NASBench101_232088
|
NASBench101
|
232088
|
8c8662725ce9763a599c018012f895fb
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_923[FLOAT, 128x3x3x3]
%onnx::Conv_924[FLOAT, 128]
%onnx::Conv_926[FLOAT, 43x128x1x1]
%onnx::Conv_927[FLOAT, 43]
%onnx::Conv_929[FLOAT, 43x43x3x3]
%onnx::Conv_932[FLOAT, 43x43x3x3]
%onnx::Conv_935[FLOAT, 43x128x1x1]
%onnx::Conv_938[FLOAT, 43x43x1x1]
%onnx::Conv_941[FLOAT, 43x43x1x1]
%onnx::Conv_944[FLOAT, 43x128x1x1]
%onnx::Conv_947[FLOAT, 43x43x3x3]
%onnx::Conv_950[FLOAT, 43x43x3x3]
%onnx::Conv_953[FLOAT, 43x128x1x1]
%onnx::Conv_956[FLOAT, 43x43x1x1]
%onnx::Conv_959[FLOAT, 43x43x1x1]
%onnx::Conv_962[FLOAT, 43x128x1x1]
%onnx::Conv_965[FLOAT, 43x43x3x3]
%onnx::Conv_968[FLOAT, 43x43x3x3]
%onnx::Conv_971[FLOAT, 43x128x1x1]
%onnx::Conv_974[FLOAT, 43x43x1x1]
%onnx::Conv_977[FLOAT, 43x43x1x1]
%onnx::Conv_980[FLOAT, 86x128x1x1]
%onnx::Conv_981[FLOAT, 86]
%onnx::Conv_983[FLOAT, 86x86x3x3]
%onnx::Conv_986[FLOAT, 85x85x3x3]
%onnx::Conv_987[FLOAT, 85]
%onnx::Conv_989[FLOAT, 85x128x1x1]
%onnx::Conv_992[FLOAT, 85x85x1x1]
%onnx::Conv_995[FLOAT, 85x85x1x1]
%onnx::Conv_998[FLOAT, 86x256x1x1]
%onnx::Conv_1001[FLOAT, 86x86x3x3]
%onnx::Conv_1004[FLOAT, 85x85x3x3]
%onnx::Conv_1007[FLOAT, 85x256x1x1]
%onnx::Conv_1010[FLOAT, 85x85x1x1]
%onnx::Conv_1013[FLOAT, 85x85x1x1]
%onnx::Conv_1016[FLOAT, 86x256x1x1]
%onnx::Conv_1019[FLOAT, 86x86x3x3]
%onnx::Conv_1022[FLOAT, 85x85x3x3]
%onnx::Conv_1025[FLOAT, 85x256x1x1]
%onnx::Conv_1028[FLOAT, 85x85x1x1]
%onnx::Conv_1031[FLOAT, 85x85x1x1]
%onnx::Conv_1034[FLOAT, 171x256x1x1]
%onnx::Conv_1035[FLOAT, 171]
%onnx::Conv_1037[FLOAT, 171x171x3x3]
%onnx::Conv_1040[FLOAT, 171x171x3x3]
%onnx::Conv_1043[FLOAT, 171x256x1x1]
%onnx::Conv_1046[FLOAT, 171x171x1x1]
%onnx::Conv_1049[FLOAT, 171x171x1x1]
%onnx::Conv_1052[FLOAT, 171x512x1x1]
%onnx::Conv_1055[FLOAT, 171x171x3x3]
%onnx::Conv_1058[FLOAT, 171x171x3x3]
%onnx::Conv_1061[FLOAT, 171x512x1x1]
%onnx::Conv_1064[FLOAT, 171x171x1x1]
%onnx::Conv_1067[FLOAT, 171x171x1x1]
%onnx::Conv_1070[FLOAT, 171x512x1x1]
%onnx::Conv_1073[FLOAT, 171x171x3x3]
%onnx::Conv_1076[FLOAT, 171x171x3x3]
%onnx::Conv_1079[FLOAT, 171x512x1x1]
%onnx::Conv_1082[FLOAT, 171x171x1x1]
%onnx::Conv_1085[FLOAT, 171x171x1x1]
) {
%onnx::Conv_1086 = Identity(%onnx::Conv_1035)
%onnx::Conv_1083 = Identity(%onnx::Conv_1035)
%onnx::Conv_1080 = Identity(%onnx::Conv_1035)
%onnx::Conv_1077 = Identity(%onnx::Conv_1035)
%onnx::Conv_1074 = Identity(%onnx::Conv_1035)
%onnx::Conv_1071 = Identity(%onnx::Conv_1035)
%onnx::Conv_1068 = Identity(%onnx::Conv_1035)
%onnx::Conv_1065 = Identity(%onnx::Conv_1035)
%onnx::Conv_1062 = Identity(%onnx::Conv_1035)
%onnx::Conv_1059 = Identity(%onnx::Conv_1035)
%onnx::Conv_1056 = Identity(%onnx::Conv_1035)
%onnx::Conv_1053 = Identity(%onnx::Conv_1035)
%onnx::Conv_1050 = Identity(%onnx::Conv_1035)
%onnx::Conv_1047 = Identity(%onnx::Conv_1035)
%onnx::Conv_1044 = Identity(%onnx::Conv_1035)
%onnx::Conv_1041 = Identity(%onnx::Conv_1035)
%onnx::Conv_1038 = Identity(%onnx::Conv_1035)
%onnx::Conv_1032 = Identity(%onnx::Conv_987)
%onnx::Conv_1029 = Identity(%onnx::Conv_987)
%onnx::Conv_1026 = Identity(%onnx::Conv_987)
%onnx::Conv_1023 = Identity(%onnx::Conv_987)
%onnx::Conv_1020 = Identity(%onnx::Conv_981)
%onnx::Conv_1017 = Identity(%onnx::Conv_981)
%onnx::Conv_1014 = Identity(%onnx::Conv_987)
%onnx::Conv_1011 = Identity(%onnx::Conv_987)
%onnx::Conv_1008 = Identity(%onnx::Conv_987)
%onnx::Conv_1005 = Identity(%onnx::Conv_987)
%onnx::Conv_1002 = Identity(%onnx::Conv_981)
%onnx::Conv_999 = Identity(%onnx::Conv_981)
%onnx::Conv_996 = Identity(%onnx::Conv_987)
%onnx::Conv_993 = Identity(%onnx::Conv_987)
%onnx::Conv_990 = Identity(%onnx::Conv_987)
%onnx::Conv_984 = Identity(%onnx::Conv_981)
%onnx::Conv_978 = Identity(%onnx::Conv_927)
%onnx::Conv_975 = Identity(%onnx::Conv_927)
%onnx::Conv_972 = Identity(%onnx::Conv_927)
%onnx::Conv_969 = Identity(%onnx::Conv_927)
%onnx::Conv_966 = Identity(%onnx::Conv_927)
%onnx::Conv_963 = Identity(%onnx::Conv_927)
%onnx::Conv_960 = Identity(%onnx::Conv_927)
%onnx::Conv_957 = Identity(%onnx::Conv_927)
%onnx::Conv_954 = Identity(%onnx::Conv_927)
%onnx::Conv_951 = Identity(%onnx::Conv_927)
%onnx::Conv_948 = Identity(%onnx::Conv_927)
%onnx::Conv_945 = Identity(%onnx::Conv_927)
%onnx::Conv_942 = Identity(%onnx::Conv_927)
%onnx::Conv_939 = Identity(%onnx::Conv_927)
%onnx::Conv_936 = Identity(%onnx::Conv_927)
%onnx::Conv_933 = Identity(%onnx::Conv_927)
%onnx::Conv_930 = Identity(%onnx::Conv_927)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_923, %onnx::Conv_924)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_6_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_7_output_0)
%/layers.1/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_8_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_6_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_7_output_0)
%/layers.2/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_8_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_6_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_7_output_0)
%/layers.3/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_8_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_1_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_7_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_8_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_1_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_7_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_8_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_1_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_7_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_8_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_6_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_7_output_0)
%/layers.9/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_8_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_6_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_7_output_0)
%/layers.10/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_8_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_6_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_7_output_0)
%/layers.11/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_8_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%921 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %921
}
|
val_accuracy
| 91.656649
| 874,990,592
| 2,903,359
|
{'zcp_epe_nas': 94.90723856147096, 'zcp_fisher': 876.5755615234375, 'zcp_flops': 13999849472.0, 'zcp_grad_norm': 559.2308959960938, 'zcp_grasp': 593.234375, 'zcp_jacov': -16.05380568624314, 'zcp_l2_norm': 885.166748046875, 'zcp_nwot': 218.6655644443996, 'zcp_params': 2903359.0, 'zcp_plain': 0.0026519177481530002, 'zcp_snip': 2582.0908203125, 'zcp_synflow': 137.2127817368088, 'zcp_zen': 88.91160583496094, 'zcp_val_accuracy': 0.902844548225402}
| |
NASBench101_21713
|
NASBench101
|
21713
|
0d2339c5c3d3961e25349815980980a1
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_878[FLOAT, 128x3x3x3]
%onnx::Conv_879[FLOAT, 128]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_882[FLOAT, 64]
%onnx::Conv_884[FLOAT, 64x64x3x3]
%onnx::Conv_887[FLOAT, 64x128x1x1]
%onnx::Conv_890[FLOAT, 64x64x3x3]
%onnx::Conv_893[FLOAT, 64x128x1x1]
%onnx::Conv_896[FLOAT, 64x64x3x3]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x128x1x1]
%onnx::Conv_908[FLOAT, 64x64x3x3]
%onnx::Conv_911[FLOAT, 64x128x1x1]
%onnx::Conv_914[FLOAT, 64x64x3x3]
%onnx::Conv_917[FLOAT, 64x128x1x1]
%onnx::Conv_920[FLOAT, 64x64x3x3]
%onnx::Conv_923[FLOAT, 64x128x1x1]
%onnx::Conv_926[FLOAT, 64x64x3x3]
%onnx::Conv_929[FLOAT, 64x128x1x1]
%onnx::Conv_932[FLOAT, 64x64x3x3]
%onnx::Conv_935[FLOAT, 128x128x1x1]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 128x128x3x3]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x128x3x3]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x256x1x1]
%onnx::Conv_962[FLOAT, 128x128x3x3]
%onnx::Conv_965[FLOAT, 128x256x1x1]
%onnx::Conv_968[FLOAT, 128x128x3x3]
%onnx::Conv_971[FLOAT, 128x256x1x1]
%onnx::Conv_974[FLOAT, 128x128x3x3]
%onnx::Conv_977[FLOAT, 128x256x1x1]
%onnx::Conv_980[FLOAT, 128x128x3x3]
%onnx::Conv_983[FLOAT, 128x256x1x1]
%onnx::Conv_986[FLOAT, 128x128x3x3]
%onnx::Conv_989[FLOAT, 256x256x1x1]
%onnx::Conv_990[FLOAT, 256]
%onnx::Conv_992[FLOAT, 256x256x3x3]
%onnx::Conv_995[FLOAT, 256x256x1x1]
%onnx::Conv_998[FLOAT, 256x256x3x3]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 256x256x3x3]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x512x1x1]
%onnx::Conv_1016[FLOAT, 256x256x3x3]
%onnx::Conv_1019[FLOAT, 256x512x1x1]
%onnx::Conv_1022[FLOAT, 256x256x3x3]
%onnx::Conv_1025[FLOAT, 256x512x1x1]
%onnx::Conv_1028[FLOAT, 256x256x3x3]
%onnx::Conv_1031[FLOAT, 256x512x1x1]
%onnx::Conv_1034[FLOAT, 256x256x3x3]
%onnx::Conv_1037[FLOAT, 256x512x1x1]
%onnx::Conv_1040[FLOAT, 256x256x3x3]
) {
%onnx::Conv_1041 = Identity(%onnx::Conv_990)
%onnx::Conv_1038 = Identity(%onnx::Conv_990)
%onnx::Conv_1035 = Identity(%onnx::Conv_990)
%onnx::Conv_1032 = Identity(%onnx::Conv_990)
%onnx::Conv_1029 = Identity(%onnx::Conv_990)
%onnx::Conv_1026 = Identity(%onnx::Conv_990)
%onnx::Conv_1023 = Identity(%onnx::Conv_990)
%onnx::Conv_1020 = Identity(%onnx::Conv_990)
%onnx::Conv_1017 = Identity(%onnx::Conv_990)
%onnx::Conv_1014 = Identity(%onnx::Conv_990)
%onnx::Conv_1011 = Identity(%onnx::Conv_990)
%onnx::Conv_1008 = Identity(%onnx::Conv_990)
%onnx::Conv_1005 = Identity(%onnx::Conv_990)
%onnx::Conv_1002 = Identity(%onnx::Conv_990)
%onnx::Conv_999 = Identity(%onnx::Conv_990)
%onnx::Conv_996 = Identity(%onnx::Conv_990)
%onnx::Conv_993 = Identity(%onnx::Conv_990)
%onnx::Conv_987 = Identity(%onnx::Conv_879)
%onnx::Conv_984 = Identity(%onnx::Conv_879)
%onnx::Conv_981 = Identity(%onnx::Conv_879)
%onnx::Conv_978 = Identity(%onnx::Conv_879)
%onnx::Conv_975 = Identity(%onnx::Conv_879)
%onnx::Conv_972 = Identity(%onnx::Conv_879)
%onnx::Conv_969 = Identity(%onnx::Conv_879)
%onnx::Conv_966 = Identity(%onnx::Conv_879)
%onnx::Conv_963 = Identity(%onnx::Conv_879)
%onnx::Conv_960 = Identity(%onnx::Conv_879)
%onnx::Conv_957 = Identity(%onnx::Conv_879)
%onnx::Conv_954 = Identity(%onnx::Conv_879)
%onnx::Conv_951 = Identity(%onnx::Conv_879)
%onnx::Conv_948 = Identity(%onnx::Conv_879)
%onnx::Conv_945 = Identity(%onnx::Conv_879)
%onnx::Conv_942 = Identity(%onnx::Conv_879)
%onnx::Conv_939 = Identity(%onnx::Conv_879)
%onnx::Conv_936 = Identity(%onnx::Conv_879)
%onnx::Conv_933 = Identity(%onnx::Conv_882)
%onnx::Conv_930 = Identity(%onnx::Conv_882)
%onnx::Conv_927 = Identity(%onnx::Conv_882)
%onnx::Conv_924 = Identity(%onnx::Conv_882)
%onnx::Conv_921 = Identity(%onnx::Conv_882)
%onnx::Conv_918 = Identity(%onnx::Conv_882)
%onnx::Conv_915 = Identity(%onnx::Conv_882)
%onnx::Conv_912 = Identity(%onnx::Conv_882)
%onnx::Conv_909 = Identity(%onnx::Conv_882)
%onnx::Conv_906 = Identity(%onnx::Conv_882)
%onnx::Conv_903 = Identity(%onnx::Conv_882)
%onnx::Conv_900 = Identity(%onnx::Conv_882)
%onnx::Conv_897 = Identity(%onnx::Conv_882)
%onnx::Conv_894 = Identity(%onnx::Conv_882)
%onnx::Conv_891 = Identity(%onnx::Conv_882)
%onnx::Conv_888 = Identity(%onnx::Conv_882)
%onnx::Conv_885 = Identity(%onnx::Conv_882)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_878, %onnx::Conv_879)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%876 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %876
}
|
val_accuracy
| 93.078929
| 2,465,736,704
| 8,294,794
|
{'zcp_epe_nas': 108.51346100747911, 'zcp_fisher': 5.903777599334717, 'zcp_flops': 39451787264.0, 'zcp_grad_norm': 46.12677001953125, 'zcp_grasp': 0.019851684570312, 'zcp_jacov': -16.05360781369562, 'zcp_l2_norm': 1040.3641357421875, 'zcp_nwot': 223.66779545443472, 'zcp_params': 8294794.0, 'zcp_plain': -0.019801214337348, 'zcp_snip': 315.081298828125, 'zcp_synflow': 100.25982380188051, 'zcp_zen': 109.45089721679688, 'zcp_val_accuracy': 0.9161658883094781}
| |
NASBench101_30377
|
NASBench101
|
30377
|
125dd123d7acedb55ba3f75f35df9b53
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_572[FLOAT, 128x3x3x3]
%onnx::Conv_573[FLOAT, 128]
%onnx::Conv_575[FLOAT, 43x128x1x1]
%onnx::Conv_576[FLOAT, 43]
%onnx::Conv_578[FLOAT, 43x43x3x3]
%onnx::Conv_581[FLOAT, 42x42x1x1]
%onnx::Conv_582[FLOAT, 42]
%onnx::Conv_584[FLOAT, 43x128x1x1]
%onnx::Conv_587[FLOAT, 43x43x3x3]
%onnx::Conv_590[FLOAT, 42x42x1x1]
%onnx::Conv_593[FLOAT, 43x128x1x1]
%onnx::Conv_596[FLOAT, 43x43x3x3]
%onnx::Conv_599[FLOAT, 42x42x1x1]
%onnx::Conv_602[FLOAT, 86x128x1x1]
%onnx::Conv_603[FLOAT, 86]
%onnx::Conv_605[FLOAT, 85x85x3x3]
%onnx::Conv_606[FLOAT, 85]
%onnx::Conv_608[FLOAT, 85x85x1x1]
%onnx::Conv_611[FLOAT, 86x256x1x1]
%onnx::Conv_614[FLOAT, 85x85x3x3]
%onnx::Conv_617[FLOAT, 85x85x1x1]
%onnx::Conv_620[FLOAT, 86x256x1x1]
%onnx::Conv_623[FLOAT, 85x85x3x3]
%onnx::Conv_626[FLOAT, 85x85x1x1]
%onnx::Conv_629[FLOAT, 171x256x1x1]
%onnx::Conv_630[FLOAT, 171]
%onnx::Conv_632[FLOAT, 171x171x3x3]
%onnx::Conv_635[FLOAT, 170x170x1x1]
%onnx::Conv_636[FLOAT, 170]
%onnx::Conv_638[FLOAT, 171x512x1x1]
%onnx::Conv_641[FLOAT, 171x171x3x3]
%onnx::Conv_644[FLOAT, 170x170x1x1]
%onnx::Conv_647[FLOAT, 171x512x1x1]
%onnx::Conv_650[FLOAT, 171x171x3x3]
%onnx::Conv_653[FLOAT, 170x170x1x1]
) {
%onnx::Conv_654 = Identity(%onnx::Conv_636)
%onnx::Conv_651 = Identity(%onnx::Conv_630)
%onnx::Conv_648 = Identity(%onnx::Conv_630)
%onnx::Conv_645 = Identity(%onnx::Conv_636)
%onnx::Conv_642 = Identity(%onnx::Conv_630)
%onnx::Conv_639 = Identity(%onnx::Conv_630)
%onnx::Conv_633 = Identity(%onnx::Conv_630)
%onnx::Conv_627 = Identity(%onnx::Conv_606)
%onnx::Conv_624 = Identity(%onnx::Conv_606)
%onnx::Conv_621 = Identity(%onnx::Conv_603)
%onnx::Conv_618 = Identity(%onnx::Conv_606)
%onnx::Conv_615 = Identity(%onnx::Conv_606)
%onnx::Conv_612 = Identity(%onnx::Conv_603)
%onnx::Conv_609 = Identity(%onnx::Conv_606)
%onnx::Conv_600 = Identity(%onnx::Conv_582)
%onnx::Conv_597 = Identity(%onnx::Conv_576)
%onnx::Conv_594 = Identity(%onnx::Conv_576)
%onnx::Conv_591 = Identity(%onnx::Conv_582)
%onnx::Conv_588 = Identity(%onnx::Conv_576)
%onnx::Conv_585 = Identity(%onnx::Conv_576)
%onnx::Conv_579 = Identity(%onnx::Conv_576)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_572, %onnx::Conv_573)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_575, %onnx::Conv_576)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_578, %onnx::Conv_579)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/Constant_2_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_1_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Slice_output_0, %onnx::Conv_581, %onnx::Conv_582)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_584, %onnx::Conv_585)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_587, %onnx::Conv_588)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/Constant_2_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_1_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Slice_output_0, %onnx::Conv_590, %onnx::Conv_591)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_593, %onnx::Conv_594)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_596, %onnx::Conv_597)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/Constant_2_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_1_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Slice_output_0, %onnx::Conv_599, %onnx::Conv_600)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_602, %onnx::Conv_603)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_1_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Slice_output_0, %onnx::Conv_605, %onnx::Conv_606)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_608, %onnx::Conv_609)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_611, %onnx::Conv_612)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_1_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Slice_output_0, %onnx::Conv_614, %onnx::Conv_615)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_617, %onnx::Conv_618)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_620, %onnx::Conv_621)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_1_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Slice_output_0, %onnx::Conv_623, %onnx::Conv_624)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_626, %onnx::Conv_627)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_629, %onnx::Conv_630)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_632, %onnx::Conv_633)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/Constant_2_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_1_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Slice_output_0, %onnx::Conv_635, %onnx::Conv_636)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_638, %onnx::Conv_639)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_641, %onnx::Conv_642)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/Constant_2_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_1_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Slice_output_0, %onnx::Conv_644, %onnx::Conv_645)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_647, %onnx::Conv_648)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_650, %onnx::Conv_651)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/Constant_2_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_1_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Slice_output_0, %onnx::Conv_653, %onnx::Conv_654)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%570 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %570
}
|
val_accuracy
| 87.620193
| 439,866,240
| 1,452,822
|
{'zcp_epe_nas': 123.3353793039628, 'zcp_fisher': 6.874601364135742, 'zcp_flops': 7037859840.0, 'zcp_grad_norm': 43.919097900390625, 'zcp_grasp': -2.449981689453125, 'zcp_jacov': -16.042461659666895, 'zcp_l2_norm': 443.6172790527344, 'zcp_nwot': 207.65608000289333, 'zcp_params': 1452822.0, 'zcp_plain': 0.079704947769641, 'zcp_snip': 218.9454803466797, 'zcp_synflow': 79.7657824912043, 'zcp_zen': 53.88709259033203, 'zcp_val_accuracy': 0.9227764606475831}
| |
NASBench101_282559
|
NASBench101
|
282559
|
aafe53d1920ae1390459e6f082367f53
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_545[FLOAT, 128x3x3x3]
%onnx::Conv_546[FLOAT, 128]
%onnx::Conv_548[FLOAT, 43x128x1x1]
%onnx::Conv_549[FLOAT, 43]
%onnx::Conv_551[FLOAT, 43x43x3x3]
%onnx::Conv_554[FLOAT, 43x128x1x1]
%onnx::Conv_557[FLOAT, 43x43x3x3]
%onnx::Conv_560[FLOAT, 43x128x1x1]
%onnx::Conv_563[FLOAT, 43x43x3x3]
%onnx::Conv_566[FLOAT, 86x128x1x1]
%onnx::Conv_567[FLOAT, 86]
%onnx::Conv_569[FLOAT, 86x86x3x3]
%onnx::Conv_572[FLOAT, 86x256x1x1]
%onnx::Conv_575[FLOAT, 86x86x3x3]
%onnx::Conv_578[FLOAT, 86x256x1x1]
%onnx::Conv_581[FLOAT, 86x86x3x3]
%onnx::Conv_584[FLOAT, 171x256x1x1]
%onnx::Conv_585[FLOAT, 171]
%onnx::Conv_587[FLOAT, 171x171x3x3]
%onnx::Conv_590[FLOAT, 171x512x1x1]
%onnx::Conv_593[FLOAT, 171x171x3x3]
%onnx::Conv_596[FLOAT, 171x512x1x1]
%onnx::Conv_599[FLOAT, 171x171x3x3]
) {
%onnx::Conv_600 = Identity(%onnx::Conv_585)
%onnx::Conv_597 = Identity(%onnx::Conv_585)
%onnx::Conv_594 = Identity(%onnx::Conv_585)
%onnx::Conv_591 = Identity(%onnx::Conv_585)
%onnx::Conv_588 = Identity(%onnx::Conv_585)
%onnx::Conv_582 = Identity(%onnx::Conv_567)
%onnx::Conv_579 = Identity(%onnx::Conv_567)
%onnx::Conv_576 = Identity(%onnx::Conv_567)
%onnx::Conv_573 = Identity(%onnx::Conv_567)
%onnx::Conv_570 = Identity(%onnx::Conv_567)
%onnx::Conv_564 = Identity(%onnx::Conv_549)
%onnx::Conv_561 = Identity(%onnx::Conv_549)
%onnx::Conv_558 = Identity(%onnx::Conv_549)
%onnx::Conv_555 = Identity(%onnx::Conv_549)
%onnx::Conv_552 = Identity(%onnx::Conv_549)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_545, %onnx::Conv_546)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_548, %onnx::Conv_549)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_551, %onnx::Conv_552)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_6_output_0)
%/layers.1/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_1_output_0 = Slice(%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/Constant_8_output_0, %/layers.1/Constant_9_output_0, %/layers.1/Constant_7_output_0, %/layers.1/Constant_10_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Slice_1_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_554, %onnx::Conv_555)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_557, %onnx::Conv_558)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_6_output_0)
%/layers.2/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_1_output_0 = Slice(%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/Constant_8_output_0, %/layers.2/Constant_9_output_0, %/layers.2/Constant_7_output_0, %/layers.2/Constant_10_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Slice_1_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_560, %onnx::Conv_561)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_563, %onnx::Conv_564)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_6_output_0)
%/layers.3/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_1_output_0 = Slice(%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/Constant_8_output_0, %/layers.3/Constant_9_output_0, %/layers.3/Constant_7_output_0, %/layers.3/Constant_10_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Slice_1_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_566, %onnx::Conv_567)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_569, %onnx::Conv_570)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_1_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_1_output_0 = Slice(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_7_output_0, %/layers.5/Constant_8_output_0, %/layers.5/Constant_6_output_0, %/layers.5/Constant_9_output_0)
%/layers.5/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/Slice_1_output_0, %/layers.5/Constant_10_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_572, %onnx::Conv_573)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_575, %onnx::Conv_576)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_1_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_1_output_0 = Slice(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_7_output_0, %/layers.6/Constant_8_output_0, %/layers.6/Constant_6_output_0, %/layers.6/Constant_9_output_0)
%/layers.6/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/Slice_1_output_0, %/layers.6/Constant_10_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_578, %onnx::Conv_579)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_581, %onnx::Conv_582)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_1_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_1_output_0 = Slice(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_7_output_0, %/layers.7/Constant_8_output_0, %/layers.7/Constant_6_output_0, %/layers.7/Constant_9_output_0)
%/layers.7/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/Slice_1_output_0, %/layers.7/Constant_10_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_584, %onnx::Conv_585)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_587, %onnx::Conv_588)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_6_output_0)
%/layers.9/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_1_output_0 = Slice(%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/Constant_8_output_0, %/layers.9/Constant_9_output_0, %/layers.9/Constant_7_output_0, %/layers.9/Constant_10_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Slice_1_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_590, %onnx::Conv_591)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_593, %onnx::Conv_594)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_6_output_0)
%/layers.10/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_1_output_0 = Slice(%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/Constant_8_output_0, %/layers.10/Constant_9_output_0, %/layers.10/Constant_7_output_0, %/layers.10/Constant_10_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Slice_1_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_596, %onnx::Conv_597)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_599, %onnx::Conv_600)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_6_output_0)
%/layers.11/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_1_output_0 = Slice(%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/Constant_8_output_0, %/layers.11/Constant_9_output_0, %/layers.11/Constant_7_output_0, %/layers.11/Constant_10_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Slice_1_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%543 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %543
}
|
val_accuracy
| 9.505209
| 407,387,520
| 1,341,996
|
{'zcp_epe_nas': 89.1159867794355, 'zcp_fisher': 151.79327392578125, 'zcp_flops': 6518200320.0, 'zcp_grad_norm': 169.88914489746094, 'zcp_grasp': -135.13427734375, 'zcp_jacov': -16.05316280046585, 'zcp_l2_norm': 321.6799621582031, 'zcp_nwot': 203.65257761420486, 'zcp_params': 1341996.0, 'zcp_plain': 0.37960878014564503, 'zcp_snip': 840.0439453125, 'zcp_synflow': 73.35169400970118, 'zcp_zen': 45.32429504394531, 'zcp_val_accuracy': 0.9256811141967771}
| |
NASBench101_368562
|
NASBench101
|
368562
|
deddeeff075964c8cbe88c92c42b389a
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_554[FLOAT, 128x3x3x3]
%onnx::Conv_555[FLOAT, 128]
%onnx::Conv_557[FLOAT, 128x128x1x1]
%onnx::Conv_560[FLOAT, 128x128x1x1]
%onnx::Conv_563[FLOAT, 128x128x1x1]
%onnx::Conv_566[FLOAT, 128x128x1x1]
%onnx::Conv_569[FLOAT, 128x128x1x1]
%onnx::Conv_572[FLOAT, 128x128x1x1]
%onnx::Conv_575[FLOAT, 128x128x1x1]
%onnx::Conv_578[FLOAT, 128x128x1x1]
%onnx::Conv_581[FLOAT, 128x128x1x1]
%onnx::Conv_584[FLOAT, 256x128x1x1]
%onnx::Conv_585[FLOAT, 256]
%onnx::Conv_587[FLOAT, 256x128x1x1]
%onnx::Conv_590[FLOAT, 256x256x1x1]
%onnx::Conv_593[FLOAT, 256x256x1x1]
%onnx::Conv_596[FLOAT, 256x256x1x1]
%onnx::Conv_599[FLOAT, 256x256x1x1]
%onnx::Conv_602[FLOAT, 256x256x1x1]
%onnx::Conv_605[FLOAT, 256x256x1x1]
%onnx::Conv_608[FLOAT, 256x256x1x1]
%onnx::Conv_611[FLOAT, 512x256x1x1]
%onnx::Conv_612[FLOAT, 512]
%onnx::Conv_614[FLOAT, 512x256x1x1]
%onnx::Conv_617[FLOAT, 512x512x1x1]
%onnx::Conv_620[FLOAT, 512x512x1x1]
%onnx::Conv_623[FLOAT, 512x512x1x1]
%onnx::Conv_626[FLOAT, 512x512x1x1]
%onnx::Conv_629[FLOAT, 512x512x1x1]
%onnx::Conv_632[FLOAT, 512x512x1x1]
%onnx::Conv_635[FLOAT, 512x512x1x1]
) {
%onnx::Conv_636 = Identity(%onnx::Conv_612)
%onnx::Conv_633 = Identity(%onnx::Conv_612)
%onnx::Conv_630 = Identity(%onnx::Conv_612)
%onnx::Conv_627 = Identity(%onnx::Conv_612)
%onnx::Conv_624 = Identity(%onnx::Conv_612)
%onnx::Conv_621 = Identity(%onnx::Conv_612)
%onnx::Conv_618 = Identity(%onnx::Conv_612)
%onnx::Conv_615 = Identity(%onnx::Conv_612)
%onnx::Conv_609 = Identity(%onnx::Conv_585)
%onnx::Conv_606 = Identity(%onnx::Conv_585)
%onnx::Conv_603 = Identity(%onnx::Conv_585)
%onnx::Conv_600 = Identity(%onnx::Conv_585)
%onnx::Conv_597 = Identity(%onnx::Conv_585)
%onnx::Conv_594 = Identity(%onnx::Conv_585)
%onnx::Conv_591 = Identity(%onnx::Conv_585)
%onnx::Conv_588 = Identity(%onnx::Conv_585)
%onnx::Conv_582 = Identity(%onnx::Conv_555)
%onnx::Conv_579 = Identity(%onnx::Conv_555)
%onnx::Conv_576 = Identity(%onnx::Conv_555)
%onnx::Conv_573 = Identity(%onnx::Conv_555)
%onnx::Conv_570 = Identity(%onnx::Conv_555)
%onnx::Conv_567 = Identity(%onnx::Conv_555)
%onnx::Conv_564 = Identity(%onnx::Conv_555)
%onnx::Conv_561 = Identity(%onnx::Conv_555)
%onnx::Conv_558 = Identity(%onnx::Conv_555)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_554, %onnx::Conv_555)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_557, %onnx::Conv_558)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_560, %onnx::Conv_561)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_563, %onnx::Conv_564)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_566, %onnx::Conv_567)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_569, %onnx::Conv_570)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_572, %onnx::Conv_573)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_575, %onnx::Conv_576)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_578, %onnx::Conv_579)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_581, %onnx::Conv_582)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_584, %onnx::Conv_585)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_587, %onnx::Conv_588)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_590, %onnx::Conv_591)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_593, %onnx::Conv_594)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_596, %onnx::Conv_597)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_599, %onnx::Conv_600)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_602, %onnx::Conv_603)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_605, %onnx::Conv_606)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_608, %onnx::Conv_609)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_611, %onnx::Conv_612)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_614, %onnx::Conv_615)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_617, %onnx::Conv_618)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_620, %onnx::Conv_621)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_623, %onnx::Conv_624)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_626, %onnx::Conv_627)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_629, %onnx::Conv_630)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_632, %onnx::Conv_633)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_635, %onnx::Conv_636)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%552 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %552
}
|
val_accuracy
| 88.261217
| 863,512,576
| 2,793,866
|
{'zcp_epe_nas': 104.69202493870222, 'zcp_fisher': 18.186260223388672, 'zcp_flops': 13816201216.0, 'zcp_grad_norm': 81.78083801269531, 'zcp_grasp': -8.957763671875, 'zcp_jacov': -16.05537371477549, 'zcp_l2_norm': 607.5007934570312, 'zcp_nwot': 224.4917698963037, 'zcp_params': 2793866.0, 'zcp_plain': 0.11827228963375001, 'zcp_snip': 563.7890625, 'zcp_synflow': 64.03349262499668, 'zcp_zen': 64.27595520019531, 'zcp_val_accuracy': 0.9231770634651181}
| |
NASBench101_4172
|
NASBench101
|
4172
|
02843663b5543f8bdf64883d62fc8af2
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_848[FLOAT, 128x3x3x3]
%onnx::Conv_849[FLOAT, 128]
%onnx::Conv_851[FLOAT, 43x128x1x1]
%onnx::Conv_852[FLOAT, 43]
%onnx::Conv_854[FLOAT, 43x43x3x3]
%onnx::Conv_857[FLOAT, 43x43x1x1]
%onnx::Conv_860[FLOAT, 43x43x1x1]
%onnx::Conv_863[FLOAT, 43x128x1x1]
%onnx::Conv_866[FLOAT, 43x128x1x1]
%onnx::Conv_869[FLOAT, 43x43x3x3]
%onnx::Conv_872[FLOAT, 43x43x1x1]
%onnx::Conv_875[FLOAT, 43x43x1x1]
%onnx::Conv_878[FLOAT, 43x128x1x1]
%onnx::Conv_881[FLOAT, 43x128x1x1]
%onnx::Conv_884[FLOAT, 43x43x3x3]
%onnx::Conv_887[FLOAT, 43x43x1x1]
%onnx::Conv_890[FLOAT, 43x43x1x1]
%onnx::Conv_893[FLOAT, 43x128x1x1]
%onnx::Conv_896[FLOAT, 86x128x1x1]
%onnx::Conv_897[FLOAT, 86]
%onnx::Conv_899[FLOAT, 86x86x3x3]
%onnx::Conv_902[FLOAT, 86x86x1x1]
%onnx::Conv_905[FLOAT, 86x86x1x1]
%onnx::Conv_908[FLOAT, 85x128x1x1]
%onnx::Conv_909[FLOAT, 85]
%onnx::Conv_911[FLOAT, 86x256x1x1]
%onnx::Conv_914[FLOAT, 86x86x3x3]
%onnx::Conv_917[FLOAT, 86x86x1x1]
%onnx::Conv_920[FLOAT, 86x86x1x1]
%onnx::Conv_923[FLOAT, 85x256x1x1]
%onnx::Conv_926[FLOAT, 86x256x1x1]
%onnx::Conv_929[FLOAT, 86x86x3x3]
%onnx::Conv_932[FLOAT, 86x86x1x1]
%onnx::Conv_935[FLOAT, 86x86x1x1]
%onnx::Conv_938[FLOAT, 85x256x1x1]
%onnx::Conv_941[FLOAT, 171x256x1x1]
%onnx::Conv_942[FLOAT, 171]
%onnx::Conv_944[FLOAT, 171x171x3x3]
%onnx::Conv_947[FLOAT, 171x171x1x1]
%onnx::Conv_950[FLOAT, 171x171x1x1]
%onnx::Conv_953[FLOAT, 171x256x1x1]
%onnx::Conv_956[FLOAT, 171x512x1x1]
%onnx::Conv_959[FLOAT, 171x171x3x3]
%onnx::Conv_962[FLOAT, 171x171x1x1]
%onnx::Conv_965[FLOAT, 171x171x1x1]
%onnx::Conv_968[FLOAT, 171x512x1x1]
%onnx::Conv_971[FLOAT, 171x512x1x1]
%onnx::Conv_974[FLOAT, 171x171x3x3]
%onnx::Conv_977[FLOAT, 171x171x1x1]
%onnx::Conv_980[FLOAT, 171x171x1x1]
%onnx::Conv_983[FLOAT, 171x512x1x1]
) {
%onnx::Conv_984 = Identity(%onnx::Conv_942)
%onnx::Conv_981 = Identity(%onnx::Conv_942)
%onnx::Conv_978 = Identity(%onnx::Conv_942)
%onnx::Conv_975 = Identity(%onnx::Conv_942)
%onnx::Conv_972 = Identity(%onnx::Conv_942)
%onnx::Conv_969 = Identity(%onnx::Conv_942)
%onnx::Conv_966 = Identity(%onnx::Conv_942)
%onnx::Conv_963 = Identity(%onnx::Conv_942)
%onnx::Conv_960 = Identity(%onnx::Conv_942)
%onnx::Conv_957 = Identity(%onnx::Conv_942)
%onnx::Conv_954 = Identity(%onnx::Conv_942)
%onnx::Conv_951 = Identity(%onnx::Conv_942)
%onnx::Conv_948 = Identity(%onnx::Conv_942)
%onnx::Conv_945 = Identity(%onnx::Conv_942)
%onnx::Conv_939 = Identity(%onnx::Conv_909)
%onnx::Conv_936 = Identity(%onnx::Conv_897)
%onnx::Conv_933 = Identity(%onnx::Conv_897)
%onnx::Conv_930 = Identity(%onnx::Conv_897)
%onnx::Conv_927 = Identity(%onnx::Conv_897)
%onnx::Conv_924 = Identity(%onnx::Conv_909)
%onnx::Conv_921 = Identity(%onnx::Conv_897)
%onnx::Conv_918 = Identity(%onnx::Conv_897)
%onnx::Conv_915 = Identity(%onnx::Conv_897)
%onnx::Conv_912 = Identity(%onnx::Conv_897)
%onnx::Conv_906 = Identity(%onnx::Conv_897)
%onnx::Conv_903 = Identity(%onnx::Conv_897)
%onnx::Conv_900 = Identity(%onnx::Conv_897)
%onnx::Conv_894 = Identity(%onnx::Conv_852)
%onnx::Conv_891 = Identity(%onnx::Conv_852)
%onnx::Conv_888 = Identity(%onnx::Conv_852)
%onnx::Conv_885 = Identity(%onnx::Conv_852)
%onnx::Conv_882 = Identity(%onnx::Conv_852)
%onnx::Conv_879 = Identity(%onnx::Conv_852)
%onnx::Conv_876 = Identity(%onnx::Conv_852)
%onnx::Conv_873 = Identity(%onnx::Conv_852)
%onnx::Conv_870 = Identity(%onnx::Conv_852)
%onnx::Conv_867 = Identity(%onnx::Conv_852)
%onnx::Conv_864 = Identity(%onnx::Conv_852)
%onnx::Conv_861 = Identity(%onnx::Conv_852)
%onnx::Conv_858 = Identity(%onnx::Conv_852)
%onnx::Conv_855 = Identity(%onnx::Conv_852)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_848, %onnx::Conv_849)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_6_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_7_output_0)
%/layers.1/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_8_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_6_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_7_output_0)
%/layers.2/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_8_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_6_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_7_output_0)
%/layers.3/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_8_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0, %/layers.5/Constant_5_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_7_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_1_output_0 = Slice(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_9_output_0, %/layers.5/Constant_10_output_0, %/layers.5/Constant_8_output_0, %/layers.5/Constant_11_output_0)
%/layers.5/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/Slice_1_output_0, %/layers.5/Constant_12_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0, %/layers.6/Constant_5_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_7_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_1_output_0 = Slice(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_9_output_0, %/layers.6/Constant_10_output_0, %/layers.6/Constant_8_output_0, %/layers.6/Constant_11_output_0)
%/layers.6/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/Slice_1_output_0, %/layers.6/Constant_12_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0, %/layers.7/Constant_5_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_7_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_1_output_0 = Slice(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_9_output_0, %/layers.7/Constant_10_output_0, %/layers.7/Constant_8_output_0, %/layers.7/Constant_11_output_0)
%/layers.7/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/Slice_1_output_0, %/layers.7/Constant_12_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_6_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_7_output_0)
%/layers.9/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_8_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_6_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_7_output_0)
%/layers.10/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_8_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_6_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_7_output_0)
%/layers.11/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_8_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%846 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %846
}
|
val_accuracy
| 89.783657
| 570,508,928
| 1,868,098
|
{'zcp_epe_nas': 86.43589700218806, 'zcp_fisher': 687.3223876953125, 'zcp_flops': 9128142848.0, 'zcp_grad_norm': 471.4422607421875, 'zcp_grasp': -3453.9921875, 'zcp_jacov': -16.053125445393555, 'zcp_l2_norm': 762.7294921875, 'zcp_nwot': 215.9058336345764, 'zcp_params': 1868098.0, 'zcp_plain': 0.10368180274963301, 'zcp_snip': 2084.880615234375, 'zcp_synflow': 110.01401309836795, 'zcp_zen': 71.44664764404297, 'zcp_val_accuracy': 0.9112580418586731}
| |
NASBench101_234364
|
NASBench101
|
234364
|
8dd717fcc5588f0967c5f53861f9fe4b
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_986[FLOAT, 128x3x3x3]
%onnx::Conv_987[FLOAT, 128]
%onnx::Conv_989[FLOAT, 43x128x1x1]
%onnx::Conv_990[FLOAT, 43]
%onnx::Conv_992[FLOAT, 43x43x1x1]
%onnx::Conv_995[FLOAT, 43x128x1x1]
%onnx::Conv_998[FLOAT, 43x43x3x3]
%onnx::Conv_1001[FLOAT, 43x128x1x1]
%onnx::Conv_1004[FLOAT, 43x43x1x1]
%onnx::Conv_1007[FLOAT, 42x42x3x3]
%onnx::Conv_1008[FLOAT, 42]
%onnx::Conv_1010[FLOAT, 43x128x1x1]
%onnx::Conv_1013[FLOAT, 43x43x1x1]
%onnx::Conv_1016[FLOAT, 43x128x1x1]
%onnx::Conv_1019[FLOAT, 43x43x3x3]
%onnx::Conv_1022[FLOAT, 43x128x1x1]
%onnx::Conv_1025[FLOAT, 43x43x1x1]
%onnx::Conv_1028[FLOAT, 42x42x3x3]
%onnx::Conv_1031[FLOAT, 43x128x1x1]
%onnx::Conv_1034[FLOAT, 43x43x1x1]
%onnx::Conv_1037[FLOAT, 43x128x1x1]
%onnx::Conv_1040[FLOAT, 43x43x3x3]
%onnx::Conv_1043[FLOAT, 43x128x1x1]
%onnx::Conv_1046[FLOAT, 43x43x1x1]
%onnx::Conv_1049[FLOAT, 42x42x3x3]
%onnx::Conv_1052[FLOAT, 86x128x1x1]
%onnx::Conv_1053[FLOAT, 86]
%onnx::Conv_1055[FLOAT, 86x86x1x1]
%onnx::Conv_1058[FLOAT, 85x128x1x1]
%onnx::Conv_1059[FLOAT, 85]
%onnx::Conv_1061[FLOAT, 85x85x3x3]
%onnx::Conv_1064[FLOAT, 85x128x1x1]
%onnx::Conv_1067[FLOAT, 85x85x1x1]
%onnx::Conv_1070[FLOAT, 85x85x3x3]
%onnx::Conv_1073[FLOAT, 86x256x1x1]
%onnx::Conv_1076[FLOAT, 86x86x1x1]
%onnx::Conv_1079[FLOAT, 85x256x1x1]
%onnx::Conv_1082[FLOAT, 85x85x3x3]
%onnx::Conv_1085[FLOAT, 85x256x1x1]
%onnx::Conv_1088[FLOAT, 85x85x1x1]
%onnx::Conv_1091[FLOAT, 85x85x3x3]
%onnx::Conv_1094[FLOAT, 86x256x1x1]
%onnx::Conv_1097[FLOAT, 86x86x1x1]
%onnx::Conv_1100[FLOAT, 85x256x1x1]
%onnx::Conv_1103[FLOAT, 85x85x3x3]
%onnx::Conv_1106[FLOAT, 85x256x1x1]
%onnx::Conv_1109[FLOAT, 85x85x1x1]
%onnx::Conv_1112[FLOAT, 85x85x3x3]
%onnx::Conv_1115[FLOAT, 171x256x1x1]
%onnx::Conv_1116[FLOAT, 171]
%onnx::Conv_1118[FLOAT, 171x171x1x1]
%onnx::Conv_1121[FLOAT, 171x256x1x1]
%onnx::Conv_1124[FLOAT, 171x171x3x3]
%onnx::Conv_1127[FLOAT, 171x256x1x1]
%onnx::Conv_1130[FLOAT, 171x171x1x1]
%onnx::Conv_1133[FLOAT, 170x170x3x3]
%onnx::Conv_1134[FLOAT, 170]
%onnx::Conv_1136[FLOAT, 171x512x1x1]
%onnx::Conv_1139[FLOAT, 171x171x1x1]
%onnx::Conv_1142[FLOAT, 171x512x1x1]
%onnx::Conv_1145[FLOAT, 171x171x3x3]
%onnx::Conv_1148[FLOAT, 171x512x1x1]
%onnx::Conv_1151[FLOAT, 171x171x1x1]
%onnx::Conv_1154[FLOAT, 170x170x3x3]
%onnx::Conv_1157[FLOAT, 171x512x1x1]
%onnx::Conv_1160[FLOAT, 171x171x1x1]
%onnx::Conv_1163[FLOAT, 171x512x1x1]
%onnx::Conv_1166[FLOAT, 171x171x3x3]
%onnx::Conv_1169[FLOAT, 171x512x1x1]
%onnx::Conv_1172[FLOAT, 171x171x1x1]
%onnx::Conv_1175[FLOAT, 170x170x3x3]
) {
%onnx::Conv_1176 = Identity(%onnx::Conv_1134)
%onnx::Conv_1173 = Identity(%onnx::Conv_1116)
%onnx::Conv_1170 = Identity(%onnx::Conv_1116)
%onnx::Conv_1167 = Identity(%onnx::Conv_1116)
%onnx::Conv_1164 = Identity(%onnx::Conv_1116)
%onnx::Conv_1161 = Identity(%onnx::Conv_1116)
%onnx::Conv_1158 = Identity(%onnx::Conv_1116)
%onnx::Conv_1155 = Identity(%onnx::Conv_1134)
%onnx::Conv_1152 = Identity(%onnx::Conv_1116)
%onnx::Conv_1149 = Identity(%onnx::Conv_1116)
%onnx::Conv_1146 = Identity(%onnx::Conv_1116)
%onnx::Conv_1143 = Identity(%onnx::Conv_1116)
%onnx::Conv_1140 = Identity(%onnx::Conv_1116)
%onnx::Conv_1137 = Identity(%onnx::Conv_1116)
%onnx::Conv_1131 = Identity(%onnx::Conv_1116)
%onnx::Conv_1128 = Identity(%onnx::Conv_1116)
%onnx::Conv_1125 = Identity(%onnx::Conv_1116)
%onnx::Conv_1122 = Identity(%onnx::Conv_1116)
%onnx::Conv_1119 = Identity(%onnx::Conv_1116)
%onnx::Conv_1113 = Identity(%onnx::Conv_1059)
%onnx::Conv_1110 = Identity(%onnx::Conv_1059)
%onnx::Conv_1107 = Identity(%onnx::Conv_1059)
%onnx::Conv_1104 = Identity(%onnx::Conv_1059)
%onnx::Conv_1101 = Identity(%onnx::Conv_1059)
%onnx::Conv_1098 = Identity(%onnx::Conv_1053)
%onnx::Conv_1095 = Identity(%onnx::Conv_1053)
%onnx::Conv_1092 = Identity(%onnx::Conv_1059)
%onnx::Conv_1089 = Identity(%onnx::Conv_1059)
%onnx::Conv_1086 = Identity(%onnx::Conv_1059)
%onnx::Conv_1083 = Identity(%onnx::Conv_1059)
%onnx::Conv_1080 = Identity(%onnx::Conv_1059)
%onnx::Conv_1077 = Identity(%onnx::Conv_1053)
%onnx::Conv_1074 = Identity(%onnx::Conv_1053)
%onnx::Conv_1071 = Identity(%onnx::Conv_1059)
%onnx::Conv_1068 = Identity(%onnx::Conv_1059)
%onnx::Conv_1065 = Identity(%onnx::Conv_1059)
%onnx::Conv_1062 = Identity(%onnx::Conv_1059)
%onnx::Conv_1056 = Identity(%onnx::Conv_1053)
%onnx::Conv_1050 = Identity(%onnx::Conv_1008)
%onnx::Conv_1047 = Identity(%onnx::Conv_990)
%onnx::Conv_1044 = Identity(%onnx::Conv_990)
%onnx::Conv_1041 = Identity(%onnx::Conv_990)
%onnx::Conv_1038 = Identity(%onnx::Conv_990)
%onnx::Conv_1035 = Identity(%onnx::Conv_990)
%onnx::Conv_1032 = Identity(%onnx::Conv_990)
%onnx::Conv_1029 = Identity(%onnx::Conv_1008)
%onnx::Conv_1026 = Identity(%onnx::Conv_990)
%onnx::Conv_1023 = Identity(%onnx::Conv_990)
%onnx::Conv_1020 = Identity(%onnx::Conv_990)
%onnx::Conv_1017 = Identity(%onnx::Conv_990)
%onnx::Conv_1014 = Identity(%onnx::Conv_990)
%onnx::Conv_1011 = Identity(%onnx::Conv_990)
%onnx::Conv_1005 = Identity(%onnx::Conv_990)
%onnx::Conv_1002 = Identity(%onnx::Conv_990)
%onnx::Conv_999 = Identity(%onnx::Conv_990)
%onnx::Conv_996 = Identity(%onnx::Conv_990)
%onnx::Conv_993 = Identity(%onnx::Conv_990)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_986, %onnx::Conv_987)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_6_output_0)
%/layers.1/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_7_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_6_output_0)
%/layers.2/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_7_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_6_output_0)
%/layers.3/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_7_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_4_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_7_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_4_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_7_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_4_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_7_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_6_output_0)
%/layers.9/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_7_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_6_output_0)
%/layers.10/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_7_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1169, %onnx::Conv_1170)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1172, %onnx::Conv_1173)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_6_output_0)
%/layers.11/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_7_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1175, %onnx::Conv_1176)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%984 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %984
}
|
val_accuracy
| 93.890226
| 958,512,256
| 3,179,327
|
{'zcp_epe_nas': 141.29217263524572, 'zcp_fisher': 1.942217469215393, 'zcp_flops': 15336196096.0, 'zcp_grad_norm': 33.8497314453125, 'zcp_grasp': 1.675994873046875, 'zcp_jacov': -16.048720309370005, 'zcp_l2_norm': 1079.9537353515625, 'zcp_nwot': 221.10113213537838, 'zcp_params': 3179327.0, 'zcp_plain': 0.047325454652309, 'zcp_snip': 176.31661987304688, 'zcp_synflow': 91.29114098735397, 'zcp_zen': 100.23685455322266, 'zcp_val_accuracy': 0.916566491127014}
| |
NASBench101_50692
|
NASBench101
|
50692
|
1ecf0509838b2ace3bd69d3c2101229b
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_887[FLOAT, 128x3x3x3]
%onnx::Conv_888[FLOAT, 128]
%onnx::Conv_890[FLOAT, 128x128x1x1]
%onnx::Conv_893[FLOAT, 128x128x1x1]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%onnx::Conv_899[FLOAT, 128x128x3x3]
%onnx::Conv_902[FLOAT, 128x128x3x3]
%onnx::Conv_905[FLOAT, 128x128x1x1]
%onnx::Conv_908[FLOAT, 128x128x1x1]
%onnx::Conv_911[FLOAT, 128x128x1x1]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 128x128x3x3]
%onnx::Conv_920[FLOAT, 128x128x3x3]
%onnx::Conv_923[FLOAT, 128x128x1x1]
%onnx::Conv_926[FLOAT, 128x128x1x1]
%onnx::Conv_929[FLOAT, 128x128x1x1]
%onnx::Conv_932[FLOAT, 128x128x1x1]
%onnx::Conv_935[FLOAT, 128x128x3x3]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 256x128x1x1]
%onnx::Conv_945[FLOAT, 256]
%onnx::Conv_947[FLOAT, 256x256x1x1]
%onnx::Conv_950[FLOAT, 256x256x1x1]
%onnx::Conv_953[FLOAT, 256x256x3x3]
%onnx::Conv_956[FLOAT, 256x256x3x3]
%onnx::Conv_959[FLOAT, 256x128x1x1]
%onnx::Conv_962[FLOAT, 256x256x1x1]
%onnx::Conv_965[FLOAT, 256x256x1x1]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 256x256x3x3]
%onnx::Conv_974[FLOAT, 256x256x3x3]
%onnx::Conv_977[FLOAT, 256x256x1x1]
%onnx::Conv_980[FLOAT, 256x256x1x1]
%onnx::Conv_983[FLOAT, 256x256x1x1]
%onnx::Conv_986[FLOAT, 256x256x1x1]
%onnx::Conv_989[FLOAT, 256x256x3x3]
%onnx::Conv_992[FLOAT, 256x256x3x3]
%onnx::Conv_995[FLOAT, 256x256x1x1]
%onnx::Conv_998[FLOAT, 512x256x1x1]
%onnx::Conv_999[FLOAT, 512]
%onnx::Conv_1001[FLOAT, 512x512x1x1]
%onnx::Conv_1004[FLOAT, 512x512x1x1]
%onnx::Conv_1007[FLOAT, 512x512x3x3]
%onnx::Conv_1010[FLOAT, 512x512x3x3]
%onnx::Conv_1013[FLOAT, 512x256x1x1]
%onnx::Conv_1016[FLOAT, 512x512x1x1]
%onnx::Conv_1019[FLOAT, 512x512x1x1]
%onnx::Conv_1022[FLOAT, 512x512x1x1]
%onnx::Conv_1025[FLOAT, 512x512x3x3]
%onnx::Conv_1028[FLOAT, 512x512x3x3]
%onnx::Conv_1031[FLOAT, 512x512x1x1]
%onnx::Conv_1034[FLOAT, 512x512x1x1]
%onnx::Conv_1037[FLOAT, 512x512x1x1]
%onnx::Conv_1040[FLOAT, 512x512x1x1]
%onnx::Conv_1043[FLOAT, 512x512x3x3]
%onnx::Conv_1046[FLOAT, 512x512x3x3]
%onnx::Conv_1049[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1050 = Identity(%onnx::Conv_999)
%onnx::Conv_1047 = Identity(%onnx::Conv_999)
%onnx::Conv_1044 = Identity(%onnx::Conv_999)
%onnx::Conv_1041 = Identity(%onnx::Conv_999)
%onnx::Conv_1038 = Identity(%onnx::Conv_999)
%onnx::Conv_1035 = Identity(%onnx::Conv_999)
%onnx::Conv_1032 = Identity(%onnx::Conv_999)
%onnx::Conv_1029 = Identity(%onnx::Conv_999)
%onnx::Conv_1026 = Identity(%onnx::Conv_999)
%onnx::Conv_1023 = Identity(%onnx::Conv_999)
%onnx::Conv_1020 = Identity(%onnx::Conv_999)
%onnx::Conv_1017 = Identity(%onnx::Conv_999)
%onnx::Conv_1014 = Identity(%onnx::Conv_999)
%onnx::Conv_1011 = Identity(%onnx::Conv_999)
%onnx::Conv_1008 = Identity(%onnx::Conv_999)
%onnx::Conv_1005 = Identity(%onnx::Conv_999)
%onnx::Conv_1002 = Identity(%onnx::Conv_999)
%onnx::Conv_996 = Identity(%onnx::Conv_945)
%onnx::Conv_993 = Identity(%onnx::Conv_945)
%onnx::Conv_990 = Identity(%onnx::Conv_945)
%onnx::Conv_987 = Identity(%onnx::Conv_945)
%onnx::Conv_984 = Identity(%onnx::Conv_945)
%onnx::Conv_981 = Identity(%onnx::Conv_945)
%onnx::Conv_978 = Identity(%onnx::Conv_945)
%onnx::Conv_975 = Identity(%onnx::Conv_945)
%onnx::Conv_972 = Identity(%onnx::Conv_945)
%onnx::Conv_969 = Identity(%onnx::Conv_945)
%onnx::Conv_966 = Identity(%onnx::Conv_945)
%onnx::Conv_963 = Identity(%onnx::Conv_945)
%onnx::Conv_960 = Identity(%onnx::Conv_945)
%onnx::Conv_957 = Identity(%onnx::Conv_945)
%onnx::Conv_954 = Identity(%onnx::Conv_945)
%onnx::Conv_951 = Identity(%onnx::Conv_945)
%onnx::Conv_948 = Identity(%onnx::Conv_945)
%onnx::Conv_942 = Identity(%onnx::Conv_888)
%onnx::Conv_939 = Identity(%onnx::Conv_888)
%onnx::Conv_936 = Identity(%onnx::Conv_888)
%onnx::Conv_933 = Identity(%onnx::Conv_888)
%onnx::Conv_930 = Identity(%onnx::Conv_888)
%onnx::Conv_927 = Identity(%onnx::Conv_888)
%onnx::Conv_924 = Identity(%onnx::Conv_888)
%onnx::Conv_921 = Identity(%onnx::Conv_888)
%onnx::Conv_918 = Identity(%onnx::Conv_888)
%onnx::Conv_915 = Identity(%onnx::Conv_888)
%onnx::Conv_912 = Identity(%onnx::Conv_888)
%onnx::Conv_909 = Identity(%onnx::Conv_888)
%onnx::Conv_906 = Identity(%onnx::Conv_888)
%onnx::Conv_903 = Identity(%onnx::Conv_888)
%onnx::Conv_900 = Identity(%onnx::Conv_888)
%onnx::Conv_897 = Identity(%onnx::Conv_888)
%onnx::Conv_894 = Identity(%onnx::Conv_888)
%onnx::Conv_891 = Identity(%onnx::Conv_888)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_887, %onnx::Conv_888)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_7_output_0 = Add(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_7_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_7_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_7_output_0 = Add(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_7_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_7_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_7_output_0 = Add(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_7_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_7_output_0 = Add(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_7_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_7_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_7_output_0 = Add(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_7_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_7_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_7_output_0 = Add(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_7_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_7_output_0 = Add(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_7_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_7_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_7_output_0 = Add(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_7_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_7_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_7_output_0 = Add(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_7_output_0)
%885 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %885
}
|
val_accuracy
| 93.499601
| 6,617,835,520
| 22,421,642
|
{'zcp_epe_nas': 90.9182061662714, 'zcp_fisher': 22.09735107421875, 'zcp_flops': 105885368320.0, 'zcp_grad_norm': 89.36631774902344, 'zcp_grasp': -0.669921875, 'zcp_jacov': -16.05228959860021, 'zcp_l2_norm': 1242.894775390625, 'zcp_nwot': 234.84832078853296, 'zcp_params': 22421642.0, 'zcp_plain': -0.012362080626189001, 'zcp_snip': 790.1932983398438, 'zcp_synflow': 155.8680955055344, 'zcp_zen': 115.37737274169922, 'zcp_val_accuracy': 0.891225934028625}
| |
NASBench101_218653
|
NASBench101
|
218653
|
847aae0f5bac5fa5817271c960a3bdfd
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_851[FLOAT, 128x3x3x3]
%onnx::Conv_852[FLOAT, 128]
%onnx::Conv_854[FLOAT, 64x128x1x1]
%onnx::Conv_855[FLOAT, 64]
%onnx::Conv_857[FLOAT, 64x64x3x3]
%onnx::Conv_860[FLOAT, 64x128x1x1]
%onnx::Conv_863[FLOAT, 64x128x1x1]
%onnx::Conv_866[FLOAT, 64x64x1x1]
%onnx::Conv_869[FLOAT, 128x128x1x1]
%onnx::Conv_872[FLOAT, 64x128x1x1]
%onnx::Conv_875[FLOAT, 64x64x3x3]
%onnx::Conv_878[FLOAT, 64x128x1x1]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_884[FLOAT, 64x64x1x1]
%onnx::Conv_887[FLOAT, 128x128x1x1]
%onnx::Conv_890[FLOAT, 64x128x1x1]
%onnx::Conv_893[FLOAT, 64x64x3x3]
%onnx::Conv_896[FLOAT, 64x128x1x1]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x64x1x1]
%onnx::Conv_905[FLOAT, 128x128x1x1]
%onnx::Conv_908[FLOAT, 128x128x1x1]
%onnx::Conv_911[FLOAT, 128x128x3x3]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 128x128x1x1]
%onnx::Conv_920[FLOAT, 128x128x1x1]
%onnx::Conv_923[FLOAT, 256x128x1x1]
%onnx::Conv_924[FLOAT, 256]
%onnx::Conv_926[FLOAT, 128x256x1x1]
%onnx::Conv_929[FLOAT, 128x128x3x3]
%onnx::Conv_932[FLOAT, 128x256x1x1]
%onnx::Conv_935[FLOAT, 128x256x1x1]
%onnx::Conv_938[FLOAT, 128x128x1x1]
%onnx::Conv_941[FLOAT, 256x256x1x1]
%onnx::Conv_944[FLOAT, 128x256x1x1]
%onnx::Conv_947[FLOAT, 128x128x3x3]
%onnx::Conv_950[FLOAT, 128x256x1x1]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x128x1x1]
%onnx::Conv_959[FLOAT, 256x256x1x1]
%onnx::Conv_962[FLOAT, 256x256x1x1]
%onnx::Conv_965[FLOAT, 256x256x3x3]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 256x256x1x1]
%onnx::Conv_974[FLOAT, 256x256x1x1]
%onnx::Conv_977[FLOAT, 512x256x1x1]
%onnx::Conv_978[FLOAT, 512]
%onnx::Conv_980[FLOAT, 256x512x1x1]
%onnx::Conv_983[FLOAT, 256x256x3x3]
%onnx::Conv_986[FLOAT, 256x512x1x1]
%onnx::Conv_989[FLOAT, 256x512x1x1]
%onnx::Conv_992[FLOAT, 256x256x1x1]
%onnx::Conv_995[FLOAT, 512x512x1x1]
%onnx::Conv_998[FLOAT, 256x512x1x1]
%onnx::Conv_1001[FLOAT, 256x256x3x3]
%onnx::Conv_1004[FLOAT, 256x512x1x1]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x256x1x1]
%onnx::Conv_1013[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1014 = Identity(%onnx::Conv_978)
%onnx::Conv_1011 = Identity(%onnx::Conv_924)
%onnx::Conv_1008 = Identity(%onnx::Conv_924)
%onnx::Conv_1005 = Identity(%onnx::Conv_924)
%onnx::Conv_1002 = Identity(%onnx::Conv_924)
%onnx::Conv_999 = Identity(%onnx::Conv_924)
%onnx::Conv_996 = Identity(%onnx::Conv_978)
%onnx::Conv_993 = Identity(%onnx::Conv_924)
%onnx::Conv_990 = Identity(%onnx::Conv_924)
%onnx::Conv_987 = Identity(%onnx::Conv_924)
%onnx::Conv_984 = Identity(%onnx::Conv_924)
%onnx::Conv_981 = Identity(%onnx::Conv_924)
%onnx::Conv_975 = Identity(%onnx::Conv_924)
%onnx::Conv_972 = Identity(%onnx::Conv_924)
%onnx::Conv_969 = Identity(%onnx::Conv_924)
%onnx::Conv_966 = Identity(%onnx::Conv_924)
%onnx::Conv_963 = Identity(%onnx::Conv_924)
%onnx::Conv_960 = Identity(%onnx::Conv_924)
%onnx::Conv_957 = Identity(%onnx::Conv_852)
%onnx::Conv_954 = Identity(%onnx::Conv_852)
%onnx::Conv_951 = Identity(%onnx::Conv_852)
%onnx::Conv_948 = Identity(%onnx::Conv_852)
%onnx::Conv_945 = Identity(%onnx::Conv_852)
%onnx::Conv_942 = Identity(%onnx::Conv_924)
%onnx::Conv_939 = Identity(%onnx::Conv_852)
%onnx::Conv_936 = Identity(%onnx::Conv_852)
%onnx::Conv_933 = Identity(%onnx::Conv_852)
%onnx::Conv_930 = Identity(%onnx::Conv_852)
%onnx::Conv_927 = Identity(%onnx::Conv_852)
%onnx::Conv_921 = Identity(%onnx::Conv_852)
%onnx::Conv_918 = Identity(%onnx::Conv_852)
%onnx::Conv_915 = Identity(%onnx::Conv_852)
%onnx::Conv_912 = Identity(%onnx::Conv_852)
%onnx::Conv_909 = Identity(%onnx::Conv_852)
%onnx::Conv_906 = Identity(%onnx::Conv_852)
%onnx::Conv_903 = Identity(%onnx::Conv_855)
%onnx::Conv_900 = Identity(%onnx::Conv_855)
%onnx::Conv_897 = Identity(%onnx::Conv_855)
%onnx::Conv_894 = Identity(%onnx::Conv_855)
%onnx::Conv_891 = Identity(%onnx::Conv_855)
%onnx::Conv_888 = Identity(%onnx::Conv_852)
%onnx::Conv_885 = Identity(%onnx::Conv_855)
%onnx::Conv_882 = Identity(%onnx::Conv_855)
%onnx::Conv_879 = Identity(%onnx::Conv_855)
%onnx::Conv_876 = Identity(%onnx::Conv_855)
%onnx::Conv_873 = Identity(%onnx::Conv_855)
%onnx::Conv_870 = Identity(%onnx::Conv_852)
%onnx::Conv_867 = Identity(%onnx::Conv_855)
%onnx::Conv_864 = Identity(%onnx::Conv_855)
%onnx::Conv_861 = Identity(%onnx::Conv_855)
%onnx::Conv_858 = Identity(%onnx::Conv_855)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_851, %onnx::Conv_852)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_5_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_5_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_5_output_0)
%849 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %849
}
|
val_accuracy
| 92.858571
| 1,453,467,648
| 4,779,018
|
{'zcp_epe_nas': 200.03720107908865, 'zcp_fisher': 0.9970174431800841, 'zcp_flops': 23255482368.0, 'zcp_grad_norm': 25.669105529785156, 'zcp_grasp': -0.997957229614257, 'zcp_jacov': -16.052021183105662, 'zcp_l2_norm': 1084.3538818359375, 'zcp_nwot': 226.41988354854, 'zcp_params': 4779018.0, 'zcp_plain': 0.023276109248399002, 'zcp_snip': 155.87083435058594, 'zcp_synflow': 85.13476144419964, 'zcp_zen': 103.48284149169922, 'zcp_val_accuracy': 0.9268830418586731}
| |
NASBench101_136741
|
NASBench101
|
136741
|
52ab3e0d299babe61ea814b3ee387de0
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_635[FLOAT, 128x3x3x3]
%onnx::Conv_636[FLOAT, 128]
%onnx::Conv_638[FLOAT, 128x128x1x1]
%onnx::Conv_641[FLOAT, 128x128x1x1]
%onnx::Conv_644[FLOAT, 128x128x1x1]
%onnx::Conv_647[FLOAT, 128x128x1x1]
%onnx::Conv_650[FLOAT, 128x128x1x1]
%onnx::Conv_653[FLOAT, 128x128x1x1]
%onnx::Conv_656[FLOAT, 128x128x1x1]
%onnx::Conv_659[FLOAT, 128x128x1x1]
%onnx::Conv_662[FLOAT, 128x128x1x1]
%onnx::Conv_665[FLOAT, 128x128x1x1]
%onnx::Conv_668[FLOAT, 128x128x1x1]
%onnx::Conv_671[FLOAT, 128x128x1x1]
%onnx::Conv_674[FLOAT, 256x128x1x1]
%onnx::Conv_675[FLOAT, 256]
%onnx::Conv_677[FLOAT, 256x256x1x1]
%onnx::Conv_680[FLOAT, 256x256x1x1]
%onnx::Conv_683[FLOAT, 256x128x1x1]
%onnx::Conv_686[FLOAT, 256x256x1x1]
%onnx::Conv_689[FLOAT, 256x256x1x1]
%onnx::Conv_692[FLOAT, 256x256x1x1]
%onnx::Conv_695[FLOAT, 256x256x1x1]
%onnx::Conv_698[FLOAT, 256x256x1x1]
%onnx::Conv_701[FLOAT, 256x256x1x1]
%onnx::Conv_704[FLOAT, 256x256x1x1]
%onnx::Conv_707[FLOAT, 256x256x1x1]
%onnx::Conv_710[FLOAT, 512x256x1x1]
%onnx::Conv_711[FLOAT, 512]
%onnx::Conv_713[FLOAT, 512x512x1x1]
%onnx::Conv_716[FLOAT, 512x512x1x1]
%onnx::Conv_719[FLOAT, 512x256x1x1]
%onnx::Conv_722[FLOAT, 512x512x1x1]
%onnx::Conv_725[FLOAT, 512x512x1x1]
%onnx::Conv_728[FLOAT, 512x512x1x1]
%onnx::Conv_731[FLOAT, 512x512x1x1]
%onnx::Conv_734[FLOAT, 512x512x1x1]
%onnx::Conv_737[FLOAT, 512x512x1x1]
%onnx::Conv_740[FLOAT, 512x512x1x1]
%onnx::Conv_743[FLOAT, 512x512x1x1]
) {
%onnx::Conv_744 = Identity(%onnx::Conv_711)
%onnx::Conv_741 = Identity(%onnx::Conv_711)
%onnx::Conv_738 = Identity(%onnx::Conv_711)
%onnx::Conv_735 = Identity(%onnx::Conv_711)
%onnx::Conv_732 = Identity(%onnx::Conv_711)
%onnx::Conv_729 = Identity(%onnx::Conv_711)
%onnx::Conv_726 = Identity(%onnx::Conv_711)
%onnx::Conv_723 = Identity(%onnx::Conv_711)
%onnx::Conv_720 = Identity(%onnx::Conv_711)
%onnx::Conv_717 = Identity(%onnx::Conv_711)
%onnx::Conv_714 = Identity(%onnx::Conv_711)
%onnx::Conv_708 = Identity(%onnx::Conv_675)
%onnx::Conv_705 = Identity(%onnx::Conv_675)
%onnx::Conv_702 = Identity(%onnx::Conv_675)
%onnx::Conv_699 = Identity(%onnx::Conv_675)
%onnx::Conv_696 = Identity(%onnx::Conv_675)
%onnx::Conv_693 = Identity(%onnx::Conv_675)
%onnx::Conv_690 = Identity(%onnx::Conv_675)
%onnx::Conv_687 = Identity(%onnx::Conv_675)
%onnx::Conv_684 = Identity(%onnx::Conv_675)
%onnx::Conv_681 = Identity(%onnx::Conv_675)
%onnx::Conv_678 = Identity(%onnx::Conv_675)
%onnx::Conv_672 = Identity(%onnx::Conv_636)
%onnx::Conv_669 = Identity(%onnx::Conv_636)
%onnx::Conv_666 = Identity(%onnx::Conv_636)
%onnx::Conv_663 = Identity(%onnx::Conv_636)
%onnx::Conv_660 = Identity(%onnx::Conv_636)
%onnx::Conv_657 = Identity(%onnx::Conv_636)
%onnx::Conv_654 = Identity(%onnx::Conv_636)
%onnx::Conv_651 = Identity(%onnx::Conv_636)
%onnx::Conv_648 = Identity(%onnx::Conv_636)
%onnx::Conv_645 = Identity(%onnx::Conv_636)
%onnx::Conv_642 = Identity(%onnx::Conv_636)
%onnx::Conv_639 = Identity(%onnx::Conv_636)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_635, %onnx::Conv_636)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_638, %onnx::Conv_639)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_641, %onnx::Conv_642)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_644, %onnx::Conv_645)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_647, %onnx::Conv_648)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_650, %onnx::Conv_651)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_653, %onnx::Conv_654)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_656, %onnx::Conv_657)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_659, %onnx::Conv_660)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_662, %onnx::Conv_663)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_4_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_4_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_4_output_0)
%633 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %633
}
|
val_accuracy
| 90.614986
| 1,171,007,488
| 3,831,434
|
{'zcp_epe_nas': 121.52650441444169, 'zcp_fisher': 10.180557250976562, 'zcp_flops': 18736119808.0, 'zcp_grad_norm': 71.89835357666016, 'zcp_grasp': -0.60150146484375, 'zcp_jacov': -16.057570308767037, 'zcp_l2_norm': 818.64990234375, 'zcp_nwot': 229.2472515801995, 'zcp_params': 3831434.0, 'zcp_plain': 0.020649820566177, 'zcp_snip': 526.5225830078125, 'zcp_synflow': 89.91232130842681, 'zcp_zen': 70.81944274902344, 'zcp_val_accuracy': 0.909054458141326}
| |
NASBench101_138948
|
NASBench101
|
138948
|
540071391d1c5998fa42a23b8620cd22
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_941[FLOAT, 128x3x3x3]
%onnx::Conv_942[FLOAT, 128]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%onnx::Conv_953[FLOAT, 128x128x1x1]
%onnx::Conv_956[FLOAT, 128x128x1x1]
%onnx::Conv_959[FLOAT, 128x128x1x1]
%onnx::Conv_962[FLOAT, 128x128x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x128x1x1]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 128x128x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x128x1x1]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x1x1]
%onnx::Conv_998[FLOAT, 128x128x1x1]
%onnx::Conv_1001[FLOAT, 128x128x1x1]
%onnx::Conv_1004[FLOAT, 128x128x1x1]
%onnx::Conv_1007[FLOAT, 256x128x1x1]
%onnx::Conv_1008[FLOAT, 256]
%onnx::Conv_1010[FLOAT, 256x256x1x1]
%onnx::Conv_1013[FLOAT, 256x128x1x1]
%onnx::Conv_1016[FLOAT, 256x256x1x1]
%onnx::Conv_1019[FLOAT, 256x128x1x1]
%onnx::Conv_1022[FLOAT, 256x256x1x1]
%onnx::Conv_1025[FLOAT, 256x256x1x1]
%onnx::Conv_1028[FLOAT, 256x256x1x1]
%onnx::Conv_1031[FLOAT, 256x256x1x1]
%onnx::Conv_1034[FLOAT, 256x256x1x1]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 256x256x1x1]
%onnx::Conv_1043[FLOAT, 256x256x1x1]
%onnx::Conv_1046[FLOAT, 256x256x1x1]
%onnx::Conv_1049[FLOAT, 256x256x1x1]
%onnx::Conv_1052[FLOAT, 256x256x1x1]
%onnx::Conv_1055[FLOAT, 256x256x1x1]
%onnx::Conv_1058[FLOAT, 256x256x1x1]
%onnx::Conv_1061[FLOAT, 256x256x1x1]
%onnx::Conv_1064[FLOAT, 256x256x1x1]
%onnx::Conv_1067[FLOAT, 256x256x1x1]
%onnx::Conv_1070[FLOAT, 512x256x1x1]
%onnx::Conv_1071[FLOAT, 512]
%onnx::Conv_1073[FLOAT, 512x512x1x1]
%onnx::Conv_1076[FLOAT, 512x256x1x1]
%onnx::Conv_1079[FLOAT, 512x512x1x1]
%onnx::Conv_1082[FLOAT, 512x256x1x1]
%onnx::Conv_1085[FLOAT, 512x512x1x1]
%onnx::Conv_1088[FLOAT, 512x512x1x1]
%onnx::Conv_1091[FLOAT, 512x512x1x1]
%onnx::Conv_1094[FLOAT, 512x512x1x1]
%onnx::Conv_1097[FLOAT, 512x512x1x1]
%onnx::Conv_1100[FLOAT, 512x512x1x1]
%onnx::Conv_1103[FLOAT, 512x512x1x1]
%onnx::Conv_1106[FLOAT, 512x512x1x1]
%onnx::Conv_1109[FLOAT, 512x512x1x1]
%onnx::Conv_1112[FLOAT, 512x512x1x1]
%onnx::Conv_1115[FLOAT, 512x512x1x1]
%onnx::Conv_1118[FLOAT, 512x512x1x1]
%onnx::Conv_1121[FLOAT, 512x512x1x1]
%onnx::Conv_1124[FLOAT, 512x512x1x1]
%onnx::Conv_1127[FLOAT, 512x512x1x1]
%onnx::Conv_1130[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1131 = Identity(%onnx::Conv_1071)
%onnx::Conv_1128 = Identity(%onnx::Conv_1071)
%onnx::Conv_1125 = Identity(%onnx::Conv_1071)
%onnx::Conv_1122 = Identity(%onnx::Conv_1071)
%onnx::Conv_1119 = Identity(%onnx::Conv_1071)
%onnx::Conv_1116 = Identity(%onnx::Conv_1071)
%onnx::Conv_1113 = Identity(%onnx::Conv_1071)
%onnx::Conv_1110 = Identity(%onnx::Conv_1071)
%onnx::Conv_1107 = Identity(%onnx::Conv_1071)
%onnx::Conv_1104 = Identity(%onnx::Conv_1071)
%onnx::Conv_1101 = Identity(%onnx::Conv_1071)
%onnx::Conv_1098 = Identity(%onnx::Conv_1071)
%onnx::Conv_1095 = Identity(%onnx::Conv_1071)
%onnx::Conv_1092 = Identity(%onnx::Conv_1071)
%onnx::Conv_1089 = Identity(%onnx::Conv_1071)
%onnx::Conv_1086 = Identity(%onnx::Conv_1071)
%onnx::Conv_1083 = Identity(%onnx::Conv_1071)
%onnx::Conv_1080 = Identity(%onnx::Conv_1071)
%onnx::Conv_1077 = Identity(%onnx::Conv_1071)
%onnx::Conv_1074 = Identity(%onnx::Conv_1071)
%onnx::Conv_1068 = Identity(%onnx::Conv_1008)
%onnx::Conv_1065 = Identity(%onnx::Conv_1008)
%onnx::Conv_1062 = Identity(%onnx::Conv_1008)
%onnx::Conv_1059 = Identity(%onnx::Conv_1008)
%onnx::Conv_1056 = Identity(%onnx::Conv_1008)
%onnx::Conv_1053 = Identity(%onnx::Conv_1008)
%onnx::Conv_1050 = Identity(%onnx::Conv_1008)
%onnx::Conv_1047 = Identity(%onnx::Conv_1008)
%onnx::Conv_1044 = Identity(%onnx::Conv_1008)
%onnx::Conv_1041 = Identity(%onnx::Conv_1008)
%onnx::Conv_1038 = Identity(%onnx::Conv_1008)
%onnx::Conv_1035 = Identity(%onnx::Conv_1008)
%onnx::Conv_1032 = Identity(%onnx::Conv_1008)
%onnx::Conv_1029 = Identity(%onnx::Conv_1008)
%onnx::Conv_1026 = Identity(%onnx::Conv_1008)
%onnx::Conv_1023 = Identity(%onnx::Conv_1008)
%onnx::Conv_1020 = Identity(%onnx::Conv_1008)
%onnx::Conv_1017 = Identity(%onnx::Conv_1008)
%onnx::Conv_1014 = Identity(%onnx::Conv_1008)
%onnx::Conv_1011 = Identity(%onnx::Conv_1008)
%onnx::Conv_1005 = Identity(%onnx::Conv_942)
%onnx::Conv_1002 = Identity(%onnx::Conv_942)
%onnx::Conv_999 = Identity(%onnx::Conv_942)
%onnx::Conv_996 = Identity(%onnx::Conv_942)
%onnx::Conv_993 = Identity(%onnx::Conv_942)
%onnx::Conv_990 = Identity(%onnx::Conv_942)
%onnx::Conv_987 = Identity(%onnx::Conv_942)
%onnx::Conv_984 = Identity(%onnx::Conv_942)
%onnx::Conv_981 = Identity(%onnx::Conv_942)
%onnx::Conv_978 = Identity(%onnx::Conv_942)
%onnx::Conv_975 = Identity(%onnx::Conv_942)
%onnx::Conv_972 = Identity(%onnx::Conv_942)
%onnx::Conv_969 = Identity(%onnx::Conv_942)
%onnx::Conv_966 = Identity(%onnx::Conv_942)
%onnx::Conv_963 = Identity(%onnx::Conv_942)
%onnx::Conv_960 = Identity(%onnx::Conv_942)
%onnx::Conv_957 = Identity(%onnx::Conv_942)
%onnx::Conv_954 = Identity(%onnx::Conv_942)
%onnx::Conv_951 = Identity(%onnx::Conv_942)
%onnx::Conv_948 = Identity(%onnx::Conv_942)
%onnx::Conv_945 = Identity(%onnx::Conv_942)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_941, %onnx::Conv_942)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%939 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %939
}
|
val_accuracy
| 75.030047
| 2,059,937,792
| 6,780,298
|
{'zcp_epe_nas': 93.10626477090828, 'zcp_fisher': 19.137744903564453, 'zcp_flops': 32959004672.0, 'zcp_grad_norm': 109.45075988769531, 'zcp_grasp': 8.280517578125, 'zcp_jacov': -16.036640580666763, 'zcp_l2_norm': 1438.4794921875, 'zcp_nwot': 237.98074314681867, 'zcp_params': 6780298.0, 'zcp_plain': 0.020424440503120003, 'zcp_snip': 791.9432373046875, 'zcp_synflow': 136.82468036092374, 'zcp_zen': 108.97801208496094, 'zcp_val_accuracy': 0.8916265964508051}
| |
NASBench101_270451
|
NASBench101
|
270451
|
a3d50c03115d380945328e53ce1fd03e
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_968[FLOAT, 128x3x3x3]
%onnx::Conv_969[FLOAT, 128]
%onnx::Conv_971[FLOAT, 64x128x1x1]
%onnx::Conv_972[FLOAT, 64]
%onnx::Conv_974[FLOAT, 64x64x1x1]
%onnx::Conv_977[FLOAT, 64x64x3x3]
%onnx::Conv_980[FLOAT, 64x128x1x1]
%onnx::Conv_983[FLOAT, 64x64x1x1]
%onnx::Conv_986[FLOAT, 64x64x3x3]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 64x128x1x1]
%onnx::Conv_995[FLOAT, 64x64x1x1]
%onnx::Conv_998[FLOAT, 64x64x3x3]
%onnx::Conv_1001[FLOAT, 64x128x1x1]
%onnx::Conv_1004[FLOAT, 64x64x1x1]
%onnx::Conv_1007[FLOAT, 64x64x3x3]
%onnx::Conv_1010[FLOAT, 128x128x1x1]
%onnx::Conv_1013[FLOAT, 64x128x1x1]
%onnx::Conv_1016[FLOAT, 64x64x1x1]
%onnx::Conv_1019[FLOAT, 64x64x3x3]
%onnx::Conv_1022[FLOAT, 64x128x1x1]
%onnx::Conv_1025[FLOAT, 64x64x1x1]
%onnx::Conv_1028[FLOAT, 64x64x3x3]
%onnx::Conv_1031[FLOAT, 128x128x1x1]
%onnx::Conv_1034[FLOAT, 128x128x1x1]
%onnx::Conv_1037[FLOAT, 128x128x1x1]
%onnx::Conv_1040[FLOAT, 128x128x3x3]
%onnx::Conv_1043[FLOAT, 128x128x1x1]
%onnx::Conv_1046[FLOAT, 128x128x1x1]
%onnx::Conv_1049[FLOAT, 128x128x3x3]
%onnx::Conv_1052[FLOAT, 256x128x1x1]
%onnx::Conv_1053[FLOAT, 256]
%onnx::Conv_1055[FLOAT, 128x256x1x1]
%onnx::Conv_1058[FLOAT, 128x128x1x1]
%onnx::Conv_1061[FLOAT, 128x128x3x3]
%onnx::Conv_1064[FLOAT, 128x256x1x1]
%onnx::Conv_1067[FLOAT, 128x128x1x1]
%onnx::Conv_1070[FLOAT, 128x128x3x3]
%onnx::Conv_1073[FLOAT, 256x256x1x1]
%onnx::Conv_1076[FLOAT, 128x256x1x1]
%onnx::Conv_1079[FLOAT, 128x128x1x1]
%onnx::Conv_1082[FLOAT, 128x128x3x3]
%onnx::Conv_1085[FLOAT, 128x256x1x1]
%onnx::Conv_1088[FLOAT, 128x128x1x1]
%onnx::Conv_1091[FLOAT, 128x128x3x3]
%onnx::Conv_1094[FLOAT, 256x256x1x1]
%onnx::Conv_1097[FLOAT, 256x256x1x1]
%onnx::Conv_1100[FLOAT, 256x256x1x1]
%onnx::Conv_1103[FLOAT, 256x256x3x3]
%onnx::Conv_1106[FLOAT, 256x256x1x1]
%onnx::Conv_1109[FLOAT, 256x256x1x1]
%onnx::Conv_1112[FLOAT, 256x256x3x3]
%onnx::Conv_1115[FLOAT, 512x256x1x1]
%onnx::Conv_1116[FLOAT, 512]
%onnx::Conv_1118[FLOAT, 256x512x1x1]
%onnx::Conv_1121[FLOAT, 256x256x1x1]
%onnx::Conv_1124[FLOAT, 256x256x3x3]
%onnx::Conv_1127[FLOAT, 256x512x1x1]
%onnx::Conv_1130[FLOAT, 256x256x1x1]
%onnx::Conv_1133[FLOAT, 256x256x3x3]
%onnx::Conv_1136[FLOAT, 512x512x1x1]
%onnx::Conv_1139[FLOAT, 256x512x1x1]
%onnx::Conv_1142[FLOAT, 256x256x1x1]
%onnx::Conv_1145[FLOAT, 256x256x3x3]
%onnx::Conv_1148[FLOAT, 256x512x1x1]
%onnx::Conv_1151[FLOAT, 256x256x1x1]
%onnx::Conv_1154[FLOAT, 256x256x3x3]
%onnx::Conv_1157[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1158 = Identity(%onnx::Conv_1116)
%onnx::Conv_1155 = Identity(%onnx::Conv_1053)
%onnx::Conv_1152 = Identity(%onnx::Conv_1053)
%onnx::Conv_1149 = Identity(%onnx::Conv_1053)
%onnx::Conv_1146 = Identity(%onnx::Conv_1053)
%onnx::Conv_1143 = Identity(%onnx::Conv_1053)
%onnx::Conv_1140 = Identity(%onnx::Conv_1053)
%onnx::Conv_1137 = Identity(%onnx::Conv_1116)
%onnx::Conv_1134 = Identity(%onnx::Conv_1053)
%onnx::Conv_1131 = Identity(%onnx::Conv_1053)
%onnx::Conv_1128 = Identity(%onnx::Conv_1053)
%onnx::Conv_1125 = Identity(%onnx::Conv_1053)
%onnx::Conv_1122 = Identity(%onnx::Conv_1053)
%onnx::Conv_1119 = Identity(%onnx::Conv_1053)
%onnx::Conv_1113 = Identity(%onnx::Conv_1053)
%onnx::Conv_1110 = Identity(%onnx::Conv_1053)
%onnx::Conv_1107 = Identity(%onnx::Conv_1053)
%onnx::Conv_1104 = Identity(%onnx::Conv_1053)
%onnx::Conv_1101 = Identity(%onnx::Conv_1053)
%onnx::Conv_1098 = Identity(%onnx::Conv_1053)
%onnx::Conv_1095 = Identity(%onnx::Conv_1053)
%onnx::Conv_1092 = Identity(%onnx::Conv_969)
%onnx::Conv_1089 = Identity(%onnx::Conv_969)
%onnx::Conv_1086 = Identity(%onnx::Conv_969)
%onnx::Conv_1083 = Identity(%onnx::Conv_969)
%onnx::Conv_1080 = Identity(%onnx::Conv_969)
%onnx::Conv_1077 = Identity(%onnx::Conv_969)
%onnx::Conv_1074 = Identity(%onnx::Conv_1053)
%onnx::Conv_1071 = Identity(%onnx::Conv_969)
%onnx::Conv_1068 = Identity(%onnx::Conv_969)
%onnx::Conv_1065 = Identity(%onnx::Conv_969)
%onnx::Conv_1062 = Identity(%onnx::Conv_969)
%onnx::Conv_1059 = Identity(%onnx::Conv_969)
%onnx::Conv_1056 = Identity(%onnx::Conv_969)
%onnx::Conv_1050 = Identity(%onnx::Conv_969)
%onnx::Conv_1047 = Identity(%onnx::Conv_969)
%onnx::Conv_1044 = Identity(%onnx::Conv_969)
%onnx::Conv_1041 = Identity(%onnx::Conv_969)
%onnx::Conv_1038 = Identity(%onnx::Conv_969)
%onnx::Conv_1035 = Identity(%onnx::Conv_969)
%onnx::Conv_1032 = Identity(%onnx::Conv_969)
%onnx::Conv_1029 = Identity(%onnx::Conv_972)
%onnx::Conv_1026 = Identity(%onnx::Conv_972)
%onnx::Conv_1023 = Identity(%onnx::Conv_972)
%onnx::Conv_1020 = Identity(%onnx::Conv_972)
%onnx::Conv_1017 = Identity(%onnx::Conv_972)
%onnx::Conv_1014 = Identity(%onnx::Conv_972)
%onnx::Conv_1011 = Identity(%onnx::Conv_969)
%onnx::Conv_1008 = Identity(%onnx::Conv_972)
%onnx::Conv_1005 = Identity(%onnx::Conv_972)
%onnx::Conv_1002 = Identity(%onnx::Conv_972)
%onnx::Conv_999 = Identity(%onnx::Conv_972)
%onnx::Conv_996 = Identity(%onnx::Conv_972)
%onnx::Conv_993 = Identity(%onnx::Conv_972)
%onnx::Conv_990 = Identity(%onnx::Conv_969)
%onnx::Conv_987 = Identity(%onnx::Conv_972)
%onnx::Conv_984 = Identity(%onnx::Conv_972)
%onnx::Conv_981 = Identity(%onnx::Conv_972)
%onnx::Conv_978 = Identity(%onnx::Conv_972)
%onnx::Conv_975 = Identity(%onnx::Conv_972)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_968, %onnx::Conv_969)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_5_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_5_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_5_output_0)
%966 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %966
}
|
val_accuracy
| 92.878604
| 2,076,977,152
| 6,928,010
|
{'zcp_epe_nas': 82.27744214557477, 'zcp_fisher': 25.647544860839844, 'zcp_flops': 33231634432.0, 'zcp_grad_norm': 125.61306762695312, 'zcp_grasp': -17.220947265625, 'zcp_jacov': -16.065953352305446, 'zcp_l2_norm': 1189.8092041015625, 'zcp_nwot': 228.72456639341374, 'zcp_params': 6928010.0, 'zcp_plain': 0.029266487807035002, 'zcp_snip': 710.8917846679688, 'zcp_synflow': 119.65398361680494, 'zcp_zen': 115.80553436279297, 'zcp_val_accuracy': 0.9036458134651181}
| |
NASBench101_275380
|
NASBench101
|
275380
|
a6bbf5488b81700ced1580f69d6d0edc
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_779[FLOAT, 128x3x3x3]
%onnx::Conv_780[FLOAT, 128]
%onnx::Conv_782[FLOAT, 64x128x1x1]
%onnx::Conv_783[FLOAT, 64]
%onnx::Conv_785[FLOAT, 64x64x1x1]
%onnx::Conv_788[FLOAT, 64x64x1x1]
%onnx::Conv_791[FLOAT, 64x64x1x1]
%onnx::Conv_794[FLOAT, 64x64x3x3]
%onnx::Conv_797[FLOAT, 64x128x1x1]
%onnx::Conv_800[FLOAT, 64x64x1x1]
%onnx::Conv_803[FLOAT, 64x64x1x1]
%onnx::Conv_806[FLOAT, 64x64x1x1]
%onnx::Conv_809[FLOAT, 64x64x3x3]
%onnx::Conv_812[FLOAT, 64x128x1x1]
%onnx::Conv_815[FLOAT, 64x64x1x1]
%onnx::Conv_818[FLOAT, 64x64x1x1]
%onnx::Conv_821[FLOAT, 64x64x1x1]
%onnx::Conv_824[FLOAT, 64x64x3x3]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 128x128x1x1]
%onnx::Conv_833[FLOAT, 128x128x1x1]
%onnx::Conv_836[FLOAT, 128x128x1x1]
%onnx::Conv_839[FLOAT, 128x128x3x3]
%onnx::Conv_842[FLOAT, 128x256x1x1]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x1x1]
%onnx::Conv_851[FLOAT, 128x128x1x1]
%onnx::Conv_854[FLOAT, 128x128x3x3]
%onnx::Conv_857[FLOAT, 128x256x1x1]
%onnx::Conv_860[FLOAT, 128x128x1x1]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%onnx::Conv_866[FLOAT, 128x128x1x1]
%onnx::Conv_869[FLOAT, 128x128x3x3]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_873[FLOAT, 256]
%onnx::Conv_875[FLOAT, 256x256x1x1]
%onnx::Conv_878[FLOAT, 256x256x1x1]
%onnx::Conv_881[FLOAT, 256x256x1x1]
%onnx::Conv_884[FLOAT, 256x256x3x3]
%onnx::Conv_887[FLOAT, 256x512x1x1]
%onnx::Conv_890[FLOAT, 256x256x1x1]
%onnx::Conv_893[FLOAT, 256x256x1x1]
%onnx::Conv_896[FLOAT, 256x256x1x1]
%onnx::Conv_899[FLOAT, 256x256x3x3]
%onnx::Conv_902[FLOAT, 256x512x1x1]
%onnx::Conv_905[FLOAT, 256x256x1x1]
%onnx::Conv_908[FLOAT, 256x256x1x1]
%onnx::Conv_911[FLOAT, 256x256x1x1]
%onnx::Conv_914[FLOAT, 256x256x3x3]
) {
%onnx::Conv_915 = Identity(%onnx::Conv_873)
%onnx::Conv_912 = Identity(%onnx::Conv_873)
%onnx::Conv_909 = Identity(%onnx::Conv_873)
%onnx::Conv_906 = Identity(%onnx::Conv_873)
%onnx::Conv_903 = Identity(%onnx::Conv_873)
%onnx::Conv_900 = Identity(%onnx::Conv_873)
%onnx::Conv_897 = Identity(%onnx::Conv_873)
%onnx::Conv_894 = Identity(%onnx::Conv_873)
%onnx::Conv_891 = Identity(%onnx::Conv_873)
%onnx::Conv_888 = Identity(%onnx::Conv_873)
%onnx::Conv_885 = Identity(%onnx::Conv_873)
%onnx::Conv_882 = Identity(%onnx::Conv_873)
%onnx::Conv_879 = Identity(%onnx::Conv_873)
%onnx::Conv_876 = Identity(%onnx::Conv_873)
%onnx::Conv_870 = Identity(%onnx::Conv_780)
%onnx::Conv_867 = Identity(%onnx::Conv_780)
%onnx::Conv_864 = Identity(%onnx::Conv_780)
%onnx::Conv_861 = Identity(%onnx::Conv_780)
%onnx::Conv_858 = Identity(%onnx::Conv_780)
%onnx::Conv_855 = Identity(%onnx::Conv_780)
%onnx::Conv_852 = Identity(%onnx::Conv_780)
%onnx::Conv_849 = Identity(%onnx::Conv_780)
%onnx::Conv_846 = Identity(%onnx::Conv_780)
%onnx::Conv_843 = Identity(%onnx::Conv_780)
%onnx::Conv_840 = Identity(%onnx::Conv_780)
%onnx::Conv_837 = Identity(%onnx::Conv_780)
%onnx::Conv_834 = Identity(%onnx::Conv_780)
%onnx::Conv_831 = Identity(%onnx::Conv_780)
%onnx::Conv_828 = Identity(%onnx::Conv_780)
%onnx::Conv_825 = Identity(%onnx::Conv_783)
%onnx::Conv_822 = Identity(%onnx::Conv_783)
%onnx::Conv_819 = Identity(%onnx::Conv_783)
%onnx::Conv_816 = Identity(%onnx::Conv_783)
%onnx::Conv_813 = Identity(%onnx::Conv_783)
%onnx::Conv_810 = Identity(%onnx::Conv_783)
%onnx::Conv_807 = Identity(%onnx::Conv_783)
%onnx::Conv_804 = Identity(%onnx::Conv_783)
%onnx::Conv_801 = Identity(%onnx::Conv_783)
%onnx::Conv_798 = Identity(%onnx::Conv_783)
%onnx::Conv_795 = Identity(%onnx::Conv_783)
%onnx::Conv_792 = Identity(%onnx::Conv_783)
%onnx::Conv_789 = Identity(%onnx::Conv_783)
%onnx::Conv_786 = Identity(%onnx::Conv_783)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_779, %onnx::Conv_780)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%777 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %777
}
|
val_accuracy
| 88.782054
| 1,062,086,656
| 3,553,034
|
{'zcp_epe_nas': 79.43781114230487, 'zcp_fisher': 971.5950927734375, 'zcp_flops': 16993386496.0, 'zcp_grad_norm': 587.5595092773438, 'zcp_grasp': -2141.8671875, 'zcp_jacov': -16.061753893223585, 'zcp_l2_norm': 797.2958984375, 'zcp_nwot': 222.13249329808792, 'zcp_params': 3553034.0, 'zcp_plain': 0.020523969084024003, 'zcp_snip': 2801.834716796875, 'zcp_synflow': 110.49560498708024, 'zcp_zen': 73.8230209350586, 'zcp_val_accuracy': 0.8641827106475831}
| |
NASBench101_339921
|
NASBench101
|
339921
|
cd8e6a49b538c1072c818ef34f749614
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_959[FLOAT, 128x3x3x3]
%onnx::Conv_960[FLOAT, 128]
%onnx::Conv_962[FLOAT, 128x128x1x1]
%onnx::Conv_965[FLOAT, 128x128x3x3]
%onnx::Conv_968[FLOAT, 128x128x1x1]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 128x128x3x3]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x128x3x3]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x1x1]
%onnx::Conv_998[FLOAT, 128x128x1x1]
%onnx::Conv_1001[FLOAT, 128x128x3x3]
%onnx::Conv_1004[FLOAT, 128x128x1x1]
%onnx::Conv_1007[FLOAT, 128x128x3x3]
%onnx::Conv_1010[FLOAT, 128x128x1x1]
%onnx::Conv_1013[FLOAT, 128x128x1x1]
%onnx::Conv_1016[FLOAT, 128x128x1x1]
%onnx::Conv_1019[FLOAT, 128x128x1x1]
%onnx::Conv_1022[FLOAT, 128x128x3x3]
%onnx::Conv_1025[FLOAT, 256x128x1x1]
%onnx::Conv_1026[FLOAT, 256]
%onnx::Conv_1028[FLOAT, 256x256x3x3]
%onnx::Conv_1031[FLOAT, 256x128x1x1]
%onnx::Conv_1034[FLOAT, 256x256x1x1]
%onnx::Conv_1037[FLOAT, 256x128x1x1]
%onnx::Conv_1040[FLOAT, 256x128x1x1]
%onnx::Conv_1043[FLOAT, 256x256x3x3]
%onnx::Conv_1046[FLOAT, 256x256x1x1]
%onnx::Conv_1049[FLOAT, 256x256x3x3]
%onnx::Conv_1052[FLOAT, 256x256x1x1]
%onnx::Conv_1055[FLOAT, 256x256x1x1]
%onnx::Conv_1058[FLOAT, 256x256x1x1]
%onnx::Conv_1061[FLOAT, 256x256x1x1]
%onnx::Conv_1064[FLOAT, 256x256x3x3]
%onnx::Conv_1067[FLOAT, 256x256x1x1]
%onnx::Conv_1070[FLOAT, 256x256x3x3]
%onnx::Conv_1073[FLOAT, 256x256x1x1]
%onnx::Conv_1076[FLOAT, 256x256x1x1]
%onnx::Conv_1079[FLOAT, 256x256x1x1]
%onnx::Conv_1082[FLOAT, 256x256x1x1]
%onnx::Conv_1085[FLOAT, 256x256x3x3]
%onnx::Conv_1088[FLOAT, 512x256x1x1]
%onnx::Conv_1089[FLOAT, 512]
%onnx::Conv_1091[FLOAT, 512x512x3x3]
%onnx::Conv_1094[FLOAT, 512x256x1x1]
%onnx::Conv_1097[FLOAT, 512x512x1x1]
%onnx::Conv_1100[FLOAT, 512x256x1x1]
%onnx::Conv_1103[FLOAT, 512x256x1x1]
%onnx::Conv_1106[FLOAT, 512x512x3x3]
%onnx::Conv_1109[FLOAT, 512x512x1x1]
%onnx::Conv_1112[FLOAT, 512x512x3x3]
%onnx::Conv_1115[FLOAT, 512x512x1x1]
%onnx::Conv_1118[FLOAT, 512x512x1x1]
%onnx::Conv_1121[FLOAT, 512x512x1x1]
%onnx::Conv_1124[FLOAT, 512x512x1x1]
%onnx::Conv_1127[FLOAT, 512x512x3x3]
%onnx::Conv_1130[FLOAT, 512x512x1x1]
%onnx::Conv_1133[FLOAT, 512x512x3x3]
%onnx::Conv_1136[FLOAT, 512x512x1x1]
%onnx::Conv_1139[FLOAT, 512x512x1x1]
%onnx::Conv_1142[FLOAT, 512x512x1x1]
%onnx::Conv_1145[FLOAT, 512x512x1x1]
%onnx::Conv_1148[FLOAT, 512x512x3x3]
) {
%onnx::Conv_1149 = Identity(%onnx::Conv_1089)
%onnx::Conv_1146 = Identity(%onnx::Conv_1089)
%onnx::Conv_1143 = Identity(%onnx::Conv_1089)
%onnx::Conv_1140 = Identity(%onnx::Conv_1089)
%onnx::Conv_1137 = Identity(%onnx::Conv_1089)
%onnx::Conv_1134 = Identity(%onnx::Conv_1089)
%onnx::Conv_1131 = Identity(%onnx::Conv_1089)
%onnx::Conv_1128 = Identity(%onnx::Conv_1089)
%onnx::Conv_1125 = Identity(%onnx::Conv_1089)
%onnx::Conv_1122 = Identity(%onnx::Conv_1089)
%onnx::Conv_1119 = Identity(%onnx::Conv_1089)
%onnx::Conv_1116 = Identity(%onnx::Conv_1089)
%onnx::Conv_1113 = Identity(%onnx::Conv_1089)
%onnx::Conv_1110 = Identity(%onnx::Conv_1089)
%onnx::Conv_1107 = Identity(%onnx::Conv_1089)
%onnx::Conv_1104 = Identity(%onnx::Conv_1089)
%onnx::Conv_1101 = Identity(%onnx::Conv_1089)
%onnx::Conv_1098 = Identity(%onnx::Conv_1089)
%onnx::Conv_1095 = Identity(%onnx::Conv_1089)
%onnx::Conv_1092 = Identity(%onnx::Conv_1089)
%onnx::Conv_1086 = Identity(%onnx::Conv_1026)
%onnx::Conv_1083 = Identity(%onnx::Conv_1026)
%onnx::Conv_1080 = Identity(%onnx::Conv_1026)
%onnx::Conv_1077 = Identity(%onnx::Conv_1026)
%onnx::Conv_1074 = Identity(%onnx::Conv_1026)
%onnx::Conv_1071 = Identity(%onnx::Conv_1026)
%onnx::Conv_1068 = Identity(%onnx::Conv_1026)
%onnx::Conv_1065 = Identity(%onnx::Conv_1026)
%onnx::Conv_1062 = Identity(%onnx::Conv_1026)
%onnx::Conv_1059 = Identity(%onnx::Conv_1026)
%onnx::Conv_1056 = Identity(%onnx::Conv_1026)
%onnx::Conv_1053 = Identity(%onnx::Conv_1026)
%onnx::Conv_1050 = Identity(%onnx::Conv_1026)
%onnx::Conv_1047 = Identity(%onnx::Conv_1026)
%onnx::Conv_1044 = Identity(%onnx::Conv_1026)
%onnx::Conv_1041 = Identity(%onnx::Conv_1026)
%onnx::Conv_1038 = Identity(%onnx::Conv_1026)
%onnx::Conv_1035 = Identity(%onnx::Conv_1026)
%onnx::Conv_1032 = Identity(%onnx::Conv_1026)
%onnx::Conv_1029 = Identity(%onnx::Conv_1026)
%onnx::Conv_1023 = Identity(%onnx::Conv_960)
%onnx::Conv_1020 = Identity(%onnx::Conv_960)
%onnx::Conv_1017 = Identity(%onnx::Conv_960)
%onnx::Conv_1014 = Identity(%onnx::Conv_960)
%onnx::Conv_1011 = Identity(%onnx::Conv_960)
%onnx::Conv_1008 = Identity(%onnx::Conv_960)
%onnx::Conv_1005 = Identity(%onnx::Conv_960)
%onnx::Conv_1002 = Identity(%onnx::Conv_960)
%onnx::Conv_999 = Identity(%onnx::Conv_960)
%onnx::Conv_996 = Identity(%onnx::Conv_960)
%onnx::Conv_993 = Identity(%onnx::Conv_960)
%onnx::Conv_990 = Identity(%onnx::Conv_960)
%onnx::Conv_987 = Identity(%onnx::Conv_960)
%onnx::Conv_984 = Identity(%onnx::Conv_960)
%onnx::Conv_981 = Identity(%onnx::Conv_960)
%onnx::Conv_978 = Identity(%onnx::Conv_960)
%onnx::Conv_975 = Identity(%onnx::Conv_960)
%onnx::Conv_972 = Identity(%onnx::Conv_960)
%onnx::Conv_969 = Identity(%onnx::Conv_960)
%onnx::Conv_966 = Identity(%onnx::Conv_960)
%onnx::Conv_963 = Identity(%onnx::Conv_960)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_959, %onnx::Conv_960)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/Add_7_output_0 = Add(%/layers.1/Add_6_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_7_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/Add_7_output_0 = Add(%/layers.2/Add_6_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_7_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/Add_7_output_0 = Add(%/layers.3/Add_6_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_7_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/Add_7_output_0 = Add(%/layers.5/Add_6_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_7_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/Add_7_output_0 = Add(%/layers.6/Add_6_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_7_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/Add_7_output_0 = Add(%/layers.7/Add_6_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_7_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/Add_7_output_0 = Add(%/layers.9/Add_6_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_7_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/Add_7_output_0 = Add(%/layers.10/Add_6_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_7_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/Add_7_output_0 = Add(%/layers.11/Add_6_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_7_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%957 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %957
}
|
val_accuracy
| 92.858571
| 6,858,221,568
| 23,131,530
|
{'zcp_epe_nas': 120.33143416274142, 'zcp_fisher': 11.559283256530762, 'zcp_flops': 109731545088.0, 'zcp_grad_norm': 62.354373931884766, 'zcp_grasp': -1.1065673828125, 'zcp_jacov': -16.054878835636895, 'zcp_l2_norm': 1422.4219970703125, 'zcp_nwot': 236.5226730243828, 'zcp_params': 23131530.0, 'zcp_plain': 0.034836046397686005, 'zcp_snip': 545.9769287109375, 'zcp_synflow': 130.21405385874692, 'zcp_zen': 125.74116516113281, 'zcp_val_accuracy': 0.9095553159713741}
| |
NASBench101_316060
|
NASBench101
|
316060
|
bf3ae0fde6c7014808cfad7a2bac9f5a
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_869[FLOAT, 128x3x3x3]
%onnx::Conv_870[FLOAT, 128]
%onnx::Conv_872[FLOAT, 64x128x1x1]
%onnx::Conv_873[FLOAT, 64]
%onnx::Conv_875[FLOAT, 64x64x1x1]
%onnx::Conv_878[FLOAT, 64x128x1x1]
%onnx::Conv_881[FLOAT, 64x64x3x3]
%onnx::Conv_884[FLOAT, 64x64x1x1]
%onnx::Conv_887[FLOAT, 64x64x1x1]
%onnx::Conv_890[FLOAT, 64x128x1x1]
%onnx::Conv_893[FLOAT, 64x64x1x1]
%onnx::Conv_896[FLOAT, 64x128x1x1]
%onnx::Conv_899[FLOAT, 64x64x3x3]
%onnx::Conv_902[FLOAT, 64x64x1x1]
%onnx::Conv_905[FLOAT, 64x64x1x1]
%onnx::Conv_908[FLOAT, 64x128x1x1]
%onnx::Conv_911[FLOAT, 64x64x1x1]
%onnx::Conv_914[FLOAT, 64x128x1x1]
%onnx::Conv_917[FLOAT, 64x64x3x3]
%onnx::Conv_920[FLOAT, 64x64x1x1]
%onnx::Conv_923[FLOAT, 64x64x1x1]
%onnx::Conv_926[FLOAT, 128x128x1x1]
%onnx::Conv_929[FLOAT, 128x128x1x1]
%onnx::Conv_932[FLOAT, 128x128x1x1]
%onnx::Conv_935[FLOAT, 128x128x3x3]
%onnx::Conv_938[FLOAT, 128x128x1x1]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 128x256x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x256x1x1]
%onnx::Conv_953[FLOAT, 128x128x3x3]
%onnx::Conv_956[FLOAT, 128x128x1x1]
%onnx::Conv_959[FLOAT, 128x128x1x1]
%onnx::Conv_962[FLOAT, 128x256x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x256x1x1]
%onnx::Conv_971[FLOAT, 128x128x3x3]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 256x256x1x1]
%onnx::Conv_981[FLOAT, 256]
%onnx::Conv_983[FLOAT, 256x256x1x1]
%onnx::Conv_986[FLOAT, 256x256x1x1]
%onnx::Conv_989[FLOAT, 256x256x3x3]
%onnx::Conv_992[FLOAT, 256x256x1x1]
%onnx::Conv_995[FLOAT, 256x256x1x1]
%onnx::Conv_998[FLOAT, 256x512x1x1]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 256x512x1x1]
%onnx::Conv_1007[FLOAT, 256x256x3x3]
%onnx::Conv_1010[FLOAT, 256x256x1x1]
%onnx::Conv_1013[FLOAT, 256x256x1x1]
%onnx::Conv_1016[FLOAT, 256x512x1x1]
%onnx::Conv_1019[FLOAT, 256x256x1x1]
%onnx::Conv_1022[FLOAT, 256x512x1x1]
%onnx::Conv_1025[FLOAT, 256x256x3x3]
%onnx::Conv_1028[FLOAT, 256x256x1x1]
%onnx::Conv_1031[FLOAT, 256x256x1x1]
) {
%onnx::Conv_1032 = Identity(%onnx::Conv_981)
%onnx::Conv_1029 = Identity(%onnx::Conv_981)
%onnx::Conv_1026 = Identity(%onnx::Conv_981)
%onnx::Conv_1023 = Identity(%onnx::Conv_981)
%onnx::Conv_1020 = Identity(%onnx::Conv_981)
%onnx::Conv_1017 = Identity(%onnx::Conv_981)
%onnx::Conv_1014 = Identity(%onnx::Conv_981)
%onnx::Conv_1011 = Identity(%onnx::Conv_981)
%onnx::Conv_1008 = Identity(%onnx::Conv_981)
%onnx::Conv_1005 = Identity(%onnx::Conv_981)
%onnx::Conv_1002 = Identity(%onnx::Conv_981)
%onnx::Conv_999 = Identity(%onnx::Conv_981)
%onnx::Conv_996 = Identity(%onnx::Conv_981)
%onnx::Conv_993 = Identity(%onnx::Conv_981)
%onnx::Conv_990 = Identity(%onnx::Conv_981)
%onnx::Conv_987 = Identity(%onnx::Conv_981)
%onnx::Conv_984 = Identity(%onnx::Conv_981)
%onnx::Conv_978 = Identity(%onnx::Conv_870)
%onnx::Conv_975 = Identity(%onnx::Conv_870)
%onnx::Conv_972 = Identity(%onnx::Conv_870)
%onnx::Conv_969 = Identity(%onnx::Conv_870)
%onnx::Conv_966 = Identity(%onnx::Conv_870)
%onnx::Conv_963 = Identity(%onnx::Conv_870)
%onnx::Conv_960 = Identity(%onnx::Conv_870)
%onnx::Conv_957 = Identity(%onnx::Conv_870)
%onnx::Conv_954 = Identity(%onnx::Conv_870)
%onnx::Conv_951 = Identity(%onnx::Conv_870)
%onnx::Conv_948 = Identity(%onnx::Conv_870)
%onnx::Conv_945 = Identity(%onnx::Conv_870)
%onnx::Conv_942 = Identity(%onnx::Conv_870)
%onnx::Conv_939 = Identity(%onnx::Conv_870)
%onnx::Conv_936 = Identity(%onnx::Conv_870)
%onnx::Conv_933 = Identity(%onnx::Conv_870)
%onnx::Conv_930 = Identity(%onnx::Conv_870)
%onnx::Conv_927 = Identity(%onnx::Conv_870)
%onnx::Conv_924 = Identity(%onnx::Conv_873)
%onnx::Conv_921 = Identity(%onnx::Conv_873)
%onnx::Conv_918 = Identity(%onnx::Conv_873)
%onnx::Conv_915 = Identity(%onnx::Conv_873)
%onnx::Conv_912 = Identity(%onnx::Conv_873)
%onnx::Conv_909 = Identity(%onnx::Conv_873)
%onnx::Conv_906 = Identity(%onnx::Conv_873)
%onnx::Conv_903 = Identity(%onnx::Conv_873)
%onnx::Conv_900 = Identity(%onnx::Conv_873)
%onnx::Conv_897 = Identity(%onnx::Conv_873)
%onnx::Conv_894 = Identity(%onnx::Conv_873)
%onnx::Conv_891 = Identity(%onnx::Conv_873)
%onnx::Conv_888 = Identity(%onnx::Conv_873)
%onnx::Conv_885 = Identity(%onnx::Conv_873)
%onnx::Conv_882 = Identity(%onnx::Conv_873)
%onnx::Conv_879 = Identity(%onnx::Conv_873)
%onnx::Conv_876 = Identity(%onnx::Conv_873)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_869, %onnx::Conv_870)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%867 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %867
}
|
val_accuracy
| 93.209136
| 1,199,056,896
| 3,989,898
|
{'zcp_epe_nas': 90.64957160440414, 'zcp_fisher': 23.609445571899414, 'zcp_flops': 19184910336.0, 'zcp_grad_norm': 111.17051696777344, 'zcp_grasp': -35.672607421875, 'zcp_jacov': -16.062110324008227, 'zcp_l2_norm': 994.7344360351562, 'zcp_nwot': 224.6197390535973, 'zcp_params': 3989898.0, 'zcp_plain': 0.018288208171725003, 'zcp_snip': 611.3709716796875, 'zcp_synflow': 110.23002963728639, 'zcp_zen': 89.28192138671875, 'zcp_val_accuracy': 0.9172676205635071}
| |
NASBench101_222518
|
NASBench101
|
222518
|
86d218822995a9d6a15fcae9dc6b42fb
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_797[FLOAT, 128x3x3x3]
%onnx::Conv_798[FLOAT, 128]
%onnx::Conv_800[FLOAT, 128x128x1x1]
%onnx::Conv_803[FLOAT, 128x128x1x1]
%onnx::Conv_806[FLOAT, 128x128x1x1]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x3x3]
%onnx::Conv_815[FLOAT, 128x128x1x1]
%onnx::Conv_818[FLOAT, 128x128x1x1]
%onnx::Conv_821[FLOAT, 128x128x1x1]
%onnx::Conv_824[FLOAT, 128x128x1x1]
%onnx::Conv_827[FLOAT, 128x128x3x3]
%onnx::Conv_830[FLOAT, 128x128x1x1]
%onnx::Conv_833[FLOAT, 128x128x1x1]
%onnx::Conv_836[FLOAT, 128x128x1x1]
%onnx::Conv_839[FLOAT, 128x128x1x1]
%onnx::Conv_842[FLOAT, 128x128x3x3]
%onnx::Conv_845[FLOAT, 256x128x1x1]
%onnx::Conv_846[FLOAT, 256]
%onnx::Conv_848[FLOAT, 256x256x1x1]
%onnx::Conv_851[FLOAT, 256x128x1x1]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_857[FLOAT, 256x256x3x3]
%onnx::Conv_860[FLOAT, 256x256x1x1]
%onnx::Conv_863[FLOAT, 256x256x1x1]
%onnx::Conv_866[FLOAT, 256x256x1x1]
%onnx::Conv_869[FLOAT, 256x256x1x1]
%onnx::Conv_872[FLOAT, 256x256x3x3]
%onnx::Conv_875[FLOAT, 256x256x1x1]
%onnx::Conv_878[FLOAT, 256x256x1x1]
%onnx::Conv_881[FLOAT, 256x256x1x1]
%onnx::Conv_884[FLOAT, 256x256x1x1]
%onnx::Conv_887[FLOAT, 256x256x3x3]
%onnx::Conv_890[FLOAT, 512x256x1x1]
%onnx::Conv_891[FLOAT, 512]
%onnx::Conv_893[FLOAT, 512x512x1x1]
%onnx::Conv_896[FLOAT, 512x256x1x1]
%onnx::Conv_899[FLOAT, 512x512x1x1]
%onnx::Conv_902[FLOAT, 512x512x3x3]
%onnx::Conv_905[FLOAT, 512x512x1x1]
%onnx::Conv_908[FLOAT, 512x512x1x1]
%onnx::Conv_911[FLOAT, 512x512x1x1]
%onnx::Conv_914[FLOAT, 512x512x1x1]
%onnx::Conv_917[FLOAT, 512x512x3x3]
%onnx::Conv_920[FLOAT, 512x512x1x1]
%onnx::Conv_923[FLOAT, 512x512x1x1]
%onnx::Conv_926[FLOAT, 512x512x1x1]
%onnx::Conv_929[FLOAT, 512x512x1x1]
%onnx::Conv_932[FLOAT, 512x512x3x3]
) {
%onnx::Conv_933 = Identity(%onnx::Conv_891)
%onnx::Conv_930 = Identity(%onnx::Conv_891)
%onnx::Conv_927 = Identity(%onnx::Conv_891)
%onnx::Conv_924 = Identity(%onnx::Conv_891)
%onnx::Conv_921 = Identity(%onnx::Conv_891)
%onnx::Conv_918 = Identity(%onnx::Conv_891)
%onnx::Conv_915 = Identity(%onnx::Conv_891)
%onnx::Conv_912 = Identity(%onnx::Conv_891)
%onnx::Conv_909 = Identity(%onnx::Conv_891)
%onnx::Conv_906 = Identity(%onnx::Conv_891)
%onnx::Conv_903 = Identity(%onnx::Conv_891)
%onnx::Conv_900 = Identity(%onnx::Conv_891)
%onnx::Conv_897 = Identity(%onnx::Conv_891)
%onnx::Conv_894 = Identity(%onnx::Conv_891)
%onnx::Conv_888 = Identity(%onnx::Conv_846)
%onnx::Conv_885 = Identity(%onnx::Conv_846)
%onnx::Conv_882 = Identity(%onnx::Conv_846)
%onnx::Conv_879 = Identity(%onnx::Conv_846)
%onnx::Conv_876 = Identity(%onnx::Conv_846)
%onnx::Conv_873 = Identity(%onnx::Conv_846)
%onnx::Conv_870 = Identity(%onnx::Conv_846)
%onnx::Conv_867 = Identity(%onnx::Conv_846)
%onnx::Conv_864 = Identity(%onnx::Conv_846)
%onnx::Conv_861 = Identity(%onnx::Conv_846)
%onnx::Conv_858 = Identity(%onnx::Conv_846)
%onnx::Conv_855 = Identity(%onnx::Conv_846)
%onnx::Conv_852 = Identity(%onnx::Conv_846)
%onnx::Conv_849 = Identity(%onnx::Conv_846)
%onnx::Conv_843 = Identity(%onnx::Conv_798)
%onnx::Conv_840 = Identity(%onnx::Conv_798)
%onnx::Conv_837 = Identity(%onnx::Conv_798)
%onnx::Conv_834 = Identity(%onnx::Conv_798)
%onnx::Conv_831 = Identity(%onnx::Conv_798)
%onnx::Conv_828 = Identity(%onnx::Conv_798)
%onnx::Conv_825 = Identity(%onnx::Conv_798)
%onnx::Conv_822 = Identity(%onnx::Conv_798)
%onnx::Conv_819 = Identity(%onnx::Conv_798)
%onnx::Conv_816 = Identity(%onnx::Conv_798)
%onnx::Conv_813 = Identity(%onnx::Conv_798)
%onnx::Conv_810 = Identity(%onnx::Conv_798)
%onnx::Conv_807 = Identity(%onnx::Conv_798)
%onnx::Conv_804 = Identity(%onnx::Conv_798)
%onnx::Conv_801 = Identity(%onnx::Conv_798)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_797, %onnx::Conv_798)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_7_output_0 = Add(%/layers.1/Add_6_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_7_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_7_output_0 = Add(%/layers.2/Add_6_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_7_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_7_output_0 = Add(%/layers.3/Add_6_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_7_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_7_output_0 = Add(%/layers.5/Add_6_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_7_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_7_output_0 = Add(%/layers.6/Add_6_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_7_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_7_output_0 = Add(%/layers.7/Add_6_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_7_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_7_output_0 = Add(%/layers.9/Add_6_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_7_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_7_output_0 = Add(%/layers.10/Add_6_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_7_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_7_output_0 = Add(%/layers.11/Add_6_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_7_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%795 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %795
}
|
val_accuracy
| 86.548477
| 3,894,421,504
| 13,126,538
|
{'zcp_epe_nas': 91.09748772225927, 'zcp_fisher': 4004.273681640625, 'zcp_flops': 62310744064.0, 'zcp_grad_norm': 975.6710815429688, 'zcp_grasp': -3036.359375, 'zcp_jacov': -16.061546873980134, 'zcp_l2_norm': 1030.636962890625, 'zcp_nwot': 232.0579589846825, 'zcp_params': 13126538.0, 'zcp_plain': 0.27203404903411804, 'zcp_snip': 7653.93212890625, 'zcp_synflow': 126.71803562390919, 'zcp_zen': 100.07830810546875, 'zcp_val_accuracy': 0.923477590084075}
| |
NASBench101_280874
|
NASBench101
|
280874
|
a9fbb3474b975dcc3a64ab64bd14e53b
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_833[FLOAT, 128x3x3x3]
%onnx::Conv_834[FLOAT, 128]
%onnx::Conv_836[FLOAT, 43x128x1x1]
%onnx::Conv_837[FLOAT, 43]
%onnx::Conv_839[FLOAT, 43x43x3x3]
%onnx::Conv_842[FLOAT, 43x43x3x3]
%onnx::Conv_845[FLOAT, 43x128x1x1]
%onnx::Conv_848[FLOAT, 43x43x1x1]
%onnx::Conv_851[FLOAT, 43x128x1x1]
%onnx::Conv_854[FLOAT, 43x43x3x3]
%onnx::Conv_857[FLOAT, 43x43x3x3]
%onnx::Conv_860[FLOAT, 43x128x1x1]
%onnx::Conv_863[FLOAT, 43x43x1x1]
%onnx::Conv_866[FLOAT, 43x128x1x1]
%onnx::Conv_869[FLOAT, 43x43x3x3]
%onnx::Conv_872[FLOAT, 43x43x3x3]
%onnx::Conv_875[FLOAT, 43x128x1x1]
%onnx::Conv_878[FLOAT, 43x43x1x1]
%onnx::Conv_881[FLOAT, 86x128x1x1]
%onnx::Conv_882[FLOAT, 86]
%onnx::Conv_884[FLOAT, 86x86x3x3]
%onnx::Conv_887[FLOAT, 86x86x3x3]
%onnx::Conv_890[FLOAT, 85x128x1x1]
%onnx::Conv_891[FLOAT, 85]
%onnx::Conv_893[FLOAT, 85x85x1x1]
%onnx::Conv_896[FLOAT, 86x256x1x1]
%onnx::Conv_899[FLOAT, 86x86x3x3]
%onnx::Conv_902[FLOAT, 86x86x3x3]
%onnx::Conv_905[FLOAT, 85x256x1x1]
%onnx::Conv_908[FLOAT, 85x85x1x1]
%onnx::Conv_911[FLOAT, 86x256x1x1]
%onnx::Conv_914[FLOAT, 86x86x3x3]
%onnx::Conv_917[FLOAT, 86x86x3x3]
%onnx::Conv_920[FLOAT, 85x256x1x1]
%onnx::Conv_923[FLOAT, 85x85x1x1]
%onnx::Conv_926[FLOAT, 171x256x1x1]
%onnx::Conv_927[FLOAT, 171]
%onnx::Conv_929[FLOAT, 171x171x3x3]
%onnx::Conv_932[FLOAT, 171x171x3x3]
%onnx::Conv_935[FLOAT, 171x256x1x1]
%onnx::Conv_938[FLOAT, 171x171x1x1]
%onnx::Conv_941[FLOAT, 171x512x1x1]
%onnx::Conv_944[FLOAT, 171x171x3x3]
%onnx::Conv_947[FLOAT, 171x171x3x3]
%onnx::Conv_950[FLOAT, 171x512x1x1]
%onnx::Conv_953[FLOAT, 171x171x1x1]
%onnx::Conv_956[FLOAT, 171x512x1x1]
%onnx::Conv_959[FLOAT, 171x171x3x3]
%onnx::Conv_962[FLOAT, 171x171x3x3]
%onnx::Conv_965[FLOAT, 171x512x1x1]
%onnx::Conv_968[FLOAT, 171x171x1x1]
) {
%onnx::Conv_969 = Identity(%onnx::Conv_927)
%onnx::Conv_966 = Identity(%onnx::Conv_927)
%onnx::Conv_963 = Identity(%onnx::Conv_927)
%onnx::Conv_960 = Identity(%onnx::Conv_927)
%onnx::Conv_957 = Identity(%onnx::Conv_927)
%onnx::Conv_954 = Identity(%onnx::Conv_927)
%onnx::Conv_951 = Identity(%onnx::Conv_927)
%onnx::Conv_948 = Identity(%onnx::Conv_927)
%onnx::Conv_945 = Identity(%onnx::Conv_927)
%onnx::Conv_942 = Identity(%onnx::Conv_927)
%onnx::Conv_939 = Identity(%onnx::Conv_927)
%onnx::Conv_936 = Identity(%onnx::Conv_927)
%onnx::Conv_933 = Identity(%onnx::Conv_927)
%onnx::Conv_930 = Identity(%onnx::Conv_927)
%onnx::Conv_924 = Identity(%onnx::Conv_891)
%onnx::Conv_921 = Identity(%onnx::Conv_891)
%onnx::Conv_918 = Identity(%onnx::Conv_882)
%onnx::Conv_915 = Identity(%onnx::Conv_882)
%onnx::Conv_912 = Identity(%onnx::Conv_882)
%onnx::Conv_909 = Identity(%onnx::Conv_891)
%onnx::Conv_906 = Identity(%onnx::Conv_891)
%onnx::Conv_903 = Identity(%onnx::Conv_882)
%onnx::Conv_900 = Identity(%onnx::Conv_882)
%onnx::Conv_897 = Identity(%onnx::Conv_882)
%onnx::Conv_894 = Identity(%onnx::Conv_891)
%onnx::Conv_888 = Identity(%onnx::Conv_882)
%onnx::Conv_885 = Identity(%onnx::Conv_882)
%onnx::Conv_879 = Identity(%onnx::Conv_837)
%onnx::Conv_876 = Identity(%onnx::Conv_837)
%onnx::Conv_873 = Identity(%onnx::Conv_837)
%onnx::Conv_870 = Identity(%onnx::Conv_837)
%onnx::Conv_867 = Identity(%onnx::Conv_837)
%onnx::Conv_864 = Identity(%onnx::Conv_837)
%onnx::Conv_861 = Identity(%onnx::Conv_837)
%onnx::Conv_858 = Identity(%onnx::Conv_837)
%onnx::Conv_855 = Identity(%onnx::Conv_837)
%onnx::Conv_852 = Identity(%onnx::Conv_837)
%onnx::Conv_849 = Identity(%onnx::Conv_837)
%onnx::Conv_846 = Identity(%onnx::Conv_837)
%onnx::Conv_843 = Identity(%onnx::Conv_837)
%onnx::Conv_840 = Identity(%onnx::Conv_837)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_833, %onnx::Conv_834)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_6_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_7_output_0)
%/layers.1/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_8_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_6_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_7_output_0)
%/layers.2/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_8_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_6_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_7_output_0)
%/layers.3/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_8_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0, %/layers.5/Constant_5_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_7_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_8_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0, %/layers.6/Constant_5_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_7_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_8_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0, %/layers.7/Constant_5_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_7_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_8_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_6_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_7_output_0)
%/layers.9/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_8_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_6_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_7_output_0)
%/layers.10/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_8_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_6_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_7_output_0)
%/layers.11/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_8_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%831 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %831
}
|
val_accuracy
| 91.245991
| 841,832,576
| 2,791,243
|
{'zcp_epe_nas': 122.32167916082308, 'zcp_fisher': 25.505685806274414, 'zcp_flops': 13469321216.0, 'zcp_grad_norm': 103.81416320800781, 'zcp_grasp': 2.9776611328125, 'zcp_jacov': -16.04570889843726, 'zcp_l2_norm': 763.7227783203125, 'zcp_nwot': 215.61694552181484, 'zcp_params': 2791243.0, 'zcp_plain': -0.012651721015572001, 'zcp_snip': 529.6907958984375, 'zcp_synflow': 92.95837372211727, 'zcp_zen': 80.98001861572266, 'zcp_val_accuracy': 0.9018429517745971}
| |
NASBench101_238000
|
NASBench101
|
238000
|
900750759182437a33c719d4ed9ca2f6
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_860[FLOAT, 128x3x3x3]
%onnx::Conv_861[FLOAT, 128]
%onnx::Conv_863[FLOAT, 64x128x1x1]
%onnx::Conv_864[FLOAT, 64]
%onnx::Conv_866[FLOAT, 64x64x3x3]
%onnx::Conv_869[FLOAT, 64x128x1x1]
%onnx::Conv_872[FLOAT, 64x64x1x1]
%onnx::Conv_875[FLOAT, 64x64x3x3]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_884[FLOAT, 64x64x3x3]
%onnx::Conv_887[FLOAT, 64x128x1x1]
%onnx::Conv_890[FLOAT, 64x64x1x1]
%onnx::Conv_893[FLOAT, 64x64x3x3]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x128x1x1]
%onnx::Conv_908[FLOAT, 64x64x1x1]
%onnx::Conv_911[FLOAT, 64x64x3x3]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 128x128x1x1]
%onnx::Conv_920[FLOAT, 128x128x3x3]
%onnx::Conv_923[FLOAT, 128x128x1x1]
%onnx::Conv_926[FLOAT, 128x128x1x1]
%onnx::Conv_929[FLOAT, 128x128x3x3]
%onnx::Conv_932[FLOAT, 256x128x1x1]
%onnx::Conv_933[FLOAT, 256]
%onnx::Conv_935[FLOAT, 128x256x1x1]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 128x256x1x1]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x3x3]
%onnx::Conv_950[FLOAT, 256x256x1x1]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x256x1x1]
%onnx::Conv_962[FLOAT, 128x128x1x1]
%onnx::Conv_965[FLOAT, 128x128x3x3]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 256x256x1x1]
%onnx::Conv_974[FLOAT, 256x256x3x3]
%onnx::Conv_977[FLOAT, 256x256x1x1]
%onnx::Conv_980[FLOAT, 256x256x1x1]
%onnx::Conv_983[FLOAT, 256x256x3x3]
%onnx::Conv_986[FLOAT, 512x256x1x1]
%onnx::Conv_987[FLOAT, 512]
%onnx::Conv_989[FLOAT, 256x512x1x1]
%onnx::Conv_992[FLOAT, 256x256x3x3]
%onnx::Conv_995[FLOAT, 256x512x1x1]
%onnx::Conv_998[FLOAT, 256x256x1x1]
%onnx::Conv_1001[FLOAT, 256x256x3x3]
%onnx::Conv_1004[FLOAT, 512x512x1x1]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x512x1x1]
%onnx::Conv_1016[FLOAT, 256x256x1x1]
%onnx::Conv_1019[FLOAT, 256x256x3x3]
%onnx::Conv_1022[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1023 = Identity(%onnx::Conv_987)
%onnx::Conv_1020 = Identity(%onnx::Conv_933)
%onnx::Conv_1017 = Identity(%onnx::Conv_933)
%onnx::Conv_1014 = Identity(%onnx::Conv_933)
%onnx::Conv_1011 = Identity(%onnx::Conv_933)
%onnx::Conv_1008 = Identity(%onnx::Conv_933)
%onnx::Conv_1005 = Identity(%onnx::Conv_987)
%onnx::Conv_1002 = Identity(%onnx::Conv_933)
%onnx::Conv_999 = Identity(%onnx::Conv_933)
%onnx::Conv_996 = Identity(%onnx::Conv_933)
%onnx::Conv_993 = Identity(%onnx::Conv_933)
%onnx::Conv_990 = Identity(%onnx::Conv_933)
%onnx::Conv_984 = Identity(%onnx::Conv_933)
%onnx::Conv_981 = Identity(%onnx::Conv_933)
%onnx::Conv_978 = Identity(%onnx::Conv_933)
%onnx::Conv_975 = Identity(%onnx::Conv_933)
%onnx::Conv_972 = Identity(%onnx::Conv_933)
%onnx::Conv_969 = Identity(%onnx::Conv_933)
%onnx::Conv_966 = Identity(%onnx::Conv_861)
%onnx::Conv_963 = Identity(%onnx::Conv_861)
%onnx::Conv_960 = Identity(%onnx::Conv_861)
%onnx::Conv_957 = Identity(%onnx::Conv_861)
%onnx::Conv_954 = Identity(%onnx::Conv_861)
%onnx::Conv_951 = Identity(%onnx::Conv_933)
%onnx::Conv_948 = Identity(%onnx::Conv_861)
%onnx::Conv_945 = Identity(%onnx::Conv_861)
%onnx::Conv_942 = Identity(%onnx::Conv_861)
%onnx::Conv_939 = Identity(%onnx::Conv_861)
%onnx::Conv_936 = Identity(%onnx::Conv_861)
%onnx::Conv_930 = Identity(%onnx::Conv_861)
%onnx::Conv_927 = Identity(%onnx::Conv_861)
%onnx::Conv_924 = Identity(%onnx::Conv_861)
%onnx::Conv_921 = Identity(%onnx::Conv_861)
%onnx::Conv_918 = Identity(%onnx::Conv_861)
%onnx::Conv_915 = Identity(%onnx::Conv_861)
%onnx::Conv_912 = Identity(%onnx::Conv_864)
%onnx::Conv_909 = Identity(%onnx::Conv_864)
%onnx::Conv_906 = Identity(%onnx::Conv_864)
%onnx::Conv_903 = Identity(%onnx::Conv_864)
%onnx::Conv_900 = Identity(%onnx::Conv_864)
%onnx::Conv_897 = Identity(%onnx::Conv_861)
%onnx::Conv_894 = Identity(%onnx::Conv_864)
%onnx::Conv_891 = Identity(%onnx::Conv_864)
%onnx::Conv_888 = Identity(%onnx::Conv_864)
%onnx::Conv_885 = Identity(%onnx::Conv_864)
%onnx::Conv_882 = Identity(%onnx::Conv_864)
%onnx::Conv_879 = Identity(%onnx::Conv_861)
%onnx::Conv_876 = Identity(%onnx::Conv_864)
%onnx::Conv_873 = Identity(%onnx::Conv_864)
%onnx::Conv_870 = Identity(%onnx::Conv_864)
%onnx::Conv_867 = Identity(%onnx::Conv_864)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_860, %onnx::Conv_861)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_4_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_4_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_4_output_0)
%858 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %858
}
|
val_accuracy
| 90.685093
| 1,998,727,168
| 6,667,274
|
{'zcp_epe_nas': 180.33326207861992, 'zcp_fisher': 4.7905144691467285, 'zcp_flops': 31979634688.0, 'zcp_grad_norm': 55.25663757324219, 'zcp_grasp': 4.566253662109375, 'zcp_jacov': -16.059636874922717, 'zcp_l2_norm': 1040.499755859375, 'zcp_nwot': 226.7288677863984, 'zcp_params': 6667274.0, 'zcp_plain': -0.05035869032144501, 'zcp_snip': 348.21881103515625, 'zcp_synflow': 96.40159252485775, 'zcp_zen': 107.4398422241211, 'zcp_val_accuracy': 0.884515225887298}
| |
NASBench101_350895
|
NASBench101
|
350895
|
d41d017dcff777b98a0753f210f6177d
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_644[FLOAT, 128x3x3x3]
%onnx::Conv_645[FLOAT, 128]
%onnx::Conv_647[FLOAT, 128x128x1x1]
%onnx::Conv_650[FLOAT, 128x128x1x1]
%onnx::Conv_653[FLOAT, 128x128x3x3]
%onnx::Conv_656[FLOAT, 128x128x1x1]
%onnx::Conv_659[FLOAT, 128x128x1x1]
%onnx::Conv_662[FLOAT, 128x128x1x1]
%onnx::Conv_665[FLOAT, 128x128x3x3]
%onnx::Conv_668[FLOAT, 128x128x1x1]
%onnx::Conv_671[FLOAT, 128x128x1x1]
%onnx::Conv_674[FLOAT, 128x128x1x1]
%onnx::Conv_677[FLOAT, 128x128x3x3]
%onnx::Conv_680[FLOAT, 128x128x1x1]
%onnx::Conv_683[FLOAT, 256x128x1x1]
%onnx::Conv_684[FLOAT, 256]
%onnx::Conv_686[FLOAT, 256x128x1x1]
%onnx::Conv_689[FLOAT, 256x256x3x3]
%onnx::Conv_692[FLOAT, 256x128x1x1]
%onnx::Conv_695[FLOAT, 256x256x1x1]
%onnx::Conv_698[FLOAT, 256x256x1x1]
%onnx::Conv_701[FLOAT, 256x256x3x3]
%onnx::Conv_704[FLOAT, 256x256x1x1]
%onnx::Conv_707[FLOAT, 256x256x1x1]
%onnx::Conv_710[FLOAT, 256x256x1x1]
%onnx::Conv_713[FLOAT, 256x256x3x3]
%onnx::Conv_716[FLOAT, 256x256x1x1]
%onnx::Conv_719[FLOAT, 512x256x1x1]
%onnx::Conv_720[FLOAT, 512]
%onnx::Conv_722[FLOAT, 512x256x1x1]
%onnx::Conv_725[FLOAT, 512x512x3x3]
%onnx::Conv_728[FLOAT, 512x256x1x1]
%onnx::Conv_731[FLOAT, 512x512x1x1]
%onnx::Conv_734[FLOAT, 512x512x1x1]
%onnx::Conv_737[FLOAT, 512x512x3x3]
%onnx::Conv_740[FLOAT, 512x512x1x1]
%onnx::Conv_743[FLOAT, 512x512x1x1]
%onnx::Conv_746[FLOAT, 512x512x1x1]
%onnx::Conv_749[FLOAT, 512x512x3x3]
%onnx::Conv_752[FLOAT, 512x512x1x1]
) {
%onnx::Conv_753 = Identity(%onnx::Conv_720)
%onnx::Conv_750 = Identity(%onnx::Conv_720)
%onnx::Conv_747 = Identity(%onnx::Conv_720)
%onnx::Conv_744 = Identity(%onnx::Conv_720)
%onnx::Conv_741 = Identity(%onnx::Conv_720)
%onnx::Conv_738 = Identity(%onnx::Conv_720)
%onnx::Conv_735 = Identity(%onnx::Conv_720)
%onnx::Conv_732 = Identity(%onnx::Conv_720)
%onnx::Conv_729 = Identity(%onnx::Conv_720)
%onnx::Conv_726 = Identity(%onnx::Conv_720)
%onnx::Conv_723 = Identity(%onnx::Conv_720)
%onnx::Conv_717 = Identity(%onnx::Conv_684)
%onnx::Conv_714 = Identity(%onnx::Conv_684)
%onnx::Conv_711 = Identity(%onnx::Conv_684)
%onnx::Conv_708 = Identity(%onnx::Conv_684)
%onnx::Conv_705 = Identity(%onnx::Conv_684)
%onnx::Conv_702 = Identity(%onnx::Conv_684)
%onnx::Conv_699 = Identity(%onnx::Conv_684)
%onnx::Conv_696 = Identity(%onnx::Conv_684)
%onnx::Conv_693 = Identity(%onnx::Conv_684)
%onnx::Conv_690 = Identity(%onnx::Conv_684)
%onnx::Conv_687 = Identity(%onnx::Conv_684)
%onnx::Conv_681 = Identity(%onnx::Conv_645)
%onnx::Conv_678 = Identity(%onnx::Conv_645)
%onnx::Conv_675 = Identity(%onnx::Conv_645)
%onnx::Conv_672 = Identity(%onnx::Conv_645)
%onnx::Conv_669 = Identity(%onnx::Conv_645)
%onnx::Conv_666 = Identity(%onnx::Conv_645)
%onnx::Conv_663 = Identity(%onnx::Conv_645)
%onnx::Conv_660 = Identity(%onnx::Conv_645)
%onnx::Conv_657 = Identity(%onnx::Conv_645)
%onnx::Conv_654 = Identity(%onnx::Conv_645)
%onnx::Conv_651 = Identity(%onnx::Conv_645)
%onnx::Conv_648 = Identity(%onnx::Conv_645)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_644, %onnx::Conv_645)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_647, %onnx::Conv_648)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_650, %onnx::Conv_651)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_653, %onnx::Conv_654)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_656, %onnx::Conv_657)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_659, %onnx::Conv_660)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_662, %onnx::Conv_663)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%642 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %642
}
|
val_accuracy
| 89.94391
| 3,553,372,160
| 11,925,130
|
{'zcp_epe_nas': 104.21864189232787, 'zcp_fisher': 23.35136604309082, 'zcp_flops': 56853954560.0, 'zcp_grad_norm': 84.80183410644531, 'zcp_grasp': -43.3056640625, 'zcp_jacov': -16.044247080690376, 'zcp_l2_norm': 802.7247924804688, 'zcp_nwot': 228.42718727898477, 'zcp_params': 11925130.0, 'zcp_plain': 0.25252667069435103, 'zcp_snip': 700.3328247070312, 'zcp_synflow': 73.58669509410008, 'zcp_zen': 87.58181762695312, 'zcp_val_accuracy': 0.9318910241127011}
| |
NASBench101_17864
|
NASBench101
|
17864
|
0ac5420ab1aa87390aa8473225564dcf
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_1175[FLOAT, 128x3x3x3]
%onnx::Conv_1176[FLOAT, 128]
%onnx::Conv_1178[FLOAT, 128x128x1x1]
%onnx::Conv_1181[FLOAT, 128x128x1x1]
%onnx::Conv_1184[FLOAT, 128x128x1x1]
%onnx::Conv_1187[FLOAT, 128x128x1x1]
%onnx::Conv_1190[FLOAT, 128x128x1x1]
%onnx::Conv_1193[FLOAT, 128x128x1x1]
%onnx::Conv_1196[FLOAT, 128x128x1x1]
%onnx::Conv_1199[FLOAT, 128x128x1x1]
%onnx::Conv_1202[FLOAT, 128x128x1x1]
%onnx::Conv_1205[FLOAT, 128x128x1x1]
%onnx::Conv_1208[FLOAT, 128x128x1x1]
%onnx::Conv_1211[FLOAT, 128x128x1x1]
%onnx::Conv_1214[FLOAT, 128x128x1x1]
%onnx::Conv_1217[FLOAT, 128x128x1x1]
%onnx::Conv_1220[FLOAT, 128x128x1x1]
%onnx::Conv_1223[FLOAT, 128x128x1x1]
%onnx::Conv_1226[FLOAT, 128x128x1x1]
%onnx::Conv_1229[FLOAT, 128x128x1x1]
%onnx::Conv_1232[FLOAT, 128x128x1x1]
%onnx::Conv_1235[FLOAT, 128x128x1x1]
%onnx::Conv_1238[FLOAT, 128x128x1x1]
%onnx::Conv_1241[FLOAT, 128x128x1x1]
%onnx::Conv_1244[FLOAT, 128x128x1x1]
%onnx::Conv_1247[FLOAT, 128x128x1x1]
%onnx::Conv_1250[FLOAT, 128x128x1x1]
%onnx::Conv_1253[FLOAT, 128x128x1x1]
%onnx::Conv_1256[FLOAT, 128x128x1x1]
%onnx::Conv_1259[FLOAT, 256x128x1x1]
%onnx::Conv_1260[FLOAT, 256]
%onnx::Conv_1262[FLOAT, 256x256x1x1]
%onnx::Conv_1265[FLOAT, 256x128x1x1]
%onnx::Conv_1268[FLOAT, 256x256x1x1]
%onnx::Conv_1271[FLOAT, 256x128x1x1]
%onnx::Conv_1274[FLOAT, 256x256x1x1]
%onnx::Conv_1277[FLOAT, 256x256x1x1]
%onnx::Conv_1280[FLOAT, 256x128x1x1]
%onnx::Conv_1283[FLOAT, 256x256x1x1]
%onnx::Conv_1286[FLOAT, 256x256x1x1]
%onnx::Conv_1289[FLOAT, 256x256x1x1]
%onnx::Conv_1292[FLOAT, 256x256x1x1]
%onnx::Conv_1295[FLOAT, 256x256x1x1]
%onnx::Conv_1298[FLOAT, 256x256x1x1]
%onnx::Conv_1301[FLOAT, 256x256x1x1]
%onnx::Conv_1304[FLOAT, 256x256x1x1]
%onnx::Conv_1307[FLOAT, 256x256x1x1]
%onnx::Conv_1310[FLOAT, 256x256x1x1]
%onnx::Conv_1313[FLOAT, 256x256x1x1]
%onnx::Conv_1316[FLOAT, 256x256x1x1]
%onnx::Conv_1319[FLOAT, 256x256x1x1]
%onnx::Conv_1322[FLOAT, 256x256x1x1]
%onnx::Conv_1325[FLOAT, 256x256x1x1]
%onnx::Conv_1328[FLOAT, 256x256x1x1]
%onnx::Conv_1331[FLOAT, 256x256x1x1]
%onnx::Conv_1334[FLOAT, 256x256x1x1]
%onnx::Conv_1337[FLOAT, 256x256x1x1]
%onnx::Conv_1340[FLOAT, 512x256x1x1]
%onnx::Conv_1341[FLOAT, 512]
%onnx::Conv_1343[FLOAT, 512x512x1x1]
%onnx::Conv_1346[FLOAT, 512x256x1x1]
%onnx::Conv_1349[FLOAT, 512x512x1x1]
%onnx::Conv_1352[FLOAT, 512x256x1x1]
%onnx::Conv_1355[FLOAT, 512x512x1x1]
%onnx::Conv_1358[FLOAT, 512x512x1x1]
%onnx::Conv_1361[FLOAT, 512x256x1x1]
%onnx::Conv_1364[FLOAT, 512x512x1x1]
%onnx::Conv_1367[FLOAT, 512x512x1x1]
%onnx::Conv_1370[FLOAT, 512x512x1x1]
%onnx::Conv_1373[FLOAT, 512x512x1x1]
%onnx::Conv_1376[FLOAT, 512x512x1x1]
%onnx::Conv_1379[FLOAT, 512x512x1x1]
%onnx::Conv_1382[FLOAT, 512x512x1x1]
%onnx::Conv_1385[FLOAT, 512x512x1x1]
%onnx::Conv_1388[FLOAT, 512x512x1x1]
%onnx::Conv_1391[FLOAT, 512x512x1x1]
%onnx::Conv_1394[FLOAT, 512x512x1x1]
%onnx::Conv_1397[FLOAT, 512x512x1x1]
%onnx::Conv_1400[FLOAT, 512x512x1x1]
%onnx::Conv_1403[FLOAT, 512x512x1x1]
%onnx::Conv_1406[FLOAT, 512x512x1x1]
%onnx::Conv_1409[FLOAT, 512x512x1x1]
%onnx::Conv_1412[FLOAT, 512x512x1x1]
%onnx::Conv_1415[FLOAT, 512x512x1x1]
%onnx::Conv_1418[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1419 = Identity(%onnx::Conv_1341)
%onnx::Conv_1416 = Identity(%onnx::Conv_1341)
%onnx::Conv_1413 = Identity(%onnx::Conv_1341)
%onnx::Conv_1410 = Identity(%onnx::Conv_1341)
%onnx::Conv_1407 = Identity(%onnx::Conv_1341)
%onnx::Conv_1404 = Identity(%onnx::Conv_1341)
%onnx::Conv_1401 = Identity(%onnx::Conv_1341)
%onnx::Conv_1398 = Identity(%onnx::Conv_1341)
%onnx::Conv_1395 = Identity(%onnx::Conv_1341)
%onnx::Conv_1392 = Identity(%onnx::Conv_1341)
%onnx::Conv_1389 = Identity(%onnx::Conv_1341)
%onnx::Conv_1386 = Identity(%onnx::Conv_1341)
%onnx::Conv_1383 = Identity(%onnx::Conv_1341)
%onnx::Conv_1380 = Identity(%onnx::Conv_1341)
%onnx::Conv_1377 = Identity(%onnx::Conv_1341)
%onnx::Conv_1374 = Identity(%onnx::Conv_1341)
%onnx::Conv_1371 = Identity(%onnx::Conv_1341)
%onnx::Conv_1368 = Identity(%onnx::Conv_1341)
%onnx::Conv_1365 = Identity(%onnx::Conv_1341)
%onnx::Conv_1362 = Identity(%onnx::Conv_1341)
%onnx::Conv_1359 = Identity(%onnx::Conv_1341)
%onnx::Conv_1356 = Identity(%onnx::Conv_1341)
%onnx::Conv_1353 = Identity(%onnx::Conv_1341)
%onnx::Conv_1350 = Identity(%onnx::Conv_1341)
%onnx::Conv_1347 = Identity(%onnx::Conv_1341)
%onnx::Conv_1344 = Identity(%onnx::Conv_1341)
%onnx::Conv_1338 = Identity(%onnx::Conv_1260)
%onnx::Conv_1335 = Identity(%onnx::Conv_1260)
%onnx::Conv_1332 = Identity(%onnx::Conv_1260)
%onnx::Conv_1329 = Identity(%onnx::Conv_1260)
%onnx::Conv_1326 = Identity(%onnx::Conv_1260)
%onnx::Conv_1323 = Identity(%onnx::Conv_1260)
%onnx::Conv_1320 = Identity(%onnx::Conv_1260)
%onnx::Conv_1317 = Identity(%onnx::Conv_1260)
%onnx::Conv_1314 = Identity(%onnx::Conv_1260)
%onnx::Conv_1311 = Identity(%onnx::Conv_1260)
%onnx::Conv_1308 = Identity(%onnx::Conv_1260)
%onnx::Conv_1305 = Identity(%onnx::Conv_1260)
%onnx::Conv_1302 = Identity(%onnx::Conv_1260)
%onnx::Conv_1299 = Identity(%onnx::Conv_1260)
%onnx::Conv_1296 = Identity(%onnx::Conv_1260)
%onnx::Conv_1293 = Identity(%onnx::Conv_1260)
%onnx::Conv_1290 = Identity(%onnx::Conv_1260)
%onnx::Conv_1287 = Identity(%onnx::Conv_1260)
%onnx::Conv_1284 = Identity(%onnx::Conv_1260)
%onnx::Conv_1281 = Identity(%onnx::Conv_1260)
%onnx::Conv_1278 = Identity(%onnx::Conv_1260)
%onnx::Conv_1275 = Identity(%onnx::Conv_1260)
%onnx::Conv_1272 = Identity(%onnx::Conv_1260)
%onnx::Conv_1269 = Identity(%onnx::Conv_1260)
%onnx::Conv_1266 = Identity(%onnx::Conv_1260)
%onnx::Conv_1263 = Identity(%onnx::Conv_1260)
%onnx::Conv_1257 = Identity(%onnx::Conv_1176)
%onnx::Conv_1254 = Identity(%onnx::Conv_1176)
%onnx::Conv_1251 = Identity(%onnx::Conv_1176)
%onnx::Conv_1248 = Identity(%onnx::Conv_1176)
%onnx::Conv_1245 = Identity(%onnx::Conv_1176)
%onnx::Conv_1242 = Identity(%onnx::Conv_1176)
%onnx::Conv_1239 = Identity(%onnx::Conv_1176)
%onnx::Conv_1236 = Identity(%onnx::Conv_1176)
%onnx::Conv_1233 = Identity(%onnx::Conv_1176)
%onnx::Conv_1230 = Identity(%onnx::Conv_1176)
%onnx::Conv_1227 = Identity(%onnx::Conv_1176)
%onnx::Conv_1224 = Identity(%onnx::Conv_1176)
%onnx::Conv_1221 = Identity(%onnx::Conv_1176)
%onnx::Conv_1218 = Identity(%onnx::Conv_1176)
%onnx::Conv_1215 = Identity(%onnx::Conv_1176)
%onnx::Conv_1212 = Identity(%onnx::Conv_1176)
%onnx::Conv_1209 = Identity(%onnx::Conv_1176)
%onnx::Conv_1206 = Identity(%onnx::Conv_1176)
%onnx::Conv_1203 = Identity(%onnx::Conv_1176)
%onnx::Conv_1200 = Identity(%onnx::Conv_1176)
%onnx::Conv_1197 = Identity(%onnx::Conv_1176)
%onnx::Conv_1194 = Identity(%onnx::Conv_1176)
%onnx::Conv_1191 = Identity(%onnx::Conv_1176)
%onnx::Conv_1188 = Identity(%onnx::Conv_1176)
%onnx::Conv_1185 = Identity(%onnx::Conv_1176)
%onnx::Conv_1182 = Identity(%onnx::Conv_1176)
%onnx::Conv_1179 = Identity(%onnx::Conv_1176)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_1175, %onnx::Conv_1176)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1178, %onnx::Conv_1179)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_1181, %onnx::Conv_1182)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1184, %onnx::Conv_1185)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_1187, %onnx::Conv_1188)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1190, %onnx::Conv_1191)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_1193, %onnx::Conv_1194)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_1196, %onnx::Conv_1197)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1199, %onnx::Conv_1200)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_7_output_0 = Add(%/layers.1/Add_6_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_7_output_0, %onnx::Conv_1202, %onnx::Conv_1203)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1205, %onnx::Conv_1206)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_1208, %onnx::Conv_1209)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1211, %onnx::Conv_1212)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_1214, %onnx::Conv_1215)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1217, %onnx::Conv_1218)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_1220, %onnx::Conv_1221)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1223, %onnx::Conv_1224)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1226, %onnx::Conv_1227)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_7_output_0 = Add(%/layers.2/Add_6_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_7_output_0, %onnx::Conv_1229, %onnx::Conv_1230)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1232, %onnx::Conv_1233)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1235, %onnx::Conv_1236)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1238, %onnx::Conv_1239)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1241, %onnx::Conv_1242)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1244, %onnx::Conv_1245)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1247, %onnx::Conv_1248)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1250, %onnx::Conv_1251)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1253, %onnx::Conv_1254)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_7_output_0 = Add(%/layers.3/Add_6_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_7_output_0, %onnx::Conv_1256, %onnx::Conv_1257)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1259, %onnx::Conv_1260)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1262, %onnx::Conv_1263)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1265, %onnx::Conv_1266)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1268, %onnx::Conv_1269)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1271, %onnx::Conv_1272)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1274, %onnx::Conv_1275)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1277, %onnx::Conv_1278)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1280, %onnx::Conv_1281)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_7_output_0 = Add(%/layers.5/Add_6_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_7_output_0, %onnx::Conv_1283, %onnx::Conv_1284)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1286, %onnx::Conv_1287)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1289, %onnx::Conv_1290)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1292, %onnx::Conv_1293)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1295, %onnx::Conv_1296)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1298, %onnx::Conv_1299)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1301, %onnx::Conv_1302)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1304, %onnx::Conv_1305)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1307, %onnx::Conv_1308)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_7_output_0 = Add(%/layers.6/Add_6_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_7_output_0, %onnx::Conv_1310, %onnx::Conv_1311)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1313, %onnx::Conv_1314)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1316, %onnx::Conv_1317)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1319, %onnx::Conv_1320)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1322, %onnx::Conv_1323)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1325, %onnx::Conv_1326)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1328, %onnx::Conv_1329)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1331, %onnx::Conv_1332)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1334, %onnx::Conv_1335)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_7_output_0 = Add(%/layers.7/Add_6_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_7_output_0, %onnx::Conv_1337, %onnx::Conv_1338)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1340, %onnx::Conv_1341)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1343, %onnx::Conv_1344)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1346, %onnx::Conv_1347)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1349, %onnx::Conv_1350)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1352, %onnx::Conv_1353)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1355, %onnx::Conv_1356)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1358, %onnx::Conv_1359)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1361, %onnx::Conv_1362)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_7_output_0 = Add(%/layers.9/Add_6_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_7_output_0, %onnx::Conv_1364, %onnx::Conv_1365)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1367, %onnx::Conv_1368)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1370, %onnx::Conv_1371)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1373, %onnx::Conv_1374)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1376, %onnx::Conv_1377)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1379, %onnx::Conv_1380)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1382, %onnx::Conv_1383)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1385, %onnx::Conv_1386)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1388, %onnx::Conv_1389)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_7_output_0 = Add(%/layers.10/Add_6_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_7_output_0, %onnx::Conv_1391, %onnx::Conv_1392)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1394, %onnx::Conv_1395)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1397, %onnx::Conv_1398)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1400, %onnx::Conv_1401)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1403, %onnx::Conv_1404)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1406, %onnx::Conv_1407)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1409, %onnx::Conv_1410)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1412, %onnx::Conv_1413)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1415, %onnx::Conv_1416)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_7_output_0 = Add(%/layers.11/Add_6_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_7_output_0, %onnx::Conv_1418, %onnx::Conv_1419)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%1173 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %1173
}
|
val_accuracy
| 81.260014
| 2,641,373,184
| 8,691,594
|
{'zcp_epe_nas': 83.5699178748526, 'zcp_fisher': 5.7578535079956055, 'zcp_flops': 42261970944.0, 'zcp_grad_norm': 69.9152603149414, 'zcp_grasp': -0.7032470703125, 'zcp_jacov': -16.048181778108216, 'zcp_l2_norm': 1845.3663330078125, 'zcp_nwot': 241.78820794366138, 'zcp_params': 8691594.0, 'zcp_plain': 0.013558804057538001, 'zcp_snip': 538.2939453125, 'zcp_synflow': 119.8957911736732, 'zcp_zen': 132.29978942871094, 'zcp_val_accuracy': 0.8848156929016111}
| |
NASBench101_392696
|
NASBench101
|
392696
|
ed61a03fb855938b82551f4255a13387
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_788[FLOAT, 128x3x3x3]
%onnx::Conv_789[FLOAT, 128]
%onnx::Conv_791[FLOAT, 64x128x1x1]
%onnx::Conv_792[FLOAT, 64]
%onnx::Conv_794[FLOAT, 64x64x3x3]
%onnx::Conv_797[FLOAT, 64x128x1x1]
%onnx::Conv_800[FLOAT, 64x64x1x1]
%onnx::Conv_803[FLOAT, 64x128x1x1]
%onnx::Conv_806[FLOAT, 64x128x1x1]
%onnx::Conv_809[FLOAT, 64x64x3x3]
%onnx::Conv_812[FLOAT, 64x128x1x1]
%onnx::Conv_815[FLOAT, 64x64x1x1]
%onnx::Conv_818[FLOAT, 64x128x1x1]
%onnx::Conv_821[FLOAT, 64x128x1x1]
%onnx::Conv_824[FLOAT, 64x64x3x3]
%onnx::Conv_827[FLOAT, 64x128x1x1]
%onnx::Conv_830[FLOAT, 64x64x1x1]
%onnx::Conv_833[FLOAT, 64x128x1x1]
%onnx::Conv_836[FLOAT, 128x128x1x1]
%onnx::Conv_839[FLOAT, 128x128x3x3]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x1x1]
%onnx::Conv_851[FLOAT, 128x256x1x1]
%onnx::Conv_854[FLOAT, 128x128x3x3]
%onnx::Conv_857[FLOAT, 128x256x1x1]
%onnx::Conv_860[FLOAT, 128x128x1x1]
%onnx::Conv_863[FLOAT, 128x256x1x1]
%onnx::Conv_866[FLOAT, 128x256x1x1]
%onnx::Conv_869[FLOAT, 128x128x3x3]
%onnx::Conv_872[FLOAT, 128x256x1x1]
%onnx::Conv_875[FLOAT, 128x128x1x1]
%onnx::Conv_878[FLOAT, 128x256x1x1]
%onnx::Conv_881[FLOAT, 256x256x1x1]
%onnx::Conv_882[FLOAT, 256]
%onnx::Conv_884[FLOAT, 256x256x3x3]
%onnx::Conv_887[FLOAT, 256x256x1x1]
%onnx::Conv_890[FLOAT, 256x256x1x1]
%onnx::Conv_893[FLOAT, 256x256x1x1]
%onnx::Conv_896[FLOAT, 256x512x1x1]
%onnx::Conv_899[FLOAT, 256x256x3x3]
%onnx::Conv_902[FLOAT, 256x512x1x1]
%onnx::Conv_905[FLOAT, 256x256x1x1]
%onnx::Conv_908[FLOAT, 256x512x1x1]
%onnx::Conv_911[FLOAT, 256x512x1x1]
%onnx::Conv_914[FLOAT, 256x256x3x3]
%onnx::Conv_917[FLOAT, 256x512x1x1]
%onnx::Conv_920[FLOAT, 256x256x1x1]
%onnx::Conv_923[FLOAT, 256x512x1x1]
) {
%onnx::Conv_924 = Identity(%onnx::Conv_882)
%onnx::Conv_921 = Identity(%onnx::Conv_882)
%onnx::Conv_918 = Identity(%onnx::Conv_882)
%onnx::Conv_915 = Identity(%onnx::Conv_882)
%onnx::Conv_912 = Identity(%onnx::Conv_882)
%onnx::Conv_909 = Identity(%onnx::Conv_882)
%onnx::Conv_906 = Identity(%onnx::Conv_882)
%onnx::Conv_903 = Identity(%onnx::Conv_882)
%onnx::Conv_900 = Identity(%onnx::Conv_882)
%onnx::Conv_897 = Identity(%onnx::Conv_882)
%onnx::Conv_894 = Identity(%onnx::Conv_882)
%onnx::Conv_891 = Identity(%onnx::Conv_882)
%onnx::Conv_888 = Identity(%onnx::Conv_882)
%onnx::Conv_885 = Identity(%onnx::Conv_882)
%onnx::Conv_879 = Identity(%onnx::Conv_789)
%onnx::Conv_876 = Identity(%onnx::Conv_789)
%onnx::Conv_873 = Identity(%onnx::Conv_789)
%onnx::Conv_870 = Identity(%onnx::Conv_789)
%onnx::Conv_867 = Identity(%onnx::Conv_789)
%onnx::Conv_864 = Identity(%onnx::Conv_789)
%onnx::Conv_861 = Identity(%onnx::Conv_789)
%onnx::Conv_858 = Identity(%onnx::Conv_789)
%onnx::Conv_855 = Identity(%onnx::Conv_789)
%onnx::Conv_852 = Identity(%onnx::Conv_789)
%onnx::Conv_849 = Identity(%onnx::Conv_789)
%onnx::Conv_846 = Identity(%onnx::Conv_789)
%onnx::Conv_843 = Identity(%onnx::Conv_789)
%onnx::Conv_840 = Identity(%onnx::Conv_789)
%onnx::Conv_837 = Identity(%onnx::Conv_789)
%onnx::Conv_834 = Identity(%onnx::Conv_792)
%onnx::Conv_831 = Identity(%onnx::Conv_792)
%onnx::Conv_828 = Identity(%onnx::Conv_792)
%onnx::Conv_825 = Identity(%onnx::Conv_792)
%onnx::Conv_822 = Identity(%onnx::Conv_792)
%onnx::Conv_819 = Identity(%onnx::Conv_792)
%onnx::Conv_816 = Identity(%onnx::Conv_792)
%onnx::Conv_813 = Identity(%onnx::Conv_792)
%onnx::Conv_810 = Identity(%onnx::Conv_792)
%onnx::Conv_807 = Identity(%onnx::Conv_792)
%onnx::Conv_804 = Identity(%onnx::Conv_792)
%onnx::Conv_801 = Identity(%onnx::Conv_792)
%onnx::Conv_798 = Identity(%onnx::Conv_792)
%onnx::Conv_795 = Identity(%onnx::Conv_792)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_788, %onnx::Conv_789)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%786 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %786
}
|
val_accuracy
| 91.215944
| 1,179,527,168
| 3,905,290
|
{'zcp_epe_nas': 104.10782392734768, 'zcp_fisher': 38.395347595214844, 'zcp_flops': 18872434688.0, 'zcp_grad_norm': 121.73855590820312, 'zcp_grasp': -40.2496337890625, 'zcp_jacov': -16.04349450229899, 'zcp_l2_norm': 890.6554565429688, 'zcp_nwot': 221.73264908284372, 'zcp_params': 3905290.0, 'zcp_plain': 0.11602745950222002, 'zcp_snip': 745.3787231445312, 'zcp_synflow': 68.58580939578349, 'zcp_zen': 84.75836181640625, 'zcp_val_accuracy': 0.910957515239715}
| |
NASBench101_423115
|
NASBench101
|
423115
|
ffb0c65acd80e9bf71496f362c25dfce
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_968[FLOAT, 128x3x3x3]
%onnx::Conv_969[FLOAT, 128]
%onnx::Conv_971[FLOAT, 64x128x1x1]
%onnx::Conv_972[FLOAT, 64]
%onnx::Conv_974[FLOAT, 64x64x1x1]
%onnx::Conv_977[FLOAT, 64x128x1x1]
%onnx::Conv_980[FLOAT, 64x128x1x1]
%onnx::Conv_983[FLOAT, 64x64x1x1]
%onnx::Conv_986[FLOAT, 64x64x1x1]
%onnx::Conv_989[FLOAT, 64x64x3x3]
%onnx::Conv_992[FLOAT, 64x128x1x1]
%onnx::Conv_995[FLOAT, 64x64x1x1]
%onnx::Conv_998[FLOAT, 64x128x1x1]
%onnx::Conv_1001[FLOAT, 64x128x1x1]
%onnx::Conv_1004[FLOAT, 64x64x1x1]
%onnx::Conv_1007[FLOAT, 64x64x1x1]
%onnx::Conv_1010[FLOAT, 64x64x3x3]
%onnx::Conv_1013[FLOAT, 64x128x1x1]
%onnx::Conv_1016[FLOAT, 64x64x1x1]
%onnx::Conv_1019[FLOAT, 64x128x1x1]
%onnx::Conv_1022[FLOAT, 64x128x1x1]
%onnx::Conv_1025[FLOAT, 64x64x1x1]
%onnx::Conv_1028[FLOAT, 64x64x1x1]
%onnx::Conv_1031[FLOAT, 64x64x3x3]
%onnx::Conv_1034[FLOAT, 128x128x1x1]
%onnx::Conv_1037[FLOAT, 128x128x1x1]
%onnx::Conv_1040[FLOAT, 128x128x1x1]
%onnx::Conv_1043[FLOAT, 128x128x1x1]
%onnx::Conv_1046[FLOAT, 128x128x1x1]
%onnx::Conv_1049[FLOAT, 128x128x1x1]
%onnx::Conv_1052[FLOAT, 128x128x3x3]
%onnx::Conv_1055[FLOAT, 128x256x1x1]
%onnx::Conv_1058[FLOAT, 128x128x1x1]
%onnx::Conv_1061[FLOAT, 128x256x1x1]
%onnx::Conv_1064[FLOAT, 128x256x1x1]
%onnx::Conv_1067[FLOAT, 128x128x1x1]
%onnx::Conv_1070[FLOAT, 128x128x1x1]
%onnx::Conv_1073[FLOAT, 128x128x3x3]
%onnx::Conv_1076[FLOAT, 128x256x1x1]
%onnx::Conv_1079[FLOAT, 128x128x1x1]
%onnx::Conv_1082[FLOAT, 128x256x1x1]
%onnx::Conv_1085[FLOAT, 128x256x1x1]
%onnx::Conv_1088[FLOAT, 128x128x1x1]
%onnx::Conv_1091[FLOAT, 128x128x1x1]
%onnx::Conv_1094[FLOAT, 128x128x3x3]
%onnx::Conv_1097[FLOAT, 256x256x1x1]
%onnx::Conv_1098[FLOAT, 256]
%onnx::Conv_1100[FLOAT, 256x256x1x1]
%onnx::Conv_1103[FLOAT, 256x256x1x1]
%onnx::Conv_1106[FLOAT, 256x256x1x1]
%onnx::Conv_1109[FLOAT, 256x256x1x1]
%onnx::Conv_1112[FLOAT, 256x256x1x1]
%onnx::Conv_1115[FLOAT, 256x256x3x3]
%onnx::Conv_1118[FLOAT, 256x512x1x1]
%onnx::Conv_1121[FLOAT, 256x256x1x1]
%onnx::Conv_1124[FLOAT, 256x512x1x1]
%onnx::Conv_1127[FLOAT, 256x512x1x1]
%onnx::Conv_1130[FLOAT, 256x256x1x1]
%onnx::Conv_1133[FLOAT, 256x256x1x1]
%onnx::Conv_1136[FLOAT, 256x256x3x3]
%onnx::Conv_1139[FLOAT, 256x512x1x1]
%onnx::Conv_1142[FLOAT, 256x256x1x1]
%onnx::Conv_1145[FLOAT, 256x512x1x1]
%onnx::Conv_1148[FLOAT, 256x512x1x1]
%onnx::Conv_1151[FLOAT, 256x256x1x1]
%onnx::Conv_1154[FLOAT, 256x256x1x1]
%onnx::Conv_1157[FLOAT, 256x256x3x3]
) {
%onnx::Conv_1158 = Identity(%onnx::Conv_1098)
%onnx::Conv_1155 = Identity(%onnx::Conv_1098)
%onnx::Conv_1152 = Identity(%onnx::Conv_1098)
%onnx::Conv_1149 = Identity(%onnx::Conv_1098)
%onnx::Conv_1146 = Identity(%onnx::Conv_1098)
%onnx::Conv_1143 = Identity(%onnx::Conv_1098)
%onnx::Conv_1140 = Identity(%onnx::Conv_1098)
%onnx::Conv_1137 = Identity(%onnx::Conv_1098)
%onnx::Conv_1134 = Identity(%onnx::Conv_1098)
%onnx::Conv_1131 = Identity(%onnx::Conv_1098)
%onnx::Conv_1128 = Identity(%onnx::Conv_1098)
%onnx::Conv_1125 = Identity(%onnx::Conv_1098)
%onnx::Conv_1122 = Identity(%onnx::Conv_1098)
%onnx::Conv_1119 = Identity(%onnx::Conv_1098)
%onnx::Conv_1116 = Identity(%onnx::Conv_1098)
%onnx::Conv_1113 = Identity(%onnx::Conv_1098)
%onnx::Conv_1110 = Identity(%onnx::Conv_1098)
%onnx::Conv_1107 = Identity(%onnx::Conv_1098)
%onnx::Conv_1104 = Identity(%onnx::Conv_1098)
%onnx::Conv_1101 = Identity(%onnx::Conv_1098)
%onnx::Conv_1095 = Identity(%onnx::Conv_969)
%onnx::Conv_1092 = Identity(%onnx::Conv_969)
%onnx::Conv_1089 = Identity(%onnx::Conv_969)
%onnx::Conv_1086 = Identity(%onnx::Conv_969)
%onnx::Conv_1083 = Identity(%onnx::Conv_969)
%onnx::Conv_1080 = Identity(%onnx::Conv_969)
%onnx::Conv_1077 = Identity(%onnx::Conv_969)
%onnx::Conv_1074 = Identity(%onnx::Conv_969)
%onnx::Conv_1071 = Identity(%onnx::Conv_969)
%onnx::Conv_1068 = Identity(%onnx::Conv_969)
%onnx::Conv_1065 = Identity(%onnx::Conv_969)
%onnx::Conv_1062 = Identity(%onnx::Conv_969)
%onnx::Conv_1059 = Identity(%onnx::Conv_969)
%onnx::Conv_1056 = Identity(%onnx::Conv_969)
%onnx::Conv_1053 = Identity(%onnx::Conv_969)
%onnx::Conv_1050 = Identity(%onnx::Conv_969)
%onnx::Conv_1047 = Identity(%onnx::Conv_969)
%onnx::Conv_1044 = Identity(%onnx::Conv_969)
%onnx::Conv_1041 = Identity(%onnx::Conv_969)
%onnx::Conv_1038 = Identity(%onnx::Conv_969)
%onnx::Conv_1035 = Identity(%onnx::Conv_969)
%onnx::Conv_1032 = Identity(%onnx::Conv_972)
%onnx::Conv_1029 = Identity(%onnx::Conv_972)
%onnx::Conv_1026 = Identity(%onnx::Conv_972)
%onnx::Conv_1023 = Identity(%onnx::Conv_972)
%onnx::Conv_1020 = Identity(%onnx::Conv_972)
%onnx::Conv_1017 = Identity(%onnx::Conv_972)
%onnx::Conv_1014 = Identity(%onnx::Conv_972)
%onnx::Conv_1011 = Identity(%onnx::Conv_972)
%onnx::Conv_1008 = Identity(%onnx::Conv_972)
%onnx::Conv_1005 = Identity(%onnx::Conv_972)
%onnx::Conv_1002 = Identity(%onnx::Conv_972)
%onnx::Conv_999 = Identity(%onnx::Conv_972)
%onnx::Conv_996 = Identity(%onnx::Conv_972)
%onnx::Conv_993 = Identity(%onnx::Conv_972)
%onnx::Conv_990 = Identity(%onnx::Conv_972)
%onnx::Conv_987 = Identity(%onnx::Conv_972)
%onnx::Conv_984 = Identity(%onnx::Conv_972)
%onnx::Conv_981 = Identity(%onnx::Conv_972)
%onnx::Conv_978 = Identity(%onnx::Conv_972)
%onnx::Conv_975 = Identity(%onnx::Conv_972)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_968, %onnx::Conv_969)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%966 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %966
}
|
val_accuracy
| 93.329328
| 1,336,027,136
| 4,426,762
|
{'zcp_epe_nas': 47.100357824138186, 'zcp_fisher': 13.478719711303711, 'zcp_flops': 21376434176.0, 'zcp_grad_norm': 87.47252655029297, 'zcp_grasp': -2.77587890625, 'zcp_jacov': -16.060132694971102, 'zcp_l2_norm': 1190.045166015625, 'zcp_nwot': 227.23804859333188, 'zcp_params': 4426762.0, 'zcp_plain': 0.032808110117912, 'zcp_snip': 507.14453125, 'zcp_synflow': 116.99209010609292, 'zcp_zen': 101.1393814086914, 'zcp_val_accuracy': 0.9154647588729851}
| |
NASBench101_46885
|
NASBench101
|
46885
|
1c6e634cabe7116ce099144ae6634d09
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_635[FLOAT, 128x3x3x3]
%onnx::Conv_636[FLOAT, 128]
%onnx::Conv_638[FLOAT, 128x128x1x1]
%onnx::Conv_641[FLOAT, 128x128x3x3]
%onnx::Conv_644[FLOAT, 128x128x1x1]
%onnx::Conv_647[FLOAT, 128x128x3x3]
%onnx::Conv_650[FLOAT, 128x128x1x1]
%onnx::Conv_653[FLOAT, 128x128x3x3]
%onnx::Conv_656[FLOAT, 128x128x1x1]
%onnx::Conv_659[FLOAT, 128x128x3x3]
%onnx::Conv_662[FLOAT, 128x128x1x1]
%onnx::Conv_665[FLOAT, 128x128x3x3]
%onnx::Conv_668[FLOAT, 128x128x1x1]
%onnx::Conv_671[FLOAT, 128x128x3x3]
%onnx::Conv_674[FLOAT, 256x128x1x1]
%onnx::Conv_675[FLOAT, 256]
%onnx::Conv_677[FLOAT, 256x256x3x3]
%onnx::Conv_680[FLOAT, 256x128x1x1]
%onnx::Conv_683[FLOAT, 256x256x3x3]
%onnx::Conv_686[FLOAT, 256x256x1x1]
%onnx::Conv_689[FLOAT, 256x256x3x3]
%onnx::Conv_692[FLOAT, 256x256x1x1]
%onnx::Conv_695[FLOAT, 256x256x3x3]
%onnx::Conv_698[FLOAT, 256x256x1x1]
%onnx::Conv_701[FLOAT, 256x256x3x3]
%onnx::Conv_704[FLOAT, 256x256x1x1]
%onnx::Conv_707[FLOAT, 256x256x3x3]
%onnx::Conv_710[FLOAT, 512x256x1x1]
%onnx::Conv_711[FLOAT, 512]
%onnx::Conv_713[FLOAT, 512x512x3x3]
%onnx::Conv_716[FLOAT, 512x256x1x1]
%onnx::Conv_719[FLOAT, 512x512x3x3]
%onnx::Conv_722[FLOAT, 512x512x1x1]
%onnx::Conv_725[FLOAT, 512x512x3x3]
%onnx::Conv_728[FLOAT, 512x512x1x1]
%onnx::Conv_731[FLOAT, 512x512x3x3]
%onnx::Conv_734[FLOAT, 512x512x1x1]
%onnx::Conv_737[FLOAT, 512x512x3x3]
%onnx::Conv_740[FLOAT, 512x512x1x1]
%onnx::Conv_743[FLOAT, 512x512x3x3]
) {
%onnx::Conv_744 = Identity(%onnx::Conv_711)
%onnx::Conv_741 = Identity(%onnx::Conv_711)
%onnx::Conv_738 = Identity(%onnx::Conv_711)
%onnx::Conv_735 = Identity(%onnx::Conv_711)
%onnx::Conv_732 = Identity(%onnx::Conv_711)
%onnx::Conv_729 = Identity(%onnx::Conv_711)
%onnx::Conv_726 = Identity(%onnx::Conv_711)
%onnx::Conv_723 = Identity(%onnx::Conv_711)
%onnx::Conv_720 = Identity(%onnx::Conv_711)
%onnx::Conv_717 = Identity(%onnx::Conv_711)
%onnx::Conv_714 = Identity(%onnx::Conv_711)
%onnx::Conv_708 = Identity(%onnx::Conv_675)
%onnx::Conv_705 = Identity(%onnx::Conv_675)
%onnx::Conv_702 = Identity(%onnx::Conv_675)
%onnx::Conv_699 = Identity(%onnx::Conv_675)
%onnx::Conv_696 = Identity(%onnx::Conv_675)
%onnx::Conv_693 = Identity(%onnx::Conv_675)
%onnx::Conv_690 = Identity(%onnx::Conv_675)
%onnx::Conv_687 = Identity(%onnx::Conv_675)
%onnx::Conv_684 = Identity(%onnx::Conv_675)
%onnx::Conv_681 = Identity(%onnx::Conv_675)
%onnx::Conv_678 = Identity(%onnx::Conv_675)
%onnx::Conv_672 = Identity(%onnx::Conv_636)
%onnx::Conv_669 = Identity(%onnx::Conv_636)
%onnx::Conv_666 = Identity(%onnx::Conv_636)
%onnx::Conv_663 = Identity(%onnx::Conv_636)
%onnx::Conv_660 = Identity(%onnx::Conv_636)
%onnx::Conv_657 = Identity(%onnx::Conv_636)
%onnx::Conv_654 = Identity(%onnx::Conv_636)
%onnx::Conv_651 = Identity(%onnx::Conv_636)
%onnx::Conv_648 = Identity(%onnx::Conv_636)
%onnx::Conv_645 = Identity(%onnx::Conv_636)
%onnx::Conv_642 = Identity(%onnx::Conv_636)
%onnx::Conv_639 = Identity(%onnx::Conv_636)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_635, %onnx::Conv_636)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_638, %onnx::Conv_639)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_641, %onnx::Conv_642)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_644, %onnx::Conv_645)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_647, %onnx::Conv_648)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_650, %onnx::Conv_651)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_653, %onnx::Conv_654)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_656, %onnx::Conv_657)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_659, %onnx::Conv_660)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_662, %onnx::Conv_663)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%633 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %633
}
|
val_accuracy
| 90.004009
| 6,002,845,696
| 20,346,506
|
{'zcp_epe_nas': 85.67636125900802, 'zcp_fisher': 8.423108100891113, 'zcp_flops': 96045531136.0, 'zcp_grad_norm': 39.41065216064453, 'zcp_grasp': -0.26836395263671803, 'zcp_jacov': -16.06319791124967, 'zcp_l2_norm': 818.91796875, 'zcp_nwot': 227.03752926956312, 'zcp_params': 20346506.0, 'zcp_plain': 0.010304473340511001, 'zcp_snip': 387.07421875, 'zcp_synflow': 103.80583209695548, 'zcp_zen': 89.86479187011719, 'zcp_val_accuracy': 0.901041686534881}
| |
NASBench101_126488
|
NASBench101
|
126488
|
4c67147116d276f55a049c14cc123adc
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_578[FLOAT, 128x3x3x3]
%onnx::Conv_579[FLOAT, 128]
%onnx::Conv_581[FLOAT, 43x128x1x1]
%onnx::Conv_582[FLOAT, 43]
%onnx::Conv_584[FLOAT, 43x43x3x3]
%onnx::Conv_587[FLOAT, 43x43x3x3]
%onnx::Conv_590[FLOAT, 43x128x1x1]
%onnx::Conv_593[FLOAT, 43x43x3x3]
%onnx::Conv_596[FLOAT, 43x43x3x3]
%onnx::Conv_599[FLOAT, 43x128x1x1]
%onnx::Conv_602[FLOAT, 43x43x3x3]
%onnx::Conv_605[FLOAT, 43x43x3x3]
%onnx::Conv_608[FLOAT, 86x128x1x1]
%onnx::Conv_609[FLOAT, 86]
%onnx::Conv_611[FLOAT, 86x86x3x3]
%onnx::Conv_614[FLOAT, 85x85x3x3]
%onnx::Conv_615[FLOAT, 85]
%onnx::Conv_617[FLOAT, 86x256x1x1]
%onnx::Conv_620[FLOAT, 86x86x3x3]
%onnx::Conv_623[FLOAT, 85x85x3x3]
%onnx::Conv_626[FLOAT, 86x256x1x1]
%onnx::Conv_629[FLOAT, 86x86x3x3]
%onnx::Conv_632[FLOAT, 85x85x3x3]
%onnx::Conv_635[FLOAT, 171x256x1x1]
%onnx::Conv_636[FLOAT, 171]
%onnx::Conv_638[FLOAT, 171x171x3x3]
%onnx::Conv_641[FLOAT, 171x171x3x3]
%onnx::Conv_644[FLOAT, 171x512x1x1]
%onnx::Conv_647[FLOAT, 171x171x3x3]
%onnx::Conv_650[FLOAT, 171x171x3x3]
%onnx::Conv_653[FLOAT, 171x512x1x1]
%onnx::Conv_656[FLOAT, 171x171x3x3]
%onnx::Conv_659[FLOAT, 171x171x3x3]
) {
%onnx::Conv_660 = Identity(%onnx::Conv_636)
%onnx::Conv_657 = Identity(%onnx::Conv_636)
%onnx::Conv_654 = Identity(%onnx::Conv_636)
%onnx::Conv_651 = Identity(%onnx::Conv_636)
%onnx::Conv_648 = Identity(%onnx::Conv_636)
%onnx::Conv_645 = Identity(%onnx::Conv_636)
%onnx::Conv_642 = Identity(%onnx::Conv_636)
%onnx::Conv_639 = Identity(%onnx::Conv_636)
%onnx::Conv_633 = Identity(%onnx::Conv_615)
%onnx::Conv_630 = Identity(%onnx::Conv_609)
%onnx::Conv_627 = Identity(%onnx::Conv_609)
%onnx::Conv_624 = Identity(%onnx::Conv_615)
%onnx::Conv_621 = Identity(%onnx::Conv_609)
%onnx::Conv_618 = Identity(%onnx::Conv_609)
%onnx::Conv_612 = Identity(%onnx::Conv_609)
%onnx::Conv_606 = Identity(%onnx::Conv_582)
%onnx::Conv_603 = Identity(%onnx::Conv_582)
%onnx::Conv_600 = Identity(%onnx::Conv_582)
%onnx::Conv_597 = Identity(%onnx::Conv_582)
%onnx::Conv_594 = Identity(%onnx::Conv_582)
%onnx::Conv_591 = Identity(%onnx::Conv_582)
%onnx::Conv_588 = Identity(%onnx::Conv_582)
%onnx::Conv_585 = Identity(%onnx::Conv_582)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_578, %onnx::Conv_579)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_581, %onnx::Conv_582)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_584, %onnx::Conv_585)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_587, %onnx::Conv_588)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_1_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_5_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_590, %onnx::Conv_591)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_593, %onnx::Conv_594)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_596, %onnx::Conv_597)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_1_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_5_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_599, %onnx::Conv_600)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_602, %onnx::Conv_603)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_605, %onnx::Conv_606)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_1_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_5_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_608, %onnx::Conv_609)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_611, %onnx::Conv_612)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_1_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_1_output_0 = Slice(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_6_output_0, %/layers.5/Constant_7_output_0, %/layers.5/Constant_5_output_0, %/layers.5/Constant_8_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Slice_1_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_614, %onnx::Conv_615)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_9_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_9_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_617, %onnx::Conv_618)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_620, %onnx::Conv_621)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_1_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_1_output_0 = Slice(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_6_output_0, %/layers.6/Constant_7_output_0, %/layers.6/Constant_5_output_0, %/layers.6/Constant_8_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Slice_1_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_623, %onnx::Conv_624)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_9_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_9_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_626, %onnx::Conv_627)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_629, %onnx::Conv_630)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_1_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_1_output_0 = Slice(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_6_output_0, %/layers.7/Constant_7_output_0, %/layers.7/Constant_5_output_0, %/layers.7/Constant_8_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Slice_1_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_632, %onnx::Conv_633)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_9_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_9_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_635, %onnx::Conv_636)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_638, %onnx::Conv_639)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_641, %onnx::Conv_642)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_1_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_5_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_644, %onnx::Conv_645)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_647, %onnx::Conv_648)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_650, %onnx::Conv_651)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_1_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_5_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_653, %onnx::Conv_654)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_656, %onnx::Conv_657)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_659, %onnx::Conv_660)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_1_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_5_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%576 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %576
}
|
val_accuracy
| 90.054089
| 712,406,784
| 2,378,295
|
{'zcp_epe_nas': 86.60949655751175, 'zcp_fisher': 12.215852737426758, 'zcp_flops': 11398508544.0, 'zcp_grad_norm': 60.48871612548828, 'zcp_grasp': 0.52093505859375, 'zcp_jacov': -16.059340991691073, 'zcp_l2_norm': 444.6255798339844, 'zcp_nwot': 207.95796189713897, 'zcp_params': 2378295.0, 'zcp_plain': 0.018646357581019003, 'zcp_snip': 315.40509033203125, 'zcp_synflow': 95.15030202029757, 'zcp_zen': 62.283573150634766, 'zcp_val_accuracy': 0.9124599099159241}
| |
NASBench101_211580
|
NASBench101
|
211580
|
8026942273c5fc49d41ab3791f6036e4
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_752[FLOAT, 128x3x3x3]
%onnx::Conv_753[FLOAT, 128]
%onnx::Conv_755[FLOAT, 128x128x1x1]
%onnx::Conv_758[FLOAT, 128x128x3x3]
%onnx::Conv_761[FLOAT, 128x128x3x3]
%onnx::Conv_764[FLOAT, 128x128x1x1]
%onnx::Conv_767[FLOAT, 128x128x1x1]
%onnx::Conv_770[FLOAT, 128x128x1x1]
%onnx::Conv_773[FLOAT, 128x128x3x3]
%onnx::Conv_776[FLOAT, 128x128x3x3]
%onnx::Conv_779[FLOAT, 128x128x1x1]
%onnx::Conv_782[FLOAT, 128x128x1x1]
%onnx::Conv_785[FLOAT, 128x128x1x1]
%onnx::Conv_788[FLOAT, 128x128x3x3]
%onnx::Conv_791[FLOAT, 128x128x3x3]
%onnx::Conv_794[FLOAT, 128x128x1x1]
%onnx::Conv_797[FLOAT, 128x128x1x1]
%onnx::Conv_800[FLOAT, 256x128x1x1]
%onnx::Conv_801[FLOAT, 256]
%onnx::Conv_803[FLOAT, 256x256x3x3]
%onnx::Conv_806[FLOAT, 256x256x3x3]
%onnx::Conv_809[FLOAT, 256x256x1x1]
%onnx::Conv_812[FLOAT, 256x256x1x1]
%onnx::Conv_815[FLOAT, 256x256x1x1]
%onnx::Conv_818[FLOAT, 256x256x3x3]
%onnx::Conv_821[FLOAT, 256x256x3x3]
%onnx::Conv_824[FLOAT, 256x256x1x1]
%onnx::Conv_827[FLOAT, 256x256x1x1]
%onnx::Conv_830[FLOAT, 256x256x1x1]
%onnx::Conv_833[FLOAT, 256x256x3x3]
%onnx::Conv_836[FLOAT, 256x256x3x3]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x256x1x1]
%onnx::Conv_845[FLOAT, 512x256x1x1]
%onnx::Conv_846[FLOAT, 512]
%onnx::Conv_848[FLOAT, 512x512x3x3]
%onnx::Conv_851[FLOAT, 512x512x3x3]
%onnx::Conv_854[FLOAT, 512x512x1x1]
%onnx::Conv_857[FLOAT, 512x512x1x1]
%onnx::Conv_860[FLOAT, 512x512x1x1]
%onnx::Conv_863[FLOAT, 512x512x3x3]
%onnx::Conv_866[FLOAT, 512x512x3x3]
%onnx::Conv_869[FLOAT, 512x512x1x1]
%onnx::Conv_872[FLOAT, 512x512x1x1]
%onnx::Conv_875[FLOAT, 512x512x1x1]
%onnx::Conv_878[FLOAT, 512x512x3x3]
%onnx::Conv_881[FLOAT, 512x512x3x3]
%onnx::Conv_884[FLOAT, 512x512x1x1]
%onnx::Conv_887[FLOAT, 512x512x1x1]
) {
%onnx::Conv_888 = Identity(%onnx::Conv_846)
%onnx::Conv_885 = Identity(%onnx::Conv_846)
%onnx::Conv_882 = Identity(%onnx::Conv_846)
%onnx::Conv_879 = Identity(%onnx::Conv_846)
%onnx::Conv_876 = Identity(%onnx::Conv_846)
%onnx::Conv_873 = Identity(%onnx::Conv_846)
%onnx::Conv_870 = Identity(%onnx::Conv_846)
%onnx::Conv_867 = Identity(%onnx::Conv_846)
%onnx::Conv_864 = Identity(%onnx::Conv_846)
%onnx::Conv_861 = Identity(%onnx::Conv_846)
%onnx::Conv_858 = Identity(%onnx::Conv_846)
%onnx::Conv_855 = Identity(%onnx::Conv_846)
%onnx::Conv_852 = Identity(%onnx::Conv_846)
%onnx::Conv_849 = Identity(%onnx::Conv_846)
%onnx::Conv_843 = Identity(%onnx::Conv_801)
%onnx::Conv_840 = Identity(%onnx::Conv_801)
%onnx::Conv_837 = Identity(%onnx::Conv_801)
%onnx::Conv_834 = Identity(%onnx::Conv_801)
%onnx::Conv_831 = Identity(%onnx::Conv_801)
%onnx::Conv_828 = Identity(%onnx::Conv_801)
%onnx::Conv_825 = Identity(%onnx::Conv_801)
%onnx::Conv_822 = Identity(%onnx::Conv_801)
%onnx::Conv_819 = Identity(%onnx::Conv_801)
%onnx::Conv_816 = Identity(%onnx::Conv_801)
%onnx::Conv_813 = Identity(%onnx::Conv_801)
%onnx::Conv_810 = Identity(%onnx::Conv_801)
%onnx::Conv_807 = Identity(%onnx::Conv_801)
%onnx::Conv_804 = Identity(%onnx::Conv_801)
%onnx::Conv_798 = Identity(%onnx::Conv_753)
%onnx::Conv_795 = Identity(%onnx::Conv_753)
%onnx::Conv_792 = Identity(%onnx::Conv_753)
%onnx::Conv_789 = Identity(%onnx::Conv_753)
%onnx::Conv_786 = Identity(%onnx::Conv_753)
%onnx::Conv_783 = Identity(%onnx::Conv_753)
%onnx::Conv_780 = Identity(%onnx::Conv_753)
%onnx::Conv_777 = Identity(%onnx::Conv_753)
%onnx::Conv_774 = Identity(%onnx::Conv_753)
%onnx::Conv_771 = Identity(%onnx::Conv_753)
%onnx::Conv_768 = Identity(%onnx::Conv_753)
%onnx::Conv_765 = Identity(%onnx::Conv_753)
%onnx::Conv_762 = Identity(%onnx::Conv_753)
%onnx::Conv_759 = Identity(%onnx::Conv_753)
%onnx::Conv_756 = Identity(%onnx::Conv_753)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_752, %onnx::Conv_753)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%750 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %750
}
|
val_accuracy
| 91.075718
| 6,343,895,040
| 21,547,914
|
{'zcp_epe_nas': 68.32431452965776, 'zcp_fisher': 247.3355255126953, 'zcp_flops': 101502320640.0, 'zcp_grad_norm': 252.18756103515625, 'zcp_grasp': 63.34423828125, 'zcp_jacov': -16.066008573865567, 'zcp_l2_norm': 1045.9810791015625, 'zcp_nwot': 231.9911975569838, 'zcp_params': 21547914.0, 'zcp_plain': 0.047054294496774, 'zcp_snip': 2040.1290283203125, 'zcp_synflow': 156.29370917622992, 'zcp_zen': 101.53364562988281, 'zcp_val_accuracy': 0.9008413553237911}
| |
NASBench101_324047
|
NASBench101
|
324047
|
c4122407c2836893a1f041914b3e23a4
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_929[FLOAT, 128x3x3x3]
%onnx::Conv_930[FLOAT, 128]
%onnx::Conv_932[FLOAT, 43x128x1x1]
%onnx::Conv_933[FLOAT, 43]
%onnx::Conv_935[FLOAT, 43x43x3x3]
%onnx::Conv_938[FLOAT, 43x43x3x3]
%onnx::Conv_941[FLOAT, 43x43x1x1]
%onnx::Conv_944[FLOAT, 43x43x3x3]
%onnx::Conv_947[FLOAT, 42x42x3x3]
%onnx::Conv_948[FLOAT, 42]
%onnx::Conv_950[FLOAT, 43x128x1x1]
%onnx::Conv_953[FLOAT, 43x43x3x3]
%onnx::Conv_956[FLOAT, 43x43x3x3]
%onnx::Conv_959[FLOAT, 43x43x1x1]
%onnx::Conv_962[FLOAT, 43x43x3x3]
%onnx::Conv_965[FLOAT, 42x42x3x3]
%onnx::Conv_968[FLOAT, 43x128x1x1]
%onnx::Conv_971[FLOAT, 43x43x3x3]
%onnx::Conv_974[FLOAT, 43x43x3x3]
%onnx::Conv_977[FLOAT, 43x43x1x1]
%onnx::Conv_980[FLOAT, 43x43x3x3]
%onnx::Conv_983[FLOAT, 42x42x3x3]
%onnx::Conv_986[FLOAT, 86x128x1x1]
%onnx::Conv_987[FLOAT, 86]
%onnx::Conv_989[FLOAT, 86x86x3x3]
%onnx::Conv_992[FLOAT, 86x86x3x3]
%onnx::Conv_995[FLOAT, 85x85x1x1]
%onnx::Conv_996[FLOAT, 85]
%onnx::Conv_998[FLOAT, 85x85x3x3]
%onnx::Conv_1001[FLOAT, 85x85x3x3]
%onnx::Conv_1004[FLOAT, 86x256x1x1]
%onnx::Conv_1007[FLOAT, 86x86x3x3]
%onnx::Conv_1010[FLOAT, 86x86x3x3]
%onnx::Conv_1013[FLOAT, 85x85x1x1]
%onnx::Conv_1016[FLOAT, 85x85x3x3]
%onnx::Conv_1019[FLOAT, 85x85x3x3]
%onnx::Conv_1022[FLOAT, 86x256x1x1]
%onnx::Conv_1025[FLOAT, 86x86x3x3]
%onnx::Conv_1028[FLOAT, 86x86x3x3]
%onnx::Conv_1031[FLOAT, 85x85x1x1]
%onnx::Conv_1034[FLOAT, 85x85x3x3]
%onnx::Conv_1037[FLOAT, 85x85x3x3]
%onnx::Conv_1040[FLOAT, 171x256x1x1]
%onnx::Conv_1041[FLOAT, 171]
%onnx::Conv_1043[FLOAT, 171x171x3x3]
%onnx::Conv_1046[FLOAT, 171x171x3x3]
%onnx::Conv_1049[FLOAT, 171x171x1x1]
%onnx::Conv_1052[FLOAT, 171x171x3x3]
%onnx::Conv_1055[FLOAT, 170x170x3x3]
%onnx::Conv_1056[FLOAT, 170]
%onnx::Conv_1058[FLOAT, 171x512x1x1]
%onnx::Conv_1061[FLOAT, 171x171x3x3]
%onnx::Conv_1064[FLOAT, 171x171x3x3]
%onnx::Conv_1067[FLOAT, 171x171x1x1]
%onnx::Conv_1070[FLOAT, 171x171x3x3]
%onnx::Conv_1073[FLOAT, 170x170x3x3]
%onnx::Conv_1076[FLOAT, 171x512x1x1]
%onnx::Conv_1079[FLOAT, 171x171x3x3]
%onnx::Conv_1082[FLOAT, 171x171x3x3]
%onnx::Conv_1085[FLOAT, 171x171x1x1]
%onnx::Conv_1088[FLOAT, 171x171x3x3]
%onnx::Conv_1091[FLOAT, 170x170x3x3]
) {
%onnx::Conv_1092 = Identity(%onnx::Conv_1056)
%onnx::Conv_1089 = Identity(%onnx::Conv_1041)
%onnx::Conv_1086 = Identity(%onnx::Conv_1041)
%onnx::Conv_1083 = Identity(%onnx::Conv_1041)
%onnx::Conv_1080 = Identity(%onnx::Conv_1041)
%onnx::Conv_1077 = Identity(%onnx::Conv_1041)
%onnx::Conv_1074 = Identity(%onnx::Conv_1056)
%onnx::Conv_1071 = Identity(%onnx::Conv_1041)
%onnx::Conv_1068 = Identity(%onnx::Conv_1041)
%onnx::Conv_1065 = Identity(%onnx::Conv_1041)
%onnx::Conv_1062 = Identity(%onnx::Conv_1041)
%onnx::Conv_1059 = Identity(%onnx::Conv_1041)
%onnx::Conv_1053 = Identity(%onnx::Conv_1041)
%onnx::Conv_1050 = Identity(%onnx::Conv_1041)
%onnx::Conv_1047 = Identity(%onnx::Conv_1041)
%onnx::Conv_1044 = Identity(%onnx::Conv_1041)
%onnx::Conv_1038 = Identity(%onnx::Conv_996)
%onnx::Conv_1035 = Identity(%onnx::Conv_996)
%onnx::Conv_1032 = Identity(%onnx::Conv_996)
%onnx::Conv_1029 = Identity(%onnx::Conv_987)
%onnx::Conv_1026 = Identity(%onnx::Conv_987)
%onnx::Conv_1023 = Identity(%onnx::Conv_987)
%onnx::Conv_1020 = Identity(%onnx::Conv_996)
%onnx::Conv_1017 = Identity(%onnx::Conv_996)
%onnx::Conv_1014 = Identity(%onnx::Conv_996)
%onnx::Conv_1011 = Identity(%onnx::Conv_987)
%onnx::Conv_1008 = Identity(%onnx::Conv_987)
%onnx::Conv_1005 = Identity(%onnx::Conv_987)
%onnx::Conv_1002 = Identity(%onnx::Conv_996)
%onnx::Conv_999 = Identity(%onnx::Conv_996)
%onnx::Conv_993 = Identity(%onnx::Conv_987)
%onnx::Conv_990 = Identity(%onnx::Conv_987)
%onnx::Conv_984 = Identity(%onnx::Conv_948)
%onnx::Conv_981 = Identity(%onnx::Conv_933)
%onnx::Conv_978 = Identity(%onnx::Conv_933)
%onnx::Conv_975 = Identity(%onnx::Conv_933)
%onnx::Conv_972 = Identity(%onnx::Conv_933)
%onnx::Conv_969 = Identity(%onnx::Conv_933)
%onnx::Conv_966 = Identity(%onnx::Conv_948)
%onnx::Conv_963 = Identity(%onnx::Conv_933)
%onnx::Conv_960 = Identity(%onnx::Conv_933)
%onnx::Conv_957 = Identity(%onnx::Conv_933)
%onnx::Conv_954 = Identity(%onnx::Conv_933)
%onnx::Conv_951 = Identity(%onnx::Conv_933)
%onnx::Conv_945 = Identity(%onnx::Conv_933)
%onnx::Conv_942 = Identity(%onnx::Conv_933)
%onnx::Conv_939 = Identity(%onnx::Conv_933)
%onnx::Conv_936 = Identity(%onnx::Conv_933)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_929, %onnx::Conv_930)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_6_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_7_output_0)
%/layers.1/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_8_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_6_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_7_output_0)
%/layers.2/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_8_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_6_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_7_output_0)
%/layers.3/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_8_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_4_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_1_output_0 = Slice(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_8_output_0, %/layers.5/Constant_9_output_0, %/layers.5/Constant_7_output_0, %/layers.5/Constant_10_output_0)
%/layers.5/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/Slice_1_output_0, %/layers.5/Constant_11_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_12_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_4_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_1_output_0 = Slice(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_8_output_0, %/layers.6/Constant_9_output_0, %/layers.6/Constant_7_output_0, %/layers.6/Constant_10_output_0)
%/layers.6/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/Slice_1_output_0, %/layers.6/Constant_11_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_12_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_4_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_1_output_0 = Slice(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_8_output_0, %/layers.7/Constant_9_output_0, %/layers.7/Constant_7_output_0, %/layers.7/Constant_10_output_0)
%/layers.7/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/Slice_1_output_0, %/layers.7/Constant_11_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_12_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_6_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_7_output_0)
%/layers.9/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_8_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_6_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_7_output_0)
%/layers.10/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_8_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_6_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_7_output_0)
%/layers.11/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_8_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%927 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %927
}
|
val_accuracy
| 92.217547
| 1,354,438,656
| 4,560,741
|
{'zcp_epe_nas': 100.00707670124403, 'zcp_fisher': 79.59013366699219, 'zcp_flops': 21671018496.0, 'zcp_grad_norm': 167.30230712890625, 'zcp_grasp': 42.5703125, 'zcp_jacov': -16.047897746111666, 'zcp_l2_norm': 811.6779174804688, 'zcp_nwot': 218.38616707444652, 'zcp_params': 4560741.0, 'zcp_plain': 0.011039582081139001, 'zcp_snip': 809.7750244140625, 'zcp_synflow': 141.11733478115153, 'zcp_zen': 100.99131774902344, 'zcp_val_accuracy': 0.9004406929016111}
| |
NASBench101_362237
|
NASBench101
|
362237
|
daf866b2cc5d0d9a992dba2737746bc3
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_761[FLOAT, 128x3x3x3]
%onnx::Conv_762[FLOAT, 128]
%onnx::Conv_764[FLOAT, 64x128x1x1]
%onnx::Conv_765[FLOAT, 64]
%onnx::Conv_767[FLOAT, 64x64x1x1]
%onnx::Conv_770[FLOAT, 64x128x1x1]
%onnx::Conv_773[FLOAT, 64x64x1x1]
%onnx::Conv_776[FLOAT, 64x64x3x3]
%onnx::Conv_779[FLOAT, 64x128x1x1]
%onnx::Conv_782[FLOAT, 64x64x1x1]
%onnx::Conv_785[FLOAT, 64x128x1x1]
%onnx::Conv_788[FLOAT, 64x64x1x1]
%onnx::Conv_791[FLOAT, 64x64x3x3]
%onnx::Conv_794[FLOAT, 64x128x1x1]
%onnx::Conv_797[FLOAT, 64x64x1x1]
%onnx::Conv_800[FLOAT, 64x128x1x1]
%onnx::Conv_803[FLOAT, 64x64x1x1]
%onnx::Conv_806[FLOAT, 64x64x3x3]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 128x128x1x1]
%onnx::Conv_818[FLOAT, 128x128x1x1]
%onnx::Conv_821[FLOAT, 128x128x3x3]
%onnx::Conv_824[FLOAT, 128x256x1x1]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 128x256x1x1]
%onnx::Conv_833[FLOAT, 128x128x1x1]
%onnx::Conv_836[FLOAT, 128x128x3x3]
%onnx::Conv_839[FLOAT, 128x256x1x1]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 128x256x1x1]
%onnx::Conv_848[FLOAT, 128x128x1x1]
%onnx::Conv_851[FLOAT, 128x128x3x3]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_855[FLOAT, 256]
%onnx::Conv_857[FLOAT, 256x256x1x1]
%onnx::Conv_860[FLOAT, 256x256x1x1]
%onnx::Conv_863[FLOAT, 256x256x1x1]
%onnx::Conv_866[FLOAT, 256x256x3x3]
%onnx::Conv_869[FLOAT, 256x512x1x1]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_875[FLOAT, 256x512x1x1]
%onnx::Conv_878[FLOAT, 256x256x1x1]
%onnx::Conv_881[FLOAT, 256x256x3x3]
%onnx::Conv_884[FLOAT, 256x512x1x1]
%onnx::Conv_887[FLOAT, 256x256x1x1]
%onnx::Conv_890[FLOAT, 256x512x1x1]
%onnx::Conv_893[FLOAT, 256x256x1x1]
%onnx::Conv_896[FLOAT, 256x256x3x3]
) {
%onnx::Conv_897 = Identity(%onnx::Conv_855)
%onnx::Conv_894 = Identity(%onnx::Conv_855)
%onnx::Conv_891 = Identity(%onnx::Conv_855)
%onnx::Conv_888 = Identity(%onnx::Conv_855)
%onnx::Conv_885 = Identity(%onnx::Conv_855)
%onnx::Conv_882 = Identity(%onnx::Conv_855)
%onnx::Conv_879 = Identity(%onnx::Conv_855)
%onnx::Conv_876 = Identity(%onnx::Conv_855)
%onnx::Conv_873 = Identity(%onnx::Conv_855)
%onnx::Conv_870 = Identity(%onnx::Conv_855)
%onnx::Conv_867 = Identity(%onnx::Conv_855)
%onnx::Conv_864 = Identity(%onnx::Conv_855)
%onnx::Conv_861 = Identity(%onnx::Conv_855)
%onnx::Conv_858 = Identity(%onnx::Conv_855)
%onnx::Conv_852 = Identity(%onnx::Conv_762)
%onnx::Conv_849 = Identity(%onnx::Conv_762)
%onnx::Conv_846 = Identity(%onnx::Conv_762)
%onnx::Conv_843 = Identity(%onnx::Conv_762)
%onnx::Conv_840 = Identity(%onnx::Conv_762)
%onnx::Conv_837 = Identity(%onnx::Conv_762)
%onnx::Conv_834 = Identity(%onnx::Conv_762)
%onnx::Conv_831 = Identity(%onnx::Conv_762)
%onnx::Conv_828 = Identity(%onnx::Conv_762)
%onnx::Conv_825 = Identity(%onnx::Conv_762)
%onnx::Conv_822 = Identity(%onnx::Conv_762)
%onnx::Conv_819 = Identity(%onnx::Conv_762)
%onnx::Conv_816 = Identity(%onnx::Conv_762)
%onnx::Conv_813 = Identity(%onnx::Conv_762)
%onnx::Conv_810 = Identity(%onnx::Conv_762)
%onnx::Conv_807 = Identity(%onnx::Conv_765)
%onnx::Conv_804 = Identity(%onnx::Conv_765)
%onnx::Conv_801 = Identity(%onnx::Conv_765)
%onnx::Conv_798 = Identity(%onnx::Conv_765)
%onnx::Conv_795 = Identity(%onnx::Conv_765)
%onnx::Conv_792 = Identity(%onnx::Conv_765)
%onnx::Conv_789 = Identity(%onnx::Conv_765)
%onnx::Conv_786 = Identity(%onnx::Conv_765)
%onnx::Conv_783 = Identity(%onnx::Conv_765)
%onnx::Conv_780 = Identity(%onnx::Conv_765)
%onnx::Conv_777 = Identity(%onnx::Conv_765)
%onnx::Conv_774 = Identity(%onnx::Conv_765)
%onnx::Conv_771 = Identity(%onnx::Conv_765)
%onnx::Conv_768 = Identity(%onnx::Conv_765)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_761, %onnx::Conv_762)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%759 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %759
}
|
val_accuracy
| 93.369389
| 1,120,806,912
| 3,729,162
|
{'zcp_epe_nas': 147.5723291897784, 'zcp_fisher': 3.321772336959839, 'zcp_flops': 17932910592.0, 'zcp_grad_norm': 34.479217529296875, 'zcp_grasp': 1.090896606445312, 'zcp_jacov': -16.0696504298228, 'zcp_l2_norm': 843.8839111328125, 'zcp_nwot': 221.58952323626016, 'zcp_params': 3729162.0, 'zcp_plain': -0.002045216737315, 'zcp_snip': 204.50201416015625, 'zcp_synflow': 90.66492691207975, 'zcp_zen': 78.30909729003906, 'zcp_val_accuracy': 0.09505208581686}
| |
NASBench101_353530
|
NASBench101
|
353530
|
d5b3243e6831f467b78acd68724fde82
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_950[FLOAT, 128x3x3x3]
%onnx::Conv_951[FLOAT, 128]
%onnx::Conv_953[FLOAT, 128x128x1x1]
%onnx::Conv_956[FLOAT, 128x128x1x1]
%onnx::Conv_959[FLOAT, 128x128x1x1]
%onnx::Conv_962[FLOAT, 128x128x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x128x3x3]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 128x128x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x128x1x1]
%onnx::Conv_989[FLOAT, 128x128x3x3]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x1x1]
%onnx::Conv_998[FLOAT, 128x128x1x1]
%onnx::Conv_1001[FLOAT, 128x128x1x1]
%onnx::Conv_1004[FLOAT, 128x128x1x1]
%onnx::Conv_1007[FLOAT, 128x128x1x1]
%onnx::Conv_1010[FLOAT, 128x128x3x3]
%onnx::Conv_1013[FLOAT, 128x128x1x1]
%onnx::Conv_1016[FLOAT, 256x128x1x1]
%onnx::Conv_1017[FLOAT, 256]
%onnx::Conv_1019[FLOAT, 256x256x1x1]
%onnx::Conv_1022[FLOAT, 256x128x1x1]
%onnx::Conv_1025[FLOAT, 256x256x1x1]
%onnx::Conv_1028[FLOAT, 256x128x1x1]
%onnx::Conv_1031[FLOAT, 256x256x3x3]
%onnx::Conv_1034[FLOAT, 256x128x1x1]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 256x256x1x1]
%onnx::Conv_1043[FLOAT, 256x256x1x1]
%onnx::Conv_1046[FLOAT, 256x256x1x1]
%onnx::Conv_1049[FLOAT, 256x256x1x1]
%onnx::Conv_1052[FLOAT, 256x256x3x3]
%onnx::Conv_1055[FLOAT, 256x256x1x1]
%onnx::Conv_1058[FLOAT, 256x256x1x1]
%onnx::Conv_1061[FLOAT, 256x256x1x1]
%onnx::Conv_1064[FLOAT, 256x256x1x1]
%onnx::Conv_1067[FLOAT, 256x256x1x1]
%onnx::Conv_1070[FLOAT, 256x256x1x1]
%onnx::Conv_1073[FLOAT, 256x256x3x3]
%onnx::Conv_1076[FLOAT, 256x256x1x1]
%onnx::Conv_1079[FLOAT, 512x256x1x1]
%onnx::Conv_1080[FLOAT, 512]
%onnx::Conv_1082[FLOAT, 512x512x1x1]
%onnx::Conv_1085[FLOAT, 512x256x1x1]
%onnx::Conv_1088[FLOAT, 512x512x1x1]
%onnx::Conv_1091[FLOAT, 512x256x1x1]
%onnx::Conv_1094[FLOAT, 512x512x3x3]
%onnx::Conv_1097[FLOAT, 512x256x1x1]
%onnx::Conv_1100[FLOAT, 512x512x1x1]
%onnx::Conv_1103[FLOAT, 512x512x1x1]
%onnx::Conv_1106[FLOAT, 512x512x1x1]
%onnx::Conv_1109[FLOAT, 512x512x1x1]
%onnx::Conv_1112[FLOAT, 512x512x1x1]
%onnx::Conv_1115[FLOAT, 512x512x3x3]
%onnx::Conv_1118[FLOAT, 512x512x1x1]
%onnx::Conv_1121[FLOAT, 512x512x1x1]
%onnx::Conv_1124[FLOAT, 512x512x1x1]
%onnx::Conv_1127[FLOAT, 512x512x1x1]
%onnx::Conv_1130[FLOAT, 512x512x1x1]
%onnx::Conv_1133[FLOAT, 512x512x1x1]
%onnx::Conv_1136[FLOAT, 512x512x3x3]
%onnx::Conv_1139[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1140 = Identity(%onnx::Conv_1080)
%onnx::Conv_1137 = Identity(%onnx::Conv_1080)
%onnx::Conv_1134 = Identity(%onnx::Conv_1080)
%onnx::Conv_1131 = Identity(%onnx::Conv_1080)
%onnx::Conv_1128 = Identity(%onnx::Conv_1080)
%onnx::Conv_1125 = Identity(%onnx::Conv_1080)
%onnx::Conv_1122 = Identity(%onnx::Conv_1080)
%onnx::Conv_1119 = Identity(%onnx::Conv_1080)
%onnx::Conv_1116 = Identity(%onnx::Conv_1080)
%onnx::Conv_1113 = Identity(%onnx::Conv_1080)
%onnx::Conv_1110 = Identity(%onnx::Conv_1080)
%onnx::Conv_1107 = Identity(%onnx::Conv_1080)
%onnx::Conv_1104 = Identity(%onnx::Conv_1080)
%onnx::Conv_1101 = Identity(%onnx::Conv_1080)
%onnx::Conv_1098 = Identity(%onnx::Conv_1080)
%onnx::Conv_1095 = Identity(%onnx::Conv_1080)
%onnx::Conv_1092 = Identity(%onnx::Conv_1080)
%onnx::Conv_1089 = Identity(%onnx::Conv_1080)
%onnx::Conv_1086 = Identity(%onnx::Conv_1080)
%onnx::Conv_1083 = Identity(%onnx::Conv_1080)
%onnx::Conv_1077 = Identity(%onnx::Conv_1017)
%onnx::Conv_1074 = Identity(%onnx::Conv_1017)
%onnx::Conv_1071 = Identity(%onnx::Conv_1017)
%onnx::Conv_1068 = Identity(%onnx::Conv_1017)
%onnx::Conv_1065 = Identity(%onnx::Conv_1017)
%onnx::Conv_1062 = Identity(%onnx::Conv_1017)
%onnx::Conv_1059 = Identity(%onnx::Conv_1017)
%onnx::Conv_1056 = Identity(%onnx::Conv_1017)
%onnx::Conv_1053 = Identity(%onnx::Conv_1017)
%onnx::Conv_1050 = Identity(%onnx::Conv_1017)
%onnx::Conv_1047 = Identity(%onnx::Conv_1017)
%onnx::Conv_1044 = Identity(%onnx::Conv_1017)
%onnx::Conv_1041 = Identity(%onnx::Conv_1017)
%onnx::Conv_1038 = Identity(%onnx::Conv_1017)
%onnx::Conv_1035 = Identity(%onnx::Conv_1017)
%onnx::Conv_1032 = Identity(%onnx::Conv_1017)
%onnx::Conv_1029 = Identity(%onnx::Conv_1017)
%onnx::Conv_1026 = Identity(%onnx::Conv_1017)
%onnx::Conv_1023 = Identity(%onnx::Conv_1017)
%onnx::Conv_1020 = Identity(%onnx::Conv_1017)
%onnx::Conv_1014 = Identity(%onnx::Conv_951)
%onnx::Conv_1011 = Identity(%onnx::Conv_951)
%onnx::Conv_1008 = Identity(%onnx::Conv_951)
%onnx::Conv_1005 = Identity(%onnx::Conv_951)
%onnx::Conv_1002 = Identity(%onnx::Conv_951)
%onnx::Conv_999 = Identity(%onnx::Conv_951)
%onnx::Conv_996 = Identity(%onnx::Conv_951)
%onnx::Conv_993 = Identity(%onnx::Conv_951)
%onnx::Conv_990 = Identity(%onnx::Conv_951)
%onnx::Conv_987 = Identity(%onnx::Conv_951)
%onnx::Conv_984 = Identity(%onnx::Conv_951)
%onnx::Conv_981 = Identity(%onnx::Conv_951)
%onnx::Conv_978 = Identity(%onnx::Conv_951)
%onnx::Conv_975 = Identity(%onnx::Conv_951)
%onnx::Conv_972 = Identity(%onnx::Conv_951)
%onnx::Conv_969 = Identity(%onnx::Conv_951)
%onnx::Conv_966 = Identity(%onnx::Conv_951)
%onnx::Conv_963 = Identity(%onnx::Conv_951)
%onnx::Conv_960 = Identity(%onnx::Conv_951)
%onnx::Conv_957 = Identity(%onnx::Conv_951)
%onnx::Conv_954 = Identity(%onnx::Conv_951)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_950, %onnx::Conv_951)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_6_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_6_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_6_output_0)
%948 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %948
}
|
val_accuracy
| 92.948717
| 4,442,302,464
| 14,873,994
|
{'zcp_epe_nas': 106.20363003824649, 'zcp_fisher': 52.99847412109375, 'zcp_flops': 71076839424.0, 'zcp_grad_norm': 145.11007690429688, 'zcp_grasp': -6.00634765625, 'zcp_jacov': -16.057328800075357, 'zcp_l2_norm': 1422.9971923828125, 'zcp_nwot': 237.5498266603775, 'zcp_params': 14873994.0, 'zcp_plain': -0.041789788752794, 'zcp_snip': 1174.7823486328125, 'zcp_synflow': 120.45857462111812, 'zcp_zen': 126.2541275024414, 'zcp_val_accuracy': 0.9199719429016111}
| |
NASBench101_152259
|
NASBench101
|
152259
|
5c21e976cfa53106991ac65b5571b84f
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_842[FLOAT, 128x3x3x3]
%onnx::Conv_843[FLOAT, 128]
%onnx::Conv_845[FLOAT, 64x128x1x1]
%onnx::Conv_846[FLOAT, 64]
%onnx::Conv_848[FLOAT, 64x64x1x1]
%onnx::Conv_851[FLOAT, 64x128x1x1]
%onnx::Conv_854[FLOAT, 64x64x1x1]
%onnx::Conv_857[FLOAT, 64x128x1x1]
%onnx::Conv_860[FLOAT, 64x64x3x3]
%onnx::Conv_863[FLOAT, 64x128x1x1]
%onnx::Conv_866[FLOAT, 64x64x1x1]
%onnx::Conv_869[FLOAT, 64x128x1x1]
%onnx::Conv_872[FLOAT, 64x64x1x1]
%onnx::Conv_875[FLOAT, 64x128x1x1]
%onnx::Conv_878[FLOAT, 64x64x3x3]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_884[FLOAT, 64x64x1x1]
%onnx::Conv_887[FLOAT, 64x128x1x1]
%onnx::Conv_890[FLOAT, 64x64x1x1]
%onnx::Conv_893[FLOAT, 64x128x1x1]
%onnx::Conv_896[FLOAT, 64x64x3x3]
%onnx::Conv_899[FLOAT, 128x128x1x1]
%onnx::Conv_902[FLOAT, 128x128x1x1]
%onnx::Conv_905[FLOAT, 128x128x1x1]
%onnx::Conv_908[FLOAT, 128x128x1x1]
%onnx::Conv_911[FLOAT, 128x128x1x1]
%onnx::Conv_914[FLOAT, 128x128x3x3]
%onnx::Conv_917[FLOAT, 128x256x1x1]
%onnx::Conv_920[FLOAT, 128x128x1x1]
%onnx::Conv_923[FLOAT, 128x256x1x1]
%onnx::Conv_926[FLOAT, 128x128x1x1]
%onnx::Conv_929[FLOAT, 128x256x1x1]
%onnx::Conv_932[FLOAT, 128x128x3x3]
%onnx::Conv_935[FLOAT, 128x256x1x1]
%onnx::Conv_938[FLOAT, 128x128x1x1]
%onnx::Conv_941[FLOAT, 128x256x1x1]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x256x1x1]
%onnx::Conv_950[FLOAT, 128x128x3x3]
%onnx::Conv_953[FLOAT, 256x256x1x1]
%onnx::Conv_954[FLOAT, 256]
%onnx::Conv_956[FLOAT, 256x256x1x1]
%onnx::Conv_959[FLOAT, 256x256x1x1]
%onnx::Conv_962[FLOAT, 256x256x1x1]
%onnx::Conv_965[FLOAT, 256x256x1x1]
%onnx::Conv_968[FLOAT, 256x256x3x3]
%onnx::Conv_971[FLOAT, 256x512x1x1]
%onnx::Conv_974[FLOAT, 256x256x1x1]
%onnx::Conv_977[FLOAT, 256x512x1x1]
%onnx::Conv_980[FLOAT, 256x256x1x1]
%onnx::Conv_983[FLOAT, 256x512x1x1]
%onnx::Conv_986[FLOAT, 256x256x3x3]
%onnx::Conv_989[FLOAT, 256x512x1x1]
%onnx::Conv_992[FLOAT, 256x256x1x1]
%onnx::Conv_995[FLOAT, 256x512x1x1]
%onnx::Conv_998[FLOAT, 256x256x1x1]
%onnx::Conv_1001[FLOAT, 256x512x1x1]
%onnx::Conv_1004[FLOAT, 256x256x3x3]
) {
%onnx::Conv_1005 = Identity(%onnx::Conv_954)
%onnx::Conv_1002 = Identity(%onnx::Conv_954)
%onnx::Conv_999 = Identity(%onnx::Conv_954)
%onnx::Conv_996 = Identity(%onnx::Conv_954)
%onnx::Conv_993 = Identity(%onnx::Conv_954)
%onnx::Conv_990 = Identity(%onnx::Conv_954)
%onnx::Conv_987 = Identity(%onnx::Conv_954)
%onnx::Conv_984 = Identity(%onnx::Conv_954)
%onnx::Conv_981 = Identity(%onnx::Conv_954)
%onnx::Conv_978 = Identity(%onnx::Conv_954)
%onnx::Conv_975 = Identity(%onnx::Conv_954)
%onnx::Conv_972 = Identity(%onnx::Conv_954)
%onnx::Conv_969 = Identity(%onnx::Conv_954)
%onnx::Conv_966 = Identity(%onnx::Conv_954)
%onnx::Conv_963 = Identity(%onnx::Conv_954)
%onnx::Conv_960 = Identity(%onnx::Conv_954)
%onnx::Conv_957 = Identity(%onnx::Conv_954)
%onnx::Conv_951 = Identity(%onnx::Conv_843)
%onnx::Conv_948 = Identity(%onnx::Conv_843)
%onnx::Conv_945 = Identity(%onnx::Conv_843)
%onnx::Conv_942 = Identity(%onnx::Conv_843)
%onnx::Conv_939 = Identity(%onnx::Conv_843)
%onnx::Conv_936 = Identity(%onnx::Conv_843)
%onnx::Conv_933 = Identity(%onnx::Conv_843)
%onnx::Conv_930 = Identity(%onnx::Conv_843)
%onnx::Conv_927 = Identity(%onnx::Conv_843)
%onnx::Conv_924 = Identity(%onnx::Conv_843)
%onnx::Conv_921 = Identity(%onnx::Conv_843)
%onnx::Conv_918 = Identity(%onnx::Conv_843)
%onnx::Conv_915 = Identity(%onnx::Conv_843)
%onnx::Conv_912 = Identity(%onnx::Conv_843)
%onnx::Conv_909 = Identity(%onnx::Conv_843)
%onnx::Conv_906 = Identity(%onnx::Conv_843)
%onnx::Conv_903 = Identity(%onnx::Conv_843)
%onnx::Conv_900 = Identity(%onnx::Conv_843)
%onnx::Conv_897 = Identity(%onnx::Conv_846)
%onnx::Conv_894 = Identity(%onnx::Conv_846)
%onnx::Conv_891 = Identity(%onnx::Conv_846)
%onnx::Conv_888 = Identity(%onnx::Conv_846)
%onnx::Conv_885 = Identity(%onnx::Conv_846)
%onnx::Conv_882 = Identity(%onnx::Conv_846)
%onnx::Conv_879 = Identity(%onnx::Conv_846)
%onnx::Conv_876 = Identity(%onnx::Conv_846)
%onnx::Conv_873 = Identity(%onnx::Conv_846)
%onnx::Conv_870 = Identity(%onnx::Conv_846)
%onnx::Conv_867 = Identity(%onnx::Conv_846)
%onnx::Conv_864 = Identity(%onnx::Conv_846)
%onnx::Conv_861 = Identity(%onnx::Conv_846)
%onnx::Conv_858 = Identity(%onnx::Conv_846)
%onnx::Conv_855 = Identity(%onnx::Conv_846)
%onnx::Conv_852 = Identity(%onnx::Conv_846)
%onnx::Conv_849 = Identity(%onnx::Conv_846)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_842, %onnx::Conv_843)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%840 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %840
}
|
val_accuracy
| 91.346157
| 1,257,777,152
| 4,166,026
|
{'zcp_epe_nas': 72.61169489729274, 'zcp_fisher': 14.712626457214355, 'zcp_flops': 20124434432.0, 'zcp_grad_norm': 66.62895202636719, 'zcp_grasp': -0.166015625, 'zcp_jacov': -16.063424075921304, 'zcp_l2_norm': 1039.765380859375, 'zcp_nwot': 223.99393093183494, 'zcp_params': 4166026.0, 'zcp_plain': -0.026815256103873003, 'zcp_snip': 413.6240234375, 'zcp_synflow': 87.86429738576133, 'zcp_zen': 95.25542449951172, 'zcp_val_accuracy': 0.9320913553237911}
| |
NASBench101_277329
|
NASBench101
|
277329
|
a7d9e9ec5d9c9eb10417178e74d2fe04
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_788[FLOAT, 128x3x3x3]
%onnx::Conv_789[FLOAT, 128]
%onnx::Conv_791[FLOAT, 64x128x1x1]
%onnx::Conv_792[FLOAT, 64]
%onnx::Conv_794[FLOAT, 64x64x3x3]
%onnx::Conv_797[FLOAT, 64x64x1x1]
%onnx::Conv_800[FLOAT, 64x64x1x1]
%onnx::Conv_803[FLOAT, 64x64x1x1]
%onnx::Conv_806[FLOAT, 64x128x1x1]
%onnx::Conv_809[FLOAT, 64x64x3x3]
%onnx::Conv_812[FLOAT, 64x64x1x1]
%onnx::Conv_815[FLOAT, 64x64x1x1]
%onnx::Conv_818[FLOAT, 64x64x1x1]
%onnx::Conv_821[FLOAT, 64x128x1x1]
%onnx::Conv_824[FLOAT, 64x64x3x3]
%onnx::Conv_827[FLOAT, 64x64x1x1]
%onnx::Conv_830[FLOAT, 64x64x1x1]
%onnx::Conv_833[FLOAT, 64x64x1x1]
%onnx::Conv_836[FLOAT, 128x128x1x1]
%onnx::Conv_839[FLOAT, 128x128x3x3]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x1x1]
%onnx::Conv_851[FLOAT, 128x256x1x1]
%onnx::Conv_854[FLOAT, 128x128x3x3]
%onnx::Conv_857[FLOAT, 128x128x1x1]
%onnx::Conv_860[FLOAT, 128x128x1x1]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%onnx::Conv_866[FLOAT, 128x256x1x1]
%onnx::Conv_869[FLOAT, 128x128x3x3]
%onnx::Conv_872[FLOAT, 128x128x1x1]
%onnx::Conv_875[FLOAT, 128x128x1x1]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 256x256x1x1]
%onnx::Conv_882[FLOAT, 256]
%onnx::Conv_884[FLOAT, 256x256x3x3]
%onnx::Conv_887[FLOAT, 256x256x1x1]
%onnx::Conv_890[FLOAT, 256x256x1x1]
%onnx::Conv_893[FLOAT, 256x256x1x1]
%onnx::Conv_896[FLOAT, 256x512x1x1]
%onnx::Conv_899[FLOAT, 256x256x3x3]
%onnx::Conv_902[FLOAT, 256x256x1x1]
%onnx::Conv_905[FLOAT, 256x256x1x1]
%onnx::Conv_908[FLOAT, 256x256x1x1]
%onnx::Conv_911[FLOAT, 256x512x1x1]
%onnx::Conv_914[FLOAT, 256x256x3x3]
%onnx::Conv_917[FLOAT, 256x256x1x1]
%onnx::Conv_920[FLOAT, 256x256x1x1]
%onnx::Conv_923[FLOAT, 256x256x1x1]
) {
%onnx::Conv_924 = Identity(%onnx::Conv_882)
%onnx::Conv_921 = Identity(%onnx::Conv_882)
%onnx::Conv_918 = Identity(%onnx::Conv_882)
%onnx::Conv_915 = Identity(%onnx::Conv_882)
%onnx::Conv_912 = Identity(%onnx::Conv_882)
%onnx::Conv_909 = Identity(%onnx::Conv_882)
%onnx::Conv_906 = Identity(%onnx::Conv_882)
%onnx::Conv_903 = Identity(%onnx::Conv_882)
%onnx::Conv_900 = Identity(%onnx::Conv_882)
%onnx::Conv_897 = Identity(%onnx::Conv_882)
%onnx::Conv_894 = Identity(%onnx::Conv_882)
%onnx::Conv_891 = Identity(%onnx::Conv_882)
%onnx::Conv_888 = Identity(%onnx::Conv_882)
%onnx::Conv_885 = Identity(%onnx::Conv_882)
%onnx::Conv_879 = Identity(%onnx::Conv_789)
%onnx::Conv_876 = Identity(%onnx::Conv_789)
%onnx::Conv_873 = Identity(%onnx::Conv_789)
%onnx::Conv_870 = Identity(%onnx::Conv_789)
%onnx::Conv_867 = Identity(%onnx::Conv_789)
%onnx::Conv_864 = Identity(%onnx::Conv_789)
%onnx::Conv_861 = Identity(%onnx::Conv_789)
%onnx::Conv_858 = Identity(%onnx::Conv_789)
%onnx::Conv_855 = Identity(%onnx::Conv_789)
%onnx::Conv_852 = Identity(%onnx::Conv_789)
%onnx::Conv_849 = Identity(%onnx::Conv_789)
%onnx::Conv_846 = Identity(%onnx::Conv_789)
%onnx::Conv_843 = Identity(%onnx::Conv_789)
%onnx::Conv_840 = Identity(%onnx::Conv_789)
%onnx::Conv_837 = Identity(%onnx::Conv_789)
%onnx::Conv_834 = Identity(%onnx::Conv_792)
%onnx::Conv_831 = Identity(%onnx::Conv_792)
%onnx::Conv_828 = Identity(%onnx::Conv_792)
%onnx::Conv_825 = Identity(%onnx::Conv_792)
%onnx::Conv_822 = Identity(%onnx::Conv_792)
%onnx::Conv_819 = Identity(%onnx::Conv_792)
%onnx::Conv_816 = Identity(%onnx::Conv_792)
%onnx::Conv_813 = Identity(%onnx::Conv_792)
%onnx::Conv_810 = Identity(%onnx::Conv_792)
%onnx::Conv_807 = Identity(%onnx::Conv_792)
%onnx::Conv_804 = Identity(%onnx::Conv_792)
%onnx::Conv_801 = Identity(%onnx::Conv_792)
%onnx::Conv_798 = Identity(%onnx::Conv_792)
%onnx::Conv_795 = Identity(%onnx::Conv_792)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_788, %onnx::Conv_789)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%786 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %786
}
|
val_accuracy
| 89.453125
| 1,062,086,656
| 3,553,034
|
{'zcp_epe_nas': 98.59395912388881, 'zcp_fisher': 562.5590209960938, 'zcp_flops': 16993386496.0, 'zcp_grad_norm': 420.1315612792969, 'zcp_grasp': -634.65234375, 'zcp_jacov': -16.04699436043977, 'zcp_l2_norm': 798.8107299804688, 'zcp_nwot': 222.02047572877385, 'zcp_params': 3553034.0, 'zcp_plain': -0.030739743262529002, 'zcp_snip': 2217.38720703125, 'zcp_synflow': 137.02076060051158, 'zcp_zen': 78.79473114013672, 'zcp_val_accuracy': 0.9398036599159241}
| |
NASBench101_125021
|
NASBench101
|
125021
|
4b85c3b0cc47cccda6b7ec996e15471a
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_833[FLOAT, 128x3x3x3]
%onnx::Conv_834[FLOAT, 128]
%onnx::Conv_836[FLOAT, 43x128x1x1]
%onnx::Conv_837[FLOAT, 43]
%onnx::Conv_839[FLOAT, 43x43x1x1]
%onnx::Conv_842[FLOAT, 43x43x1x1]
%onnx::Conv_845[FLOAT, 42x42x3x3]
%onnx::Conv_846[FLOAT, 42]
%onnx::Conv_848[FLOAT, 42x42x1x1]
%onnx::Conv_851[FLOAT, 43x128x1x1]
%onnx::Conv_854[FLOAT, 43x43x1x1]
%onnx::Conv_857[FLOAT, 43x43x1x1]
%onnx::Conv_860[FLOAT, 42x42x3x3]
%onnx::Conv_863[FLOAT, 42x42x1x1]
%onnx::Conv_866[FLOAT, 43x128x1x1]
%onnx::Conv_869[FLOAT, 43x43x1x1]
%onnx::Conv_872[FLOAT, 43x43x1x1]
%onnx::Conv_875[FLOAT, 42x42x3x3]
%onnx::Conv_878[FLOAT, 42x42x1x1]
%onnx::Conv_881[FLOAT, 86x128x1x1]
%onnx::Conv_882[FLOAT, 86]
%onnx::Conv_884[FLOAT, 86x86x1x1]
%onnx::Conv_887[FLOAT, 85x85x1x1]
%onnx::Conv_888[FLOAT, 85]
%onnx::Conv_890[FLOAT, 85x85x3x3]
%onnx::Conv_893[FLOAT, 85x85x1x1]
%onnx::Conv_896[FLOAT, 86x256x1x1]
%onnx::Conv_899[FLOAT, 86x86x1x1]
%onnx::Conv_902[FLOAT, 85x85x1x1]
%onnx::Conv_905[FLOAT, 85x85x3x3]
%onnx::Conv_908[FLOAT, 85x85x1x1]
%onnx::Conv_911[FLOAT, 86x256x1x1]
%onnx::Conv_914[FLOAT, 86x86x1x1]
%onnx::Conv_917[FLOAT, 85x85x1x1]
%onnx::Conv_920[FLOAT, 85x85x3x3]
%onnx::Conv_923[FLOAT, 85x85x1x1]
%onnx::Conv_926[FLOAT, 171x256x1x1]
%onnx::Conv_927[FLOAT, 171]
%onnx::Conv_929[FLOAT, 171x171x1x1]
%onnx::Conv_932[FLOAT, 171x171x1x1]
%onnx::Conv_935[FLOAT, 170x170x3x3]
%onnx::Conv_936[FLOAT, 170]
%onnx::Conv_938[FLOAT, 170x170x1x1]
%onnx::Conv_941[FLOAT, 171x512x1x1]
%onnx::Conv_944[FLOAT, 171x171x1x1]
%onnx::Conv_947[FLOAT, 171x171x1x1]
%onnx::Conv_950[FLOAT, 170x170x3x3]
%onnx::Conv_953[FLOAT, 170x170x1x1]
%onnx::Conv_956[FLOAT, 171x512x1x1]
%onnx::Conv_959[FLOAT, 171x171x1x1]
%onnx::Conv_962[FLOAT, 171x171x1x1]
%onnx::Conv_965[FLOAT, 170x170x3x3]
%onnx::Conv_968[FLOAT, 170x170x1x1]
) {
%onnx::Conv_969 = Identity(%onnx::Conv_936)
%onnx::Conv_966 = Identity(%onnx::Conv_936)
%onnx::Conv_963 = Identity(%onnx::Conv_927)
%onnx::Conv_960 = Identity(%onnx::Conv_927)
%onnx::Conv_957 = Identity(%onnx::Conv_927)
%onnx::Conv_954 = Identity(%onnx::Conv_936)
%onnx::Conv_951 = Identity(%onnx::Conv_936)
%onnx::Conv_948 = Identity(%onnx::Conv_927)
%onnx::Conv_945 = Identity(%onnx::Conv_927)
%onnx::Conv_942 = Identity(%onnx::Conv_927)
%onnx::Conv_939 = Identity(%onnx::Conv_936)
%onnx::Conv_933 = Identity(%onnx::Conv_927)
%onnx::Conv_930 = Identity(%onnx::Conv_927)
%onnx::Conv_924 = Identity(%onnx::Conv_888)
%onnx::Conv_921 = Identity(%onnx::Conv_888)
%onnx::Conv_918 = Identity(%onnx::Conv_888)
%onnx::Conv_915 = Identity(%onnx::Conv_882)
%onnx::Conv_912 = Identity(%onnx::Conv_882)
%onnx::Conv_909 = Identity(%onnx::Conv_888)
%onnx::Conv_906 = Identity(%onnx::Conv_888)
%onnx::Conv_903 = Identity(%onnx::Conv_888)
%onnx::Conv_900 = Identity(%onnx::Conv_882)
%onnx::Conv_897 = Identity(%onnx::Conv_882)
%onnx::Conv_894 = Identity(%onnx::Conv_888)
%onnx::Conv_891 = Identity(%onnx::Conv_888)
%onnx::Conv_885 = Identity(%onnx::Conv_882)
%onnx::Conv_879 = Identity(%onnx::Conv_846)
%onnx::Conv_876 = Identity(%onnx::Conv_846)
%onnx::Conv_873 = Identity(%onnx::Conv_837)
%onnx::Conv_870 = Identity(%onnx::Conv_837)
%onnx::Conv_867 = Identity(%onnx::Conv_837)
%onnx::Conv_864 = Identity(%onnx::Conv_846)
%onnx::Conv_861 = Identity(%onnx::Conv_846)
%onnx::Conv_858 = Identity(%onnx::Conv_837)
%onnx::Conv_855 = Identity(%onnx::Conv_837)
%onnx::Conv_852 = Identity(%onnx::Conv_837)
%onnx::Conv_849 = Identity(%onnx::Conv_846)
%onnx::Conv_843 = Identity(%onnx::Conv_837)
%onnx::Conv_840 = Identity(%onnx::Conv_837)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_833, %onnx::Conv_834)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_2_output_0, %/layers.1/Constant_5_output_0)
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_1_output_0 = Slice(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_7_output_0, %/layers.1/Constant_8_output_0, %/layers.1/Constant_6_output_0, %/layers.1/Constant_9_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Slice_1_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_10_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_2_output_0, %/layers.2/Constant_5_output_0)
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_1_output_0 = Slice(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_7_output_0, %/layers.2/Constant_8_output_0, %/layers.2/Constant_6_output_0, %/layers.2/Constant_9_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Slice_1_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_10_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_2_output_0, %/layers.3/Constant_5_output_0)
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_1_output_0 = Slice(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_7_output_0, %/layers.3/Constant_8_output_0, %/layers.3/Constant_6_output_0, %/layers.3/Constant_9_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Slice_1_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_10_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_1_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_1_output_0 = Slice(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/Constant_7_output_0, %/layers.5/Constant_8_output_0, %/layers.5/Constant_6_output_0, %/layers.5/Constant_9_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Slice_1_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_10_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_1_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_1_output_0 = Slice(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/Constant_7_output_0, %/layers.6/Constant_8_output_0, %/layers.6/Constant_6_output_0, %/layers.6/Constant_9_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Slice_1_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_10_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_1_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_1_output_0 = Slice(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/Constant_7_output_0, %/layers.7/Constant_8_output_0, %/layers.7/Constant_6_output_0, %/layers.7/Constant_9_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Slice_1_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_10_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_2_output_0, %/layers.9/Constant_5_output_0)
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_1_output_0 = Slice(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_7_output_0, %/layers.9/Constant_8_output_0, %/layers.9/Constant_6_output_0, %/layers.9/Constant_9_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Slice_1_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_10_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_2_output_0, %/layers.10/Constant_5_output_0)
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_1_output_0 = Slice(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_7_output_0, %/layers.10/Constant_8_output_0, %/layers.10/Constant_6_output_0, %/layers.10/Constant_9_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Slice_1_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_10_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_2_output_0, %/layers.11/Constant_5_output_0)
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_1_output_0 = Slice(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_7_output_0, %/layers.11/Constant_8_output_0, %/layers.11/Constant_6_output_0, %/layers.11/Constant_9_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Slice_1_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_10_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%831 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %831
}
|
val_accuracy
| 89.042467
| 505,286,400
| 1,675,305
|
{'zcp_epe_nas': 106.06136941046765, 'zcp_fisher': 40.17430114746094, 'zcp_flops': 8084582400.0, 'zcp_grad_norm': 116.43567657470703, 'zcp_grasp': -43.778076171875, 'zcp_jacov': -16.045560117784973, 'zcp_l2_norm': 690.0623168945312, 'zcp_nwot': 215.68062666519134, 'zcp_params': 1675305.0, 'zcp_plain': 0.024342229589819003, 'zcp_snip': 537.60107421875, 'zcp_synflow': 121.42961368195732, 'zcp_zen': 69.66983032226562, 'zcp_val_accuracy': 0.8898237347602841}
| |
NASBench101_104107
|
NASBench101
|
104107
|
3efb36cf6f66f372b77f39066a0c647a
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_563[FLOAT, 128x3x3x3]
%onnx::Conv_564[FLOAT, 128]
%onnx::Conv_566[FLOAT, 64x128x1x1]
%onnx::Conv_567[FLOAT, 64]
%onnx::Conv_569[FLOAT, 64x128x1x1]
%onnx::Conv_572[FLOAT, 64x64x3x3]
%onnx::Conv_575[FLOAT, 64x128x1x1]
%onnx::Conv_578[FLOAT, 64x128x1x1]
%onnx::Conv_581[FLOAT, 64x64x3x3]
%onnx::Conv_584[FLOAT, 64x128x1x1]
%onnx::Conv_587[FLOAT, 64x128x1x1]
%onnx::Conv_590[FLOAT, 64x64x3x3]
%onnx::Conv_593[FLOAT, 128x128x1x1]
%onnx::Conv_596[FLOAT, 128x128x1x1]
%onnx::Conv_599[FLOAT, 128x128x3x3]
%onnx::Conv_602[FLOAT, 128x256x1x1]
%onnx::Conv_605[FLOAT, 128x256x1x1]
%onnx::Conv_608[FLOAT, 128x128x3x3]
%onnx::Conv_611[FLOAT, 128x256x1x1]
%onnx::Conv_614[FLOAT, 128x256x1x1]
%onnx::Conv_617[FLOAT, 128x128x3x3]
%onnx::Conv_620[FLOAT, 256x256x1x1]
%onnx::Conv_621[FLOAT, 256]
%onnx::Conv_623[FLOAT, 256x256x1x1]
%onnx::Conv_626[FLOAT, 256x256x3x3]
%onnx::Conv_629[FLOAT, 256x512x1x1]
%onnx::Conv_632[FLOAT, 256x512x1x1]
%onnx::Conv_635[FLOAT, 256x256x3x3]
%onnx::Conv_638[FLOAT, 256x512x1x1]
%onnx::Conv_641[FLOAT, 256x512x1x1]
%onnx::Conv_644[FLOAT, 256x256x3x3]
) {
%onnx::Conv_645 = Identity(%onnx::Conv_621)
%onnx::Conv_642 = Identity(%onnx::Conv_621)
%onnx::Conv_639 = Identity(%onnx::Conv_621)
%onnx::Conv_636 = Identity(%onnx::Conv_621)
%onnx::Conv_633 = Identity(%onnx::Conv_621)
%onnx::Conv_630 = Identity(%onnx::Conv_621)
%onnx::Conv_627 = Identity(%onnx::Conv_621)
%onnx::Conv_624 = Identity(%onnx::Conv_621)
%onnx::Conv_618 = Identity(%onnx::Conv_564)
%onnx::Conv_615 = Identity(%onnx::Conv_564)
%onnx::Conv_612 = Identity(%onnx::Conv_564)
%onnx::Conv_609 = Identity(%onnx::Conv_564)
%onnx::Conv_606 = Identity(%onnx::Conv_564)
%onnx::Conv_603 = Identity(%onnx::Conv_564)
%onnx::Conv_600 = Identity(%onnx::Conv_564)
%onnx::Conv_597 = Identity(%onnx::Conv_564)
%onnx::Conv_594 = Identity(%onnx::Conv_564)
%onnx::Conv_591 = Identity(%onnx::Conv_567)
%onnx::Conv_588 = Identity(%onnx::Conv_567)
%onnx::Conv_585 = Identity(%onnx::Conv_567)
%onnx::Conv_582 = Identity(%onnx::Conv_567)
%onnx::Conv_579 = Identity(%onnx::Conv_567)
%onnx::Conv_576 = Identity(%onnx::Conv_567)
%onnx::Conv_573 = Identity(%onnx::Conv_567)
%onnx::Conv_570 = Identity(%onnx::Conv_567)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_563, %onnx::Conv_564)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_566, %onnx::Conv_567)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_569, %onnx::Conv_570)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_572, %onnx::Conv_573)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_575, %onnx::Conv_576)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_578, %onnx::Conv_579)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_581, %onnx::Conv_582)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_584, %onnx::Conv_585)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_587, %onnx::Conv_588)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_590, %onnx::Conv_591)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_593, %onnx::Conv_594)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_596, %onnx::Conv_597)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_599, %onnx::Conv_600)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_602, %onnx::Conv_603)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_605, %onnx::Conv_606)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_608, %onnx::Conv_609)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_611, %onnx::Conv_612)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_614, %onnx::Conv_615)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_617, %onnx::Conv_618)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_620, %onnx::Conv_621)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_623, %onnx::Conv_624)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_626, %onnx::Conv_627)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_629, %onnx::Conv_630)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_632, %onnx::Conv_633)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_635, %onnx::Conv_636)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_638, %onnx::Conv_639)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_641, %onnx::Conv_642)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_644, %onnx::Conv_645)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%561 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %561
}
|
val_accuracy
| 88.351363
| 964,306,944
| 3,207,690
|
{'zcp_epe_nas': 129.1960069274041, 'zcp_fisher': 7.323533535003662, 'zcp_flops': 15428911104.0, 'zcp_grad_norm': 47.080841064453125, 'zcp_grasp': -15.921234130859375, 'zcp_jacov': -16.064695683382027, 'zcp_l2_norm': 544.3468017578125, 'zcp_nwot': 213.79123884723873, 'zcp_params': 3207690.0, 'zcp_plain': 0.19409738481044703, 'zcp_snip': 265.6655578613281, 'zcp_synflow': 70.88821947911606, 'zcp_zen': 71.5921859741211, 'zcp_val_accuracy': 0.9203726053237911}
| |
NASBench101_73605
|
NASBench101
|
73605
|
2ca92f9d270ae7d33f6d3fb44980a0d3
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_761[FLOAT, 128x3x3x3]
%onnx::Conv_762[FLOAT, 128]
%onnx::Conv_764[FLOAT, 64x128x1x1]
%onnx::Conv_765[FLOAT, 64]
%onnx::Conv_767[FLOAT, 64x64x1x1]
%onnx::Conv_770[FLOAT, 64x64x1x1]
%onnx::Conv_773[FLOAT, 64x64x3x3]
%onnx::Conv_776[FLOAT, 128x128x1x1]
%onnx::Conv_779[FLOAT, 64x128x1x1]
%onnx::Conv_782[FLOAT, 64x64x1x1]
%onnx::Conv_785[FLOAT, 64x64x1x1]
%onnx::Conv_788[FLOAT, 64x64x3x3]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 64x128x1x1]
%onnx::Conv_797[FLOAT, 64x64x1x1]
%onnx::Conv_800[FLOAT, 64x64x1x1]
%onnx::Conv_803[FLOAT, 64x64x3x3]
%onnx::Conv_806[FLOAT, 128x128x1x1]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 128x128x1x1]
%onnx::Conv_818[FLOAT, 128x128x3x3]
%onnx::Conv_821[FLOAT, 256x128x1x1]
%onnx::Conv_822[FLOAT, 256]
%onnx::Conv_824[FLOAT, 128x256x1x1]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 128x128x1x1]
%onnx::Conv_833[FLOAT, 128x128x3x3]
%onnx::Conv_836[FLOAT, 256x256x1x1]
%onnx::Conv_839[FLOAT, 128x256x1x1]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x3x3]
%onnx::Conv_851[FLOAT, 256x256x1x1]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_857[FLOAT, 256x256x1x1]
%onnx::Conv_860[FLOAT, 256x256x1x1]
%onnx::Conv_863[FLOAT, 256x256x3x3]
%onnx::Conv_866[FLOAT, 512x256x1x1]
%onnx::Conv_867[FLOAT, 512]
%onnx::Conv_869[FLOAT, 256x512x1x1]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_875[FLOAT, 256x256x1x1]
%onnx::Conv_878[FLOAT, 256x256x3x3]
%onnx::Conv_881[FLOAT, 512x512x1x1]
%onnx::Conv_884[FLOAT, 256x512x1x1]
%onnx::Conv_887[FLOAT, 256x256x1x1]
%onnx::Conv_890[FLOAT, 256x256x1x1]
%onnx::Conv_893[FLOAT, 256x256x3x3]
%onnx::Conv_896[FLOAT, 512x512x1x1]
) {
%onnx::Conv_897 = Identity(%onnx::Conv_867)
%onnx::Conv_894 = Identity(%onnx::Conv_822)
%onnx::Conv_891 = Identity(%onnx::Conv_822)
%onnx::Conv_888 = Identity(%onnx::Conv_822)
%onnx::Conv_885 = Identity(%onnx::Conv_822)
%onnx::Conv_882 = Identity(%onnx::Conv_867)
%onnx::Conv_879 = Identity(%onnx::Conv_822)
%onnx::Conv_876 = Identity(%onnx::Conv_822)
%onnx::Conv_873 = Identity(%onnx::Conv_822)
%onnx::Conv_870 = Identity(%onnx::Conv_822)
%onnx::Conv_864 = Identity(%onnx::Conv_822)
%onnx::Conv_861 = Identity(%onnx::Conv_822)
%onnx::Conv_858 = Identity(%onnx::Conv_822)
%onnx::Conv_855 = Identity(%onnx::Conv_822)
%onnx::Conv_852 = Identity(%onnx::Conv_822)
%onnx::Conv_849 = Identity(%onnx::Conv_762)
%onnx::Conv_846 = Identity(%onnx::Conv_762)
%onnx::Conv_843 = Identity(%onnx::Conv_762)
%onnx::Conv_840 = Identity(%onnx::Conv_762)
%onnx::Conv_837 = Identity(%onnx::Conv_822)
%onnx::Conv_834 = Identity(%onnx::Conv_762)
%onnx::Conv_831 = Identity(%onnx::Conv_762)
%onnx::Conv_828 = Identity(%onnx::Conv_762)
%onnx::Conv_825 = Identity(%onnx::Conv_762)
%onnx::Conv_819 = Identity(%onnx::Conv_762)
%onnx::Conv_816 = Identity(%onnx::Conv_762)
%onnx::Conv_813 = Identity(%onnx::Conv_762)
%onnx::Conv_810 = Identity(%onnx::Conv_762)
%onnx::Conv_807 = Identity(%onnx::Conv_762)
%onnx::Conv_804 = Identity(%onnx::Conv_765)
%onnx::Conv_801 = Identity(%onnx::Conv_765)
%onnx::Conv_798 = Identity(%onnx::Conv_765)
%onnx::Conv_795 = Identity(%onnx::Conv_765)
%onnx::Conv_792 = Identity(%onnx::Conv_762)
%onnx::Conv_789 = Identity(%onnx::Conv_765)
%onnx::Conv_786 = Identity(%onnx::Conv_765)
%onnx::Conv_783 = Identity(%onnx::Conv_765)
%onnx::Conv_780 = Identity(%onnx::Conv_765)
%onnx::Conv_777 = Identity(%onnx::Conv_762)
%onnx::Conv_774 = Identity(%onnx::Conv_765)
%onnx::Conv_771 = Identity(%onnx::Conv_765)
%onnx::Conv_768 = Identity(%onnx::Conv_765)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_761, %onnx::Conv_762)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_4_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_4_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_4_output_0)
%759 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %759
}
|
val_accuracy
| 91.195911
| 1,257,777,152
| 4,166,026
|
{'zcp_epe_nas': 163.07101525547054, 'zcp_fisher': 4.84559440612793, 'zcp_flops': 20124434432.0, 'zcp_grad_norm': 51.38945388793945, 'zcp_grasp': -1.399368286132812, 'zcp_jacov': -16.053955014129656, 'zcp_l2_norm': 844.688720703125, 'zcp_nwot': 224.3094124674772, 'zcp_params': 4166026.0, 'zcp_plain': 0.012176239863038, 'zcp_snip': 314.4059143066406, 'zcp_synflow': 88.75527870004225, 'zcp_zen': 85.01032257080078, 'zcp_val_accuracy': 0.936197936534881}
| |
NASBench101_183228
|
NASBench101
|
183228
|
6ed7cb48c17b6739788b3603c86e2539
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_860[FLOAT, 128x3x3x3]
%onnx::Conv_861[FLOAT, 128]
%onnx::Conv_863[FLOAT, 64x128x1x1]
%onnx::Conv_864[FLOAT, 64]
%onnx::Conv_866[FLOAT, 64x64x3x3]
%onnx::Conv_869[FLOAT, 64x64x3x3]
%onnx::Conv_872[FLOAT, 64x64x1x1]
%onnx::Conv_875[FLOAT, 64x64x3x3]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_884[FLOAT, 64x64x3x3]
%onnx::Conv_887[FLOAT, 64x64x3x3]
%onnx::Conv_890[FLOAT, 64x64x1x1]
%onnx::Conv_893[FLOAT, 64x64x3x3]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x64x3x3]
%onnx::Conv_908[FLOAT, 64x64x1x1]
%onnx::Conv_911[FLOAT, 64x64x3x3]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 128x128x1x1]
%onnx::Conv_920[FLOAT, 128x128x3x3]
%onnx::Conv_923[FLOAT, 128x128x3x3]
%onnx::Conv_926[FLOAT, 128x128x1x1]
%onnx::Conv_929[FLOAT, 128x128x3x3]
%onnx::Conv_932[FLOAT, 256x128x1x1]
%onnx::Conv_933[FLOAT, 256]
%onnx::Conv_935[FLOAT, 128x256x1x1]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 128x128x3x3]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x3x3]
%onnx::Conv_950[FLOAT, 256x256x1x1]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x128x3x3]
%onnx::Conv_962[FLOAT, 128x128x1x1]
%onnx::Conv_965[FLOAT, 128x128x3x3]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 256x256x1x1]
%onnx::Conv_974[FLOAT, 256x256x3x3]
%onnx::Conv_977[FLOAT, 256x256x3x3]
%onnx::Conv_980[FLOAT, 256x256x1x1]
%onnx::Conv_983[FLOAT, 256x256x3x3]
%onnx::Conv_986[FLOAT, 512x256x1x1]
%onnx::Conv_987[FLOAT, 512]
%onnx::Conv_989[FLOAT, 256x512x1x1]
%onnx::Conv_992[FLOAT, 256x256x3x3]
%onnx::Conv_995[FLOAT, 256x256x3x3]
%onnx::Conv_998[FLOAT, 256x256x1x1]
%onnx::Conv_1001[FLOAT, 256x256x3x3]
%onnx::Conv_1004[FLOAT, 512x512x1x1]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x256x3x3]
%onnx::Conv_1016[FLOAT, 256x256x1x1]
%onnx::Conv_1019[FLOAT, 256x256x3x3]
%onnx::Conv_1022[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1023 = Identity(%onnx::Conv_987)
%onnx::Conv_1020 = Identity(%onnx::Conv_933)
%onnx::Conv_1017 = Identity(%onnx::Conv_933)
%onnx::Conv_1014 = Identity(%onnx::Conv_933)
%onnx::Conv_1011 = Identity(%onnx::Conv_933)
%onnx::Conv_1008 = Identity(%onnx::Conv_933)
%onnx::Conv_1005 = Identity(%onnx::Conv_987)
%onnx::Conv_1002 = Identity(%onnx::Conv_933)
%onnx::Conv_999 = Identity(%onnx::Conv_933)
%onnx::Conv_996 = Identity(%onnx::Conv_933)
%onnx::Conv_993 = Identity(%onnx::Conv_933)
%onnx::Conv_990 = Identity(%onnx::Conv_933)
%onnx::Conv_984 = Identity(%onnx::Conv_933)
%onnx::Conv_981 = Identity(%onnx::Conv_933)
%onnx::Conv_978 = Identity(%onnx::Conv_933)
%onnx::Conv_975 = Identity(%onnx::Conv_933)
%onnx::Conv_972 = Identity(%onnx::Conv_933)
%onnx::Conv_969 = Identity(%onnx::Conv_933)
%onnx::Conv_966 = Identity(%onnx::Conv_861)
%onnx::Conv_963 = Identity(%onnx::Conv_861)
%onnx::Conv_960 = Identity(%onnx::Conv_861)
%onnx::Conv_957 = Identity(%onnx::Conv_861)
%onnx::Conv_954 = Identity(%onnx::Conv_861)
%onnx::Conv_951 = Identity(%onnx::Conv_933)
%onnx::Conv_948 = Identity(%onnx::Conv_861)
%onnx::Conv_945 = Identity(%onnx::Conv_861)
%onnx::Conv_942 = Identity(%onnx::Conv_861)
%onnx::Conv_939 = Identity(%onnx::Conv_861)
%onnx::Conv_936 = Identity(%onnx::Conv_861)
%onnx::Conv_930 = Identity(%onnx::Conv_861)
%onnx::Conv_927 = Identity(%onnx::Conv_861)
%onnx::Conv_924 = Identity(%onnx::Conv_861)
%onnx::Conv_921 = Identity(%onnx::Conv_861)
%onnx::Conv_918 = Identity(%onnx::Conv_861)
%onnx::Conv_915 = Identity(%onnx::Conv_861)
%onnx::Conv_912 = Identity(%onnx::Conv_864)
%onnx::Conv_909 = Identity(%onnx::Conv_864)
%onnx::Conv_906 = Identity(%onnx::Conv_864)
%onnx::Conv_903 = Identity(%onnx::Conv_864)
%onnx::Conv_900 = Identity(%onnx::Conv_864)
%onnx::Conv_897 = Identity(%onnx::Conv_861)
%onnx::Conv_894 = Identity(%onnx::Conv_864)
%onnx::Conv_891 = Identity(%onnx::Conv_864)
%onnx::Conv_888 = Identity(%onnx::Conv_864)
%onnx::Conv_885 = Identity(%onnx::Conv_864)
%onnx::Conv_882 = Identity(%onnx::Conv_864)
%onnx::Conv_879 = Identity(%onnx::Conv_861)
%onnx::Conv_876 = Identity(%onnx::Conv_864)
%onnx::Conv_873 = Identity(%onnx::Conv_864)
%onnx::Conv_870 = Identity(%onnx::Conv_864)
%onnx::Conv_867 = Identity(%onnx::Conv_864)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_860, %onnx::Conv_861)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_4_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_4_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_4_output_0)
%858 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %858
}
|
val_accuracy
| 93.619794
| 2,543,986,688
| 8,555,530
|
{'zcp_epe_nas': 103.12411064661494, 'zcp_fisher': 17.4626522064209, 'zcp_flops': 40703787008.0, 'zcp_grad_norm': 90.50105285644531, 'zcp_grasp': -0.19732666015625, 'zcp_jacov': -16.05199506501176, 'zcp_l2_norm': 994.3348388671875, 'zcp_nwot': 226.70831907316168, 'zcp_params': 8555530.0, 'zcp_plain': 0.037546906620264005, 'zcp_snip': 561.06005859375, 'zcp_synflow': 117.26405191340145, 'zcp_zen': 107.02976989746094, 'zcp_val_accuracy': 0.9377003312110901}
| |
NASBench101_26105
|
NASBench101
|
26105
|
0fc61f918480b2181e71e70d4b8c621f
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_851[FLOAT, 128x3x3x3]
%onnx::Conv_852[FLOAT, 128]
%onnx::Conv_854[FLOAT, 32x128x1x1]
%onnx::Conv_855[FLOAT, 32]
%onnx::Conv_857[FLOAT, 32x32x1x1]
%onnx::Conv_860[FLOAT, 32x32x3x3]
%onnx::Conv_863[FLOAT, 32x128x1x1]
%onnx::Conv_866[FLOAT, 32x32x3x3]
%onnx::Conv_869[FLOAT, 32x32x1x1]
%onnx::Conv_872[FLOAT, 32x128x1x1]
%onnx::Conv_875[FLOAT, 32x32x1x1]
%onnx::Conv_878[FLOAT, 32x32x3x3]
%onnx::Conv_881[FLOAT, 32x128x1x1]
%onnx::Conv_884[FLOAT, 32x32x3x3]
%onnx::Conv_887[FLOAT, 32x32x1x1]
%onnx::Conv_890[FLOAT, 32x128x1x1]
%onnx::Conv_893[FLOAT, 32x32x1x1]
%onnx::Conv_896[FLOAT, 32x32x3x3]
%onnx::Conv_899[FLOAT, 32x128x1x1]
%onnx::Conv_902[FLOAT, 32x32x3x3]
%onnx::Conv_905[FLOAT, 32x32x1x1]
%onnx::Conv_908[FLOAT, 64x128x1x1]
%onnx::Conv_909[FLOAT, 64]
%onnx::Conv_911[FLOAT, 64x64x1x1]
%onnx::Conv_914[FLOAT, 64x64x3x3]
%onnx::Conv_917[FLOAT, 64x128x1x1]
%onnx::Conv_920[FLOAT, 64x64x3x3]
%onnx::Conv_923[FLOAT, 64x64x1x1]
%onnx::Conv_926[FLOAT, 64x256x1x1]
%onnx::Conv_929[FLOAT, 64x64x1x1]
%onnx::Conv_932[FLOAT, 64x64x3x3]
%onnx::Conv_935[FLOAT, 64x256x1x1]
%onnx::Conv_938[FLOAT, 64x64x3x3]
%onnx::Conv_941[FLOAT, 64x64x1x1]
%onnx::Conv_944[FLOAT, 64x256x1x1]
%onnx::Conv_947[FLOAT, 64x64x1x1]
%onnx::Conv_950[FLOAT, 64x64x3x3]
%onnx::Conv_953[FLOAT, 64x256x1x1]
%onnx::Conv_956[FLOAT, 64x64x3x3]
%onnx::Conv_959[FLOAT, 64x64x1x1]
%onnx::Conv_962[FLOAT, 128x256x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x128x3x3]
%onnx::Conv_971[FLOAT, 128x256x1x1]
%onnx::Conv_974[FLOAT, 128x128x3x3]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 128x512x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x128x3x3]
%onnx::Conv_989[FLOAT, 128x512x1x1]
%onnx::Conv_992[FLOAT, 128x128x3x3]
%onnx::Conv_995[FLOAT, 128x128x1x1]
%onnx::Conv_998[FLOAT, 128x512x1x1]
%onnx::Conv_1001[FLOAT, 128x128x1x1]
%onnx::Conv_1004[FLOAT, 128x128x3x3]
%onnx::Conv_1007[FLOAT, 128x512x1x1]
%onnx::Conv_1010[FLOAT, 128x128x3x3]
%onnx::Conv_1013[FLOAT, 128x128x1x1]
) {
%onnx::Conv_1014 = Identity(%onnx::Conv_852)
%onnx::Conv_1011 = Identity(%onnx::Conv_852)
%onnx::Conv_1008 = Identity(%onnx::Conv_852)
%onnx::Conv_1005 = Identity(%onnx::Conv_852)
%onnx::Conv_1002 = Identity(%onnx::Conv_852)
%onnx::Conv_999 = Identity(%onnx::Conv_852)
%onnx::Conv_996 = Identity(%onnx::Conv_852)
%onnx::Conv_993 = Identity(%onnx::Conv_852)
%onnx::Conv_990 = Identity(%onnx::Conv_852)
%onnx::Conv_987 = Identity(%onnx::Conv_852)
%onnx::Conv_984 = Identity(%onnx::Conv_852)
%onnx::Conv_981 = Identity(%onnx::Conv_852)
%onnx::Conv_978 = Identity(%onnx::Conv_852)
%onnx::Conv_975 = Identity(%onnx::Conv_852)
%onnx::Conv_972 = Identity(%onnx::Conv_852)
%onnx::Conv_969 = Identity(%onnx::Conv_852)
%onnx::Conv_966 = Identity(%onnx::Conv_852)
%onnx::Conv_963 = Identity(%onnx::Conv_852)
%onnx::Conv_960 = Identity(%onnx::Conv_909)
%onnx::Conv_957 = Identity(%onnx::Conv_909)
%onnx::Conv_954 = Identity(%onnx::Conv_909)
%onnx::Conv_951 = Identity(%onnx::Conv_909)
%onnx::Conv_948 = Identity(%onnx::Conv_909)
%onnx::Conv_945 = Identity(%onnx::Conv_909)
%onnx::Conv_942 = Identity(%onnx::Conv_909)
%onnx::Conv_939 = Identity(%onnx::Conv_909)
%onnx::Conv_936 = Identity(%onnx::Conv_909)
%onnx::Conv_933 = Identity(%onnx::Conv_909)
%onnx::Conv_930 = Identity(%onnx::Conv_909)
%onnx::Conv_927 = Identity(%onnx::Conv_909)
%onnx::Conv_924 = Identity(%onnx::Conv_909)
%onnx::Conv_921 = Identity(%onnx::Conv_909)
%onnx::Conv_918 = Identity(%onnx::Conv_909)
%onnx::Conv_915 = Identity(%onnx::Conv_909)
%onnx::Conv_912 = Identity(%onnx::Conv_909)
%onnx::Conv_906 = Identity(%onnx::Conv_855)
%onnx::Conv_903 = Identity(%onnx::Conv_855)
%onnx::Conv_900 = Identity(%onnx::Conv_855)
%onnx::Conv_897 = Identity(%onnx::Conv_855)
%onnx::Conv_894 = Identity(%onnx::Conv_855)
%onnx::Conv_891 = Identity(%onnx::Conv_855)
%onnx::Conv_888 = Identity(%onnx::Conv_855)
%onnx::Conv_885 = Identity(%onnx::Conv_855)
%onnx::Conv_882 = Identity(%onnx::Conv_855)
%onnx::Conv_879 = Identity(%onnx::Conv_855)
%onnx::Conv_876 = Identity(%onnx::Conv_855)
%onnx::Conv_873 = Identity(%onnx::Conv_855)
%onnx::Conv_870 = Identity(%onnx::Conv_855)
%onnx::Conv_867 = Identity(%onnx::Conv_855)
%onnx::Conv_864 = Identity(%onnx::Conv_855)
%onnx::Conv_861 = Identity(%onnx::Conv_855)
%onnx::Conv_858 = Identity(%onnx::Conv_855)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_851, %onnx::Conv_852)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%849 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %849
}
|
val_accuracy
| 91.716748
| 528,099,328
| 1,741,322
|
{'zcp_epe_nas': 82.1134220111424, 'zcp_fisher': 15.115734100341797, 'zcp_flops': 8449589248.0, 'zcp_grad_norm': 77.70206451416016, 'zcp_grasp': -1.06927490234375, 'zcp_jacov': -16.056149801271616, 'zcp_l2_norm': 818.3993530273438, 'zcp_nwot': 214.62316109991528, 'zcp_params': 1741322.0, 'zcp_plain': -0.033855903893709, 'zcp_snip': 361.7281188964844, 'zcp_synflow': 81.5982000275985, 'zcp_zen': 81.28792572021484, 'zcp_val_accuracy': 0.8876202106475831}
| |
NASBench101_129969
|
NASBench101
|
129969
|
4e90d778379ffeb840d200355f587b69
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_560[FLOAT, 128x3x3x3]
%onnx::Conv_561[FLOAT, 128]
%onnx::Conv_563[FLOAT, 43x128x1x1]
%onnx::Conv_564[FLOAT, 43]
%onnx::Conv_566[FLOAT, 43x43x3x3]
%onnx::Conv_569[FLOAT, 42x42x3x3]
%onnx::Conv_570[FLOAT, 42]
%onnx::Conv_572[FLOAT, 43x128x1x1]
%onnx::Conv_575[FLOAT, 43x43x3x3]
%onnx::Conv_578[FLOAT, 42x42x3x3]
%onnx::Conv_581[FLOAT, 43x128x1x1]
%onnx::Conv_584[FLOAT, 43x43x3x3]
%onnx::Conv_587[FLOAT, 42x42x3x3]
%onnx::Conv_590[FLOAT, 86x128x1x1]
%onnx::Conv_591[FLOAT, 86]
%onnx::Conv_593[FLOAT, 86x86x3x3]
%onnx::Conv_596[FLOAT, 85x85x3x3]
%onnx::Conv_597[FLOAT, 85]
%onnx::Conv_599[FLOAT, 86x256x1x1]
%onnx::Conv_602[FLOAT, 86x86x3x3]
%onnx::Conv_605[FLOAT, 85x85x3x3]
%onnx::Conv_608[FLOAT, 86x256x1x1]
%onnx::Conv_611[FLOAT, 86x86x3x3]
%onnx::Conv_614[FLOAT, 85x85x3x3]
%onnx::Conv_617[FLOAT, 171x256x1x1]
%onnx::Conv_618[FLOAT, 171]
%onnx::Conv_620[FLOAT, 171x171x3x3]
%onnx::Conv_623[FLOAT, 170x170x3x3]
%onnx::Conv_624[FLOAT, 170]
%onnx::Conv_626[FLOAT, 171x512x1x1]
%onnx::Conv_629[FLOAT, 171x171x3x3]
%onnx::Conv_632[FLOAT, 170x170x3x3]
%onnx::Conv_635[FLOAT, 171x512x1x1]
%onnx::Conv_638[FLOAT, 171x171x3x3]
%onnx::Conv_641[FLOAT, 170x170x3x3]
) {
%onnx::Conv_642 = Identity(%onnx::Conv_624)
%onnx::Conv_639 = Identity(%onnx::Conv_618)
%onnx::Conv_636 = Identity(%onnx::Conv_618)
%onnx::Conv_633 = Identity(%onnx::Conv_624)
%onnx::Conv_630 = Identity(%onnx::Conv_618)
%onnx::Conv_627 = Identity(%onnx::Conv_618)
%onnx::Conv_621 = Identity(%onnx::Conv_618)
%onnx::Conv_615 = Identity(%onnx::Conv_597)
%onnx::Conv_612 = Identity(%onnx::Conv_591)
%onnx::Conv_609 = Identity(%onnx::Conv_591)
%onnx::Conv_606 = Identity(%onnx::Conv_597)
%onnx::Conv_603 = Identity(%onnx::Conv_591)
%onnx::Conv_600 = Identity(%onnx::Conv_591)
%onnx::Conv_594 = Identity(%onnx::Conv_591)
%onnx::Conv_588 = Identity(%onnx::Conv_570)
%onnx::Conv_585 = Identity(%onnx::Conv_564)
%onnx::Conv_582 = Identity(%onnx::Conv_564)
%onnx::Conv_579 = Identity(%onnx::Conv_570)
%onnx::Conv_576 = Identity(%onnx::Conv_564)
%onnx::Conv_573 = Identity(%onnx::Conv_564)
%onnx::Conv_567 = Identity(%onnx::Conv_564)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_560, %onnx::Conv_561)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_563, %onnx::Conv_564)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_566, %onnx::Conv_567)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/Constant_2_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_1_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Slice_output_0, %onnx::Conv_569, %onnx::Conv_570)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_572, %onnx::Conv_573)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_575, %onnx::Conv_576)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/Constant_2_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_1_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Slice_output_0, %onnx::Conv_578, %onnx::Conv_579)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_581, %onnx::Conv_582)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_584, %onnx::Conv_585)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/Constant_2_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_1_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Slice_output_0, %onnx::Conv_587, %onnx::Conv_588)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_590, %onnx::Conv_591)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_593, %onnx::Conv_594)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_1_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_1_output_0 = Slice(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_6_output_0, %/layers.5/Constant_7_output_0, %/layers.5/Constant_5_output_0, %/layers.5/Constant_8_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Slice_1_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_596, %onnx::Conv_597)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_599, %onnx::Conv_600)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_602, %onnx::Conv_603)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_1_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_1_output_0 = Slice(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_6_output_0, %/layers.6/Constant_7_output_0, %/layers.6/Constant_5_output_0, %/layers.6/Constant_8_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Slice_1_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_605, %onnx::Conv_606)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_608, %onnx::Conv_609)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_611, %onnx::Conv_612)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_1_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_1_output_0 = Slice(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_6_output_0, %/layers.7/Constant_7_output_0, %/layers.7/Constant_5_output_0, %/layers.7/Constant_8_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Slice_1_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_614, %onnx::Conv_615)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_617, %onnx::Conv_618)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_620, %onnx::Conv_621)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/Constant_2_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_1_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Slice_output_0, %onnx::Conv_623, %onnx::Conv_624)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_626, %onnx::Conv_627)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_629, %onnx::Conv_630)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/Constant_2_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_1_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Slice_output_0, %onnx::Conv_632, %onnx::Conv_633)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_635, %onnx::Conv_636)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_638, %onnx::Conv_639)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/Constant_2_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_1_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Slice_output_0, %onnx::Conv_641, %onnx::Conv_642)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%558 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %558
}
|
val_accuracy
| 88.741988
| 706,502,016
| 2,366,781
|
{'zcp_epe_nas': 86.51052163242494, 'zcp_fisher': 9.556004524230957, 'zcp_flops': 11304032256.0, 'zcp_grad_norm': 53.92864227294922, 'zcp_grasp': -5.10308837890625, 'zcp_jacov': -16.05117453096259, 'zcp_l2_norm': 443.7821350097656, 'zcp_nwot': 208.15117412219678, 'zcp_params': 2366781.0, 'zcp_plain': 0.0044124862179160005, 'zcp_snip': 267.37274169921875, 'zcp_synflow': 89.19618657646835, 'zcp_zen': 64.1761703491211, 'zcp_val_accuracy': 0.9278846383094781}
|
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