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_95255
|
NASBench101
|
95255
|
39a038956467c4c941eba96514508d32
|
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, 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, 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, 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_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/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_653, %onnx::Conv_654)
%/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_656, %onnx::Conv_657)
%/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.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/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_665, %onnx::Conv_666)
%/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_668, %onnx::Conv_669)
%/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.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/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_677, %onnx::Conv_678)
%/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_680, %onnx::Conv_681)
%/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.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/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_689, %onnx::Conv_690)
%/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_692, %onnx::Conv_693)
%/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.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/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_701, %onnx::Conv_702)
%/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_704, %onnx::Conv_705)
%/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.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/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_713, %onnx::Conv_714)
%/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_716, %onnx::Conv_717)
%/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.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/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_725, %onnx::Conv_726)
%/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_728, %onnx::Conv_729)
%/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.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/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_737, %onnx::Conv_738)
%/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_740, %onnx::Conv_741)
%/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.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/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_749, %onnx::Conv_750)
%/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_752, %onnx::Conv_753)
%/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)
%/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
| 88.952321
| 1,171,007,488
| 3,831,434
|
{'zcp_epe_nas': 134.34498651210063, 'zcp_fisher': 17.943893432617188, 'zcp_flops': 18736119808.0, 'zcp_grad_norm': 95.86196899414062, 'zcp_grasp': -32.619873046875, 'zcp_jacov': -16.047438585651783, 'zcp_l2_norm': 818.5125732421875, 'zcp_nwot': 229.02264784259262, 'zcp_params': 3831434.0, 'zcp_plain': 0.20634761452674802, 'zcp_snip': 681.5751953125, 'zcp_synflow': 84.22003482383931, 'zcp_zen': 71.71488952636719, 'zcp_val_accuracy': 0.9004406929016111}
| |
NASBench101_41709
|
NASBench101
|
41709
|
194c3215b40ec55a5b8288d481d1c83f
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_338[FLOAT, 128x3x3x3]
%onnx::Conv_339[FLOAT, 128]
%onnx::Conv_341[FLOAT, 128x128x1x1]
%onnx::Conv_344[FLOAT, 128x128x1x1]
%onnx::Conv_347[FLOAT, 128x128x1x1]
%onnx::Conv_350[FLOAT, 256x128x1x1]
%onnx::Conv_351[FLOAT, 256]
%onnx::Conv_353[FLOAT, 256x256x1x1]
%onnx::Conv_356[FLOAT, 256x256x1x1]
%onnx::Conv_359[FLOAT, 512x256x1x1]
%onnx::Conv_360[FLOAT, 512]
%onnx::Conv_362[FLOAT, 512x512x1x1]
%onnx::Conv_365[FLOAT, 512x512x1x1]
) {
%onnx::Conv_366 = Identity(%onnx::Conv_360)
%onnx::Conv_363 = Identity(%onnx::Conv_360)
%onnx::Conv_357 = Identity(%onnx::Conv_351)
%onnx::Conv_354 = Identity(%onnx::Conv_351)
%onnx::Conv_348 = Identity(%onnx::Conv_339)
%onnx::Conv_345 = Identity(%onnx::Conv_339)
%onnx::Conv_342 = Identity(%onnx::Conv_339)
%/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_338, %onnx::Conv_339)
%/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_341, %onnx::Conv_342)
%/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/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/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/Add_1_output_0 = Add(%/layers.1/vertex_op.3/maxpool/MaxPool_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_1_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_344, %onnx::Conv_345)
%/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/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/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/Add_1_output_0 = Add(%/layers.2/vertex_op.3/maxpool/MaxPool_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_1_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_347, %onnx::Conv_348)
%/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/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/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/Add_1_output_0 = Add(%/layers.3/vertex_op.3/maxpool/MaxPool_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_1_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_350, %onnx::Conv_351)
%/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/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/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/Add_1_output_0 = Add(%/layers.5/vertex_op.3/maxpool/MaxPool_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_1_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_353, %onnx::Conv_354)
%/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/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/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/Add_1_output_0 = Add(%/layers.6/vertex_op.3/maxpool/MaxPool_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_1_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_356, %onnx::Conv_357)
%/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/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/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/Add_1_output_0 = Add(%/layers.7/vertex_op.3/maxpool/MaxPool_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_1_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_359, %onnx::Conv_360)
%/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/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/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/Add_1_output_0 = Add(%/layers.9/vertex_op.3/maxpool/MaxPool_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_1_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_362, %onnx::Conv_363)
%/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/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/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/Add_1_output_0 = Add(%/layers.10/vertex_op.3/maxpool/MaxPool_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_1_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_365, %onnx::Conv_366)
%/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/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/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/Add_1_output_0 = Add(%/layers.11/vertex_op.3/maxpool/MaxPool_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_1_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%336 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %336
}
|
val_accuracy
| 83.64383
| 282,077,184
| 882,570
|
{'zcp_epe_nas': 91.56736828714311, 'zcp_fisher': 10.590023040771484, 'zcp_flops': 4513234944.0, 'zcp_grad_norm': 46.597373962402344, 'zcp_grasp': -10.362091064453125, 'zcp_jacov': -16.056632435321177, 'zcp_l2_norm': 199.4592742919922, 'zcp_nwot': 208.6816803639644, 'zcp_params': 882570.0, 'zcp_plain': 0.206545412540435, 'zcp_snip': 279.6631774902344, 'zcp_synflow': 36.89600610719478, 'zcp_zen': 25.853382110595703, 'zcp_val_accuracy': 0.888221144676208}
| |
NASBench101_79594
|
NASBench101
|
79594
|
3044e607c958fb668518b6c142a9db58
|
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, 64x128x1x1]
%onnx::Conv_875[FLOAT, 64x64x3x3]
%onnx::Conv_878[FLOAT, 64x64x3x3]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_884[FLOAT, 64x64x3x3]
%onnx::Conv_887[FLOAT, 64x64x3x3]
%onnx::Conv_890[FLOAT, 64x128x1x1]
%onnx::Conv_893[FLOAT, 64x64x3x3]
%onnx::Conv_896[FLOAT, 64x64x3x3]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x64x3x3]
%onnx::Conv_908[FLOAT, 64x128x1x1]
%onnx::Conv_911[FLOAT, 64x64x3x3]
%onnx::Conv_914[FLOAT, 64x64x3x3]
%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, 128x128x3x3]
%onnx::Conv_935[FLOAT, 128x256x1x1]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 128x128x3x3]
%onnx::Conv_944[FLOAT, 128x256x1x1]
%onnx::Conv_947[FLOAT, 128x128x3x3]
%onnx::Conv_950[FLOAT, 128x128x3x3]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x128x3x3]
%onnx::Conv_962[FLOAT, 128x256x1x1]
%onnx::Conv_965[FLOAT, 128x128x3x3]
%onnx::Conv_968[FLOAT, 128x128x3x3]
%onnx::Conv_971[FLOAT, 256x256x1x1]
%onnx::Conv_972[FLOAT, 256]
%onnx::Conv_974[FLOAT, 256x256x3x3]
%onnx::Conv_977[FLOAT, 256x256x3x3]
%onnx::Conv_980[FLOAT, 256x256x1x1]
%onnx::Conv_983[FLOAT, 256x256x3x3]
%onnx::Conv_986[FLOAT, 256x256x3x3]
%onnx::Conv_989[FLOAT, 256x512x1x1]
%onnx::Conv_992[FLOAT, 256x256x3x3]
%onnx::Conv_995[FLOAT, 256x256x3x3]
%onnx::Conv_998[FLOAT, 256x512x1x1]
%onnx::Conv_1001[FLOAT, 256x256x3x3]
%onnx::Conv_1004[FLOAT, 256x256x3x3]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x256x3x3]
%onnx::Conv_1016[FLOAT, 256x512x1x1]
%onnx::Conv_1019[FLOAT, 256x256x3x3]
%onnx::Conv_1022[FLOAT, 256x256x3x3]
) {
%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_861)
%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_861)
%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_933 = 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_864)
%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_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)
%/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/input_op.3/conv_bn_relu/conv_bn_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.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_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/Constant_3_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_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_4_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.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.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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_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/Constant_3_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_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_4_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.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.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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_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/Constant_3_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_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_4_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.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.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_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/input_op.3/conv_bn_relu/conv_bn_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.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_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/Constant_3_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_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_4_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.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.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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_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/Constant_3_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_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_4_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.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.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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_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/Constant_3_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_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_4_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.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.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_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/input_op.3/conv_bn_relu/conv_bn_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.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_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/Constant_3_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_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_4_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.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.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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_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/Constant_3_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_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_4_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.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.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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_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/Constant_3_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_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_4_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)
%/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.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)
%858 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %858
}
|
val_accuracy
| 92.08734
| 3,010,996,224
| 10,183,050
|
{'zcp_epe_nas': 99.24439165323409, 'zcp_fisher': 300.8633117675781, 'zcp_flops': 48175939584.0, 'zcp_grad_norm': 304.0283508300781, 'zcp_grasp': 38.171875, 'zcp_jacov': -16.059034628883303, 'zcp_l2_norm': 994.4503784179688, 'zcp_nwot': 223.86651697839207, 'zcp_params': 10183050.0, 'zcp_plain': 0.06431175768375301, 'zcp_snip': 1848.199951171875, 'zcp_synflow': 159.67698836131487, 'zcp_zen': 113.96621704101562, 'zcp_val_accuracy': 0.9110577106475831}
| |
NASBench101_195352
|
NASBench101
|
195352
|
76313fcdceb40cb9ab4737e0252db22b
|
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, 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, 128x128x1x1]
%onnx::Conv_803[FLOAT, 128x128x3x3]
%onnx::Conv_806[FLOAT, 128x128x3x3]
%onnx::Conv_809[FLOAT, 256x128x1x1]
%onnx::Conv_810[FLOAT, 256]
%onnx::Conv_812[FLOAT, 256x256x1x1]
%onnx::Conv_815[FLOAT, 256x128x1x1]
%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, 256x256x1x1]
%onnx::Conv_848[FLOAT, 256x256x3x3]
%onnx::Conv_851[FLOAT, 256x256x3x3]
%onnx::Conv_854[FLOAT, 512x256x1x1]
%onnx::Conv_855[FLOAT, 512]
%onnx::Conv_857[FLOAT, 512x512x1x1]
%onnx::Conv_860[FLOAT, 512x256x1x1]
%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_890[FLOAT, 512x512x1x1]
%onnx::Conv_893[FLOAT, 512x512x3x3]
%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/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_767, %onnx::Conv_768)
%/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/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_770, %onnx::Conv_771)
%/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.1/maxpool/MaxPool_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_773, %onnx::Conv_774)
%/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.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/vertex_op.3/maxpool/MaxPool_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_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.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_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/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_782, %onnx::Conv_783)
%/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/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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/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.1/maxpool/MaxPool_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_788, %onnx::Conv_789)
%/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.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/vertex_op.3/maxpool/MaxPool_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_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.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_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/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_797, %onnx::Conv_798)
%/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/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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/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.1/maxpool/MaxPool_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_803, %onnx::Conv_804)
%/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.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/vertex_op.3/maxpool/MaxPool_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_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.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_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/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_812, %onnx::Conv_813)
%/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_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/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_815, %onnx::Conv_816)
%/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.1/maxpool/MaxPool_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_818, %onnx::Conv_819)
%/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.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/vertex_op.3/maxpool/MaxPool_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_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.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_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/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_827, %onnx::Conv_828)
%/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_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/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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/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.1/maxpool/MaxPool_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_833, %onnx::Conv_834)
%/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.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/vertex_op.3/maxpool/MaxPool_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_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.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_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/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_842, %onnx::Conv_843)
%/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_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/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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/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.1/maxpool/MaxPool_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_848, %onnx::Conv_849)
%/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.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/vertex_op.3/maxpool/MaxPool_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_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.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_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/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_857, %onnx::Conv_858)
%/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/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_860, %onnx::Conv_861)
%/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.1/maxpool/MaxPool_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_863, %onnx::Conv_864)
%/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.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/vertex_op.3/maxpool/MaxPool_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_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.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_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/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_872, %onnx::Conv_873)
%/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/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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/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.1/maxpool/MaxPool_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_878, %onnx::Conv_879)
%/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.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/vertex_op.3/maxpool/MaxPool_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_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.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_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/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_887, %onnx::Conv_888)
%/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/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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/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.1/maxpool/MaxPool_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_893, %onnx::Conv_894)
%/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.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/vertex_op.3/maxpool/MaxPool_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_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)
%/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)
%759 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %759
}
|
val_accuracy
| 91.836941
| 6,310,340,608
| 21,384,074
|
{'zcp_epe_nas': 61.19671083687059, 'zcp_fisher': 32.745601654052734, 'zcp_flops': 100965449728.0, 'zcp_grad_norm': 90.63980865478516, 'zcp_grasp': 0.70074462890625, 'zcp_jacov': -16.056240308190024, 'zcp_l2_norm': 1030.1822509765625, 'zcp_nwot': 232.1273193709386, 'zcp_params': 21384074.0, 'zcp_plain': -0.018741976469755003, 'zcp_snip': 852.9667358398438, 'zcp_synflow': 111.89202555967846, 'zcp_zen': 104.4365005493164, 'zcp_val_accuracy': 0.9202724099159241}
| |
NASBench101_62903
|
NASBench101
|
62903
|
26326a4865a65e0dcbf262449c731422
|
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, 64x128x1x1]
%onnx::Conv_693[FLOAT, 64]
%onnx::Conv_695[FLOAT, 64x64x1x1]
%onnx::Conv_698[FLOAT, 64x128x1x1]
%onnx::Conv_701[FLOAT, 64x64x3x3]
%onnx::Conv_704[FLOAT, 64x128x1x1]
%onnx::Conv_707[FLOAT, 64x64x1x1]
%onnx::Conv_710[FLOAT, 64x128x1x1]
%onnx::Conv_713[FLOAT, 64x64x3x3]
%onnx::Conv_716[FLOAT, 64x128x1x1]
%onnx::Conv_719[FLOAT, 64x64x1x1]
%onnx::Conv_722[FLOAT, 64x128x1x1]
%onnx::Conv_725[FLOAT, 64x64x3x3]
%onnx::Conv_728[FLOAT, 128x128x1x1]
%onnx::Conv_731[FLOAT, 128x128x1x1]
%onnx::Conv_734[FLOAT, 128x128x1x1]
%onnx::Conv_737[FLOAT, 128x128x3x3]
%onnx::Conv_740[FLOAT, 128x256x1x1]
%onnx::Conv_743[FLOAT, 128x128x1x1]
%onnx::Conv_746[FLOAT, 128x256x1x1]
%onnx::Conv_749[FLOAT, 128x128x3x3]
%onnx::Conv_752[FLOAT, 128x256x1x1]
%onnx::Conv_755[FLOAT, 128x128x1x1]
%onnx::Conv_758[FLOAT, 128x256x1x1]
%onnx::Conv_761[FLOAT, 128x128x3x3]
%onnx::Conv_764[FLOAT, 256x256x1x1]
%onnx::Conv_765[FLOAT, 256]
%onnx::Conv_767[FLOAT, 256x256x1x1]
%onnx::Conv_770[FLOAT, 256x256x1x1]
%onnx::Conv_773[FLOAT, 256x256x3x3]
%onnx::Conv_776[FLOAT, 256x512x1x1]
%onnx::Conv_779[FLOAT, 256x256x1x1]
%onnx::Conv_782[FLOAT, 256x512x1x1]
%onnx::Conv_785[FLOAT, 256x256x3x3]
%onnx::Conv_788[FLOAT, 256x512x1x1]
%onnx::Conv_791[FLOAT, 256x256x1x1]
%onnx::Conv_794[FLOAT, 256x512x1x1]
%onnx::Conv_797[FLOAT, 256x256x3x3]
) {
%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_690)
%onnx::Conv_759 = Identity(%onnx::Conv_690)
%onnx::Conv_756 = Identity(%onnx::Conv_690)
%onnx::Conv_753 = Identity(%onnx::Conv_690)
%onnx::Conv_750 = Identity(%onnx::Conv_690)
%onnx::Conv_747 = Identity(%onnx::Conv_690)
%onnx::Conv_744 = Identity(%onnx::Conv_690)
%onnx::Conv_741 = Identity(%onnx::Conv_690)
%onnx::Conv_738 = Identity(%onnx::Conv_690)
%onnx::Conv_735 = Identity(%onnx::Conv_690)
%onnx::Conv_732 = Identity(%onnx::Conv_690)
%onnx::Conv_729 = Identity(%onnx::Conv_690)
%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)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_695, %onnx::Conv_696)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_701, %onnx::Conv_702)
%/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/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/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/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_5_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_707, %onnx::Conv_708)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_713, %onnx::Conv_714)
%/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/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/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/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_5_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.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_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/conv1x1/conv_bn_relu/conv_bn_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_719, %onnx::Conv_720)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_725, %onnx::Conv_726)
%/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/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/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/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_5_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_731, %onnx::Conv_732)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_737, %onnx::Conv_738)
%/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/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/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/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_5_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_743, %onnx::Conv_744)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_749, %onnx::Conv_750)
%/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/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/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/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_5_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.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_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/conv1x1/conv_bn_relu/conv_bn_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_755, %onnx::Conv_756)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_761, %onnx::Conv_762)
%/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/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/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/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_5_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_767, %onnx::Conv_768)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_773, %onnx::Conv_774)
%/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/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/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/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_5_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_779, %onnx::Conv_780)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_785, %onnx::Conv_786)
%/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/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/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/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_5_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.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_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/conv1x1/conv_bn_relu/conv_bn_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_791, %onnx::Conv_792)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_797, %onnx::Conv_798)
%/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/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/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/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_5_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.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)
%687 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %687
}
|
val_accuracy
| 85.83734
| 1,042,556,928
| 3,468,426
|
{'zcp_epe_nas': 128.02575410845427, 'zcp_fisher': 135.76156616210938, 'zcp_flops': 16680910848.0, 'zcp_grad_norm': 198.77613830566406, 'zcp_grasp': -125.853515625, 'zcp_jacov': -16.04174281187821, 'zcp_l2_norm': 694.5319213867188, 'zcp_nwot': 218.75652882494362, 'zcp_params': 3468426.0, 'zcp_plain': 0.35389587283134405, 'zcp_snip': 1239.2125244140625, 'zcp_synflow': 71.76711865001207, 'zcp_zen': 76.38983154296875, 'zcp_val_accuracy': 0.9190705418586731}
| |
NASBench101_335342
|
NASBench101
|
335342
|
cac729b6268517d1c7d3759f832dafd5
|
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, 64x64x3x3]
%onnx::Conv_662[FLOAT, 64x64x1x1]
%onnx::Conv_665[FLOAT, 128x128x1x1]
%onnx::Conv_668[FLOAT, 64x128x1x1]
%onnx::Conv_671[FLOAT, 64x64x3x3]
%onnx::Conv_674[FLOAT, 64x64x1x1]
%onnx::Conv_677[FLOAT, 128x128x1x1]
%onnx::Conv_680[FLOAT, 64x128x1x1]
%onnx::Conv_683[FLOAT, 64x64x3x3]
%onnx::Conv_686[FLOAT, 64x64x1x1]
%onnx::Conv_689[FLOAT, 128x128x1x1]
%onnx::Conv_692[FLOAT, 128x128x1x1]
%onnx::Conv_695[FLOAT, 128x128x3x3]
%onnx::Conv_698[FLOAT, 128x128x1x1]
%onnx::Conv_701[FLOAT, 256x128x1x1]
%onnx::Conv_702[FLOAT, 256]
%onnx::Conv_704[FLOAT, 128x256x1x1]
%onnx::Conv_707[FLOAT, 128x128x3x3]
%onnx::Conv_710[FLOAT, 128x128x1x1]
%onnx::Conv_713[FLOAT, 256x256x1x1]
%onnx::Conv_716[FLOAT, 128x256x1x1]
%onnx::Conv_719[FLOAT, 128x128x3x3]
%onnx::Conv_722[FLOAT, 128x128x1x1]
%onnx::Conv_725[FLOAT, 256x256x1x1]
%onnx::Conv_728[FLOAT, 256x256x1x1]
%onnx::Conv_731[FLOAT, 256x256x3x3]
%onnx::Conv_734[FLOAT, 256x256x1x1]
%onnx::Conv_737[FLOAT, 512x256x1x1]
%onnx::Conv_738[FLOAT, 512]
%onnx::Conv_740[FLOAT, 256x512x1x1]
%onnx::Conv_743[FLOAT, 256x256x3x3]
%onnx::Conv_746[FLOAT, 256x256x1x1]
%onnx::Conv_749[FLOAT, 512x512x1x1]
%onnx::Conv_752[FLOAT, 256x512x1x1]
%onnx::Conv_755[FLOAT, 256x256x3x3]
%onnx::Conv_758[FLOAT, 256x256x1x1]
%onnx::Conv_761[FLOAT, 512x512x1x1]
) {
%onnx::Conv_762 = Identity(%onnx::Conv_738)
%onnx::Conv_759 = Identity(%onnx::Conv_702)
%onnx::Conv_756 = Identity(%onnx::Conv_702)
%onnx::Conv_753 = Identity(%onnx::Conv_702)
%onnx::Conv_750 = Identity(%onnx::Conv_738)
%onnx::Conv_747 = Identity(%onnx::Conv_702)
%onnx::Conv_744 = Identity(%onnx::Conv_702)
%onnx::Conv_741 = Identity(%onnx::Conv_702)
%onnx::Conv_735 = Identity(%onnx::Conv_702)
%onnx::Conv_732 = Identity(%onnx::Conv_702)
%onnx::Conv_729 = Identity(%onnx::Conv_702)
%onnx::Conv_726 = Identity(%onnx::Conv_702)
%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_702)
%onnx::Conv_711 = Identity(%onnx::Conv_654)
%onnx::Conv_708 = Identity(%onnx::Conv_654)
%onnx::Conv_705 = 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_654)
%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_654)
%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_654)
%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/conv3x3/conv_bn_relu/conv_bn_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_659, %onnx::Conv_660)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_662, %onnx::Conv_663)
%/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_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/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_2_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_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_665, %onnx::Conv_666)
%/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_3_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_3_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/conv3x3/conv_bn_relu/conv_bn_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_671, %onnx::Conv_672)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_674, %onnx::Conv_675)
%/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_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/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_2_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_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_3_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/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_3_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_3_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/conv3x3/conv_bn_relu/conv_bn_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_683, %onnx::Conv_684)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_686, %onnx::Conv_687)
%/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_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/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_2_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_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_3_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/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_3_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_3_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/conv3x3/conv_bn_relu/conv_bn_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_695, %onnx::Conv_696)
%/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/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_698, %onnx::Conv_699)
%/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_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/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_2_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_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_701, %onnx::Conv_702)
%/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_3_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_3_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/conv3x3/conv_bn_relu/conv_bn_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_707, %onnx::Conv_708)
%/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/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_710, %onnx::Conv_711)
%/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_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/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_2_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_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_3_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/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_3_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_3_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/conv3x3/conv_bn_relu/conv_bn_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_719, %onnx::Conv_720)
%/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/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_722, %onnx::Conv_723)
%/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_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/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_2_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_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_3_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/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_3_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_3_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/conv3x3/conv_bn_relu/conv_bn_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_731, %onnx::Conv_732)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_734, %onnx::Conv_735)
%/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_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/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_2_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_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_737, %onnx::Conv_738)
%/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_3_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_3_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/conv3x3/conv_bn_relu/conv_bn_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_743, %onnx::Conv_744)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_746, %onnx::Conv_747)
%/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_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/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_2_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_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_3_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/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_3_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_3_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/conv3x3/conv_bn_relu/conv_bn_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_755, %onnx::Conv_756)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_758, %onnx::Conv_759)
%/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_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/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_2_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_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_3_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/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_3_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_3_output_0)
%651 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %651
}
|
val_accuracy
| 91.155851
| 1,179,527,168
| 3,905,290
|
{'zcp_epe_nas': 103.8237914189678, 'zcp_fisher': 7.7525153160095215, 'zcp_flops': 18872434688.0, 'zcp_grad_norm': 53.65375518798828, 'zcp_grasp': -9.29034423828125, 'zcp_jacov': -16.053124797980608, 'zcp_l2_norm': 694.864013671875, 'zcp_nwot': 221.4366525523875, 'zcp_params': 3905290.0, 'zcp_plain': 0.10197880864143301, 'zcp_snip': 340.5071105957031, 'zcp_synflow': 63.93628112454428, 'zcp_zen': 73.61317443847656, 'zcp_val_accuracy': 0.8944311141967771}
| |
NASBench101_104295
|
NASBench101
|
104295
|
3f19fbda99d0971f5d0bb51303b7e1af
|
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, 128x128x1x1]
%onnx::Conv_731[FLOAT, 128x128x3x3]
%onnx::Conv_734[FLOAT, 128x128x1x1]
%onnx::Conv_737[FLOAT, 128x128x1x1]
%onnx::Conv_740[FLOAT, 128x128x3x3]
%onnx::Conv_743[FLOAT, 128x128x1x1]
%onnx::Conv_746[FLOAT, 128x128x3x3]
%onnx::Conv_749[FLOAT, 128x128x1x1]
%onnx::Conv_752[FLOAT, 128x128x1x1]
%onnx::Conv_755[FLOAT, 128x128x3x3]
%onnx::Conv_758[FLOAT, 128x128x1x1]
%onnx::Conv_761[FLOAT, 128x128x3x3]
%onnx::Conv_764[FLOAT, 128x128x1x1]
%onnx::Conv_767[FLOAT, 128x128x1x1]
%onnx::Conv_770[FLOAT, 128x128x3x3]
%onnx::Conv_773[FLOAT, 256x128x1x1]
%onnx::Conv_774[FLOAT, 256]
%onnx::Conv_776[FLOAT, 256x256x3x3]
%onnx::Conv_779[FLOAT, 256x128x1x1]
%onnx::Conv_782[FLOAT, 256x256x1x1]
%onnx::Conv_785[FLOAT, 256x256x3x3]
%onnx::Conv_788[FLOAT, 256x256x1x1]
%onnx::Conv_791[FLOAT, 256x256x3x3]
%onnx::Conv_794[FLOAT, 256x256x1x1]
%onnx::Conv_797[FLOAT, 256x256x1x1]
%onnx::Conv_800[FLOAT, 256x256x3x3]
%onnx::Conv_803[FLOAT, 256x256x1x1]
%onnx::Conv_806[FLOAT, 256x256x3x3]
%onnx::Conv_809[FLOAT, 256x256x1x1]
%onnx::Conv_812[FLOAT, 256x256x1x1]
%onnx::Conv_815[FLOAT, 256x256x3x3]
%onnx::Conv_818[FLOAT, 512x256x1x1]
%onnx::Conv_819[FLOAT, 512]
%onnx::Conv_821[FLOAT, 512x512x3x3]
%onnx::Conv_824[FLOAT, 512x256x1x1]
%onnx::Conv_827[FLOAT, 512x512x1x1]
%onnx::Conv_830[FLOAT, 512x512x3x3]
%onnx::Conv_833[FLOAT, 512x512x1x1]
%onnx::Conv_836[FLOAT, 512x512x3x3]
%onnx::Conv_839[FLOAT, 512x512x1x1]
%onnx::Conv_842[FLOAT, 512x512x1x1]
%onnx::Conv_845[FLOAT, 512x512x3x3]
%onnx::Conv_848[FLOAT, 512x512x1x1]
%onnx::Conv_851[FLOAT, 512x512x3x3]
%onnx::Conv_854[FLOAT, 512x512x1x1]
%onnx::Conv_857[FLOAT, 512x512x1x1]
%onnx::Conv_860[FLOAT, 512x512x3x3]
) {
%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_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)
%onnx::Conv_771 = Identity(%onnx::Conv_726)
%onnx::Conv_768 = Identity(%onnx::Conv_726)
%onnx::Conv_765 = Identity(%onnx::Conv_726)
%onnx::Conv_762 = Identity(%onnx::Conv_726)
%onnx::Conv_759 = Identity(%onnx::Conv_726)
%onnx::Conv_756 = Identity(%onnx::Conv_726)
%onnx::Conv_753 = Identity(%onnx::Conv_726)
%onnx::Conv_750 = Identity(%onnx::Conv_726)
%onnx::Conv_747 = Identity(%onnx::Conv_726)
%onnx::Conv_744 = Identity(%onnx::Conv_726)
%onnx::Conv_741 = Identity(%onnx::Conv_726)
%onnx::Conv_738 = Identity(%onnx::Conv_726)
%onnx::Conv_735 = Identity(%onnx::Conv_726)
%onnx::Conv_732 = Identity(%onnx::Conv_726)
%onnx::Conv_729 = Identity(%onnx::Conv_726)
%/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/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_731, %onnx::Conv_732)
%/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_734, %onnx::Conv_735)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_737, %onnx::Conv_738)
%/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_740, %onnx::Conv_741)
%/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_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/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_746, %onnx::Conv_747)
%/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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_752, %onnx::Conv_753)
%/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_755, %onnx::Conv_756)
%/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_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/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_761, %onnx::Conv_762)
%/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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/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/conv1x1/conv_bn_relu/conv_bn_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_767, %onnx::Conv_768)
%/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_770, %onnx::Conv_771)
%/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_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/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_776, %onnx::Conv_777)
%/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_779, %onnx::Conv_780)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_782, %onnx::Conv_783)
%/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_785, %onnx::Conv_786)
%/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_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/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_791, %onnx::Conv_792)
%/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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_797, %onnx::Conv_798)
%/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_800, %onnx::Conv_801)
%/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_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/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_806, %onnx::Conv_807)
%/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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/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/conv1x1/conv_bn_relu/conv_bn_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_812, %onnx::Conv_813)
%/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_815, %onnx::Conv_816)
%/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_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/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_821, %onnx::Conv_822)
%/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_824, %onnx::Conv_825)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_827, %onnx::Conv_828)
%/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_830, %onnx::Conv_831)
%/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_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/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_836, %onnx::Conv_837)
%/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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_842, %onnx::Conv_843)
%/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_845, %onnx::Conv_846)
%/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_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/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_851, %onnx::Conv_852)
%/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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/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/conv1x1/conv_bn_relu/conv_bn_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_857, %onnx::Conv_858)
%/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_860, %onnx::Conv_861)
%/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)
%723 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %723
}
|
val_accuracy
| 92.28766
| 6,310,340,608
| 21,384,074
|
{'zcp_epe_nas': 101.9677755821726, 'zcp_fisher': 23.14020347595215, 'zcp_flops': 100965449728.0, 'zcp_grad_norm': 78.71659088134766, 'zcp_grasp': 1.023162841796875, 'zcp_jacov': -16.05640410020822, 'zcp_l2_norm': 1029.9107666015625, 'zcp_nwot': 231.82392364710626, 'zcp_params': 21384074.0, 'zcp_plain': 0.07158488035202, 'zcp_snip': 687.28369140625, 'zcp_synflow': 129.93802150845, 'zcp_zen': 102.74156188964844, 'zcp_val_accuracy': 0.923577725887298}
| |
NASBench101_250371
|
NASBench101
|
250371
|
978b72939863800f5894e5b128354f07
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_773[FLOAT, 128x3x3x3]
%onnx::Conv_774[FLOAT, 128]
%onnx::Conv_776[FLOAT, 43x128x1x1]
%onnx::Conv_777[FLOAT, 43]
%onnx::Conv_779[FLOAT, 43x43x1x1]
%onnx::Conv_782[FLOAT, 43x128x1x1]
%onnx::Conv_785[FLOAT, 43x43x1x1]
%onnx::Conv_788[FLOAT, 128x128x1x1]
%onnx::Conv_791[FLOAT, 43x128x1x1]
%onnx::Conv_794[FLOAT, 43x43x1x1]
%onnx::Conv_797[FLOAT, 43x128x1x1]
%onnx::Conv_800[FLOAT, 43x43x1x1]
%onnx::Conv_803[FLOAT, 128x128x1x1]
%onnx::Conv_806[FLOAT, 43x128x1x1]
%onnx::Conv_809[FLOAT, 43x43x1x1]
%onnx::Conv_812[FLOAT, 43x128x1x1]
%onnx::Conv_815[FLOAT, 43x43x1x1]
%onnx::Conv_818[FLOAT, 128x128x1x1]
%onnx::Conv_821[FLOAT, 86x128x1x1]
%onnx::Conv_822[FLOAT, 86]
%onnx::Conv_824[FLOAT, 86x86x1x1]
%onnx::Conv_827[FLOAT, 85x128x1x1]
%onnx::Conv_828[FLOAT, 85]
%onnx::Conv_830[FLOAT, 85x85x1x1]
%onnx::Conv_833[FLOAT, 256x128x1x1]
%onnx::Conv_834[FLOAT, 256]
%onnx::Conv_836[FLOAT, 86x256x1x1]
%onnx::Conv_839[FLOAT, 86x86x1x1]
%onnx::Conv_842[FLOAT, 85x256x1x1]
%onnx::Conv_845[FLOAT, 85x85x1x1]
%onnx::Conv_848[FLOAT, 256x256x1x1]
%onnx::Conv_851[FLOAT, 86x256x1x1]
%onnx::Conv_854[FLOAT, 86x86x1x1]
%onnx::Conv_857[FLOAT, 85x256x1x1]
%onnx::Conv_860[FLOAT, 85x85x1x1]
%onnx::Conv_863[FLOAT, 256x256x1x1]
%onnx::Conv_866[FLOAT, 171x256x1x1]
%onnx::Conv_867[FLOAT, 171]
%onnx::Conv_869[FLOAT, 171x171x1x1]
%onnx::Conv_872[FLOAT, 171x256x1x1]
%onnx::Conv_875[FLOAT, 171x171x1x1]
%onnx::Conv_878[FLOAT, 512x256x1x1]
%onnx::Conv_879[FLOAT, 512]
%onnx::Conv_881[FLOAT, 171x512x1x1]
%onnx::Conv_884[FLOAT, 171x171x1x1]
%onnx::Conv_887[FLOAT, 171x512x1x1]
%onnx::Conv_890[FLOAT, 171x171x1x1]
%onnx::Conv_893[FLOAT, 512x512x1x1]
%onnx::Conv_896[FLOAT, 171x512x1x1]
%onnx::Conv_899[FLOAT, 171x171x1x1]
%onnx::Conv_902[FLOAT, 171x512x1x1]
%onnx::Conv_905[FLOAT, 171x171x1x1]
%onnx::Conv_908[FLOAT, 512x512x1x1]
) {
%onnx::Conv_909 = Identity(%onnx::Conv_879)
%onnx::Conv_906 = Identity(%onnx::Conv_867)
%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_879)
%onnx::Conv_891 = Identity(%onnx::Conv_867)
%onnx::Conv_888 = Identity(%onnx::Conv_867)
%onnx::Conv_885 = Identity(%onnx::Conv_867)
%onnx::Conv_882 = Identity(%onnx::Conv_867)
%onnx::Conv_876 = Identity(%onnx::Conv_867)
%onnx::Conv_873 = Identity(%onnx::Conv_867)
%onnx::Conv_870 = Identity(%onnx::Conv_867)
%onnx::Conv_864 = Identity(%onnx::Conv_834)
%onnx::Conv_861 = Identity(%onnx::Conv_828)
%onnx::Conv_858 = Identity(%onnx::Conv_828)
%onnx::Conv_855 = Identity(%onnx::Conv_822)
%onnx::Conv_852 = Identity(%onnx::Conv_822)
%onnx::Conv_849 = Identity(%onnx::Conv_834)
%onnx::Conv_846 = Identity(%onnx::Conv_828)
%onnx::Conv_843 = Identity(%onnx::Conv_828)
%onnx::Conv_840 = Identity(%onnx::Conv_822)
%onnx::Conv_837 = Identity(%onnx::Conv_822)
%onnx::Conv_831 = Identity(%onnx::Conv_828)
%onnx::Conv_825 = Identity(%onnx::Conv_822)
%onnx::Conv_819 = Identity(%onnx::Conv_774)
%onnx::Conv_816 = Identity(%onnx::Conv_777)
%onnx::Conv_813 = Identity(%onnx::Conv_777)
%onnx::Conv_810 = Identity(%onnx::Conv_777)
%onnx::Conv_807 = Identity(%onnx::Conv_777)
%onnx::Conv_804 = Identity(%onnx::Conv_774)
%onnx::Conv_801 = Identity(%onnx::Conv_777)
%onnx::Conv_798 = Identity(%onnx::Conv_777)
%onnx::Conv_795 = Identity(%onnx::Conv_777)
%onnx::Conv_792 = Identity(%onnx::Conv_777)
%onnx::Conv_789 = Identity(%onnx::Conv_774)
%onnx::Conv_786 = Identity(%onnx::Conv_777)
%onnx::Conv_783 = Identity(%onnx::Conv_777)
%onnx::Conv_780 = Identity(%onnx::Conv_777)
%/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_773, %onnx::Conv_774)
%/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_776, %onnx::Conv_777)
%/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_779, %onnx::Conv_780)
%/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_782, %onnx::Conv_783)
%/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_785, %onnx::Conv_786)
%/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/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/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/Slice_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.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.5/maxpool/MaxPool_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_788, %onnx::Conv_789)
%/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_2_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_2_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/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_794, %onnx::Conv_795)
%/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_2_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/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_800, %onnx::Conv_801)
%/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/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/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/Slice_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.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.5/maxpool/MaxPool_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_2_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/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_2_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_2_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/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_809, %onnx::Conv_810)
%/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_2_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/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_815, %onnx::Conv_816)
%/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/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/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/Slice_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.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.5/maxpool/MaxPool_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_2_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/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_2_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_2_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_821, %onnx::Conv_822)
%/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_824, %onnx::Conv_825)
%/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_827, %onnx::Conv_828)
%/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_830, %onnx::Conv_831)
%/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/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.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.5/maxpool/MaxPool_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_833, %onnx::Conv_834)
%/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_2_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_2_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/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_839, %onnx::Conv_840)
%/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_2_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/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_845, %onnx::Conv_846)
%/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/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.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.5/maxpool/MaxPool_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_2_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/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_2_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_2_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/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_854, %onnx::Conv_855)
%/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_2_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/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_860, %onnx::Conv_861)
%/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/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.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.5/maxpool/MaxPool_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_2_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/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_2_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_2_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_866, %onnx::Conv_867)
%/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_869, %onnx::Conv_870)
%/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_872, %onnx::Conv_873)
%/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_875, %onnx::Conv_876)
%/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/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/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/Slice_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.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.5/maxpool/MaxPool_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_878, %onnx::Conv_879)
%/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_2_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_2_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/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_884, %onnx::Conv_885)
%/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_2_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/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_890, %onnx::Conv_891)
%/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/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/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/Slice_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.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.5/maxpool/MaxPool_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_2_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/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_2_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_2_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/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_899, %onnx::Conv_900)
%/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_2_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/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_905, %onnx::Conv_906)
%/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/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/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/Slice_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.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.5/maxpool/MaxPool_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_2_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/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_2_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_2_output_0)
%771 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %771
}
|
val_accuracy
| 89.573318
| 536,791,296
| 1,700,385
|
{'zcp_epe_nas': 111.82693115296968, 'zcp_fisher': 2.765563488006592, 'zcp_flops': 8588660736.0, 'zcp_grad_norm': 37.922874450683594, 'zcp_grasp': -11.247062683105469, 'zcp_jacov': -16.0636784533783, 'zcp_l2_norm': 835.1452026367188, 'zcp_nwot': 220.82356323898057, 'zcp_params': 1700385.0, 'zcp_plain': 0.192792385816574, 'zcp_snip': 203.2632598876953, 'zcp_synflow': 54.76275714144397, 'zcp_zen': 70.92434692382812, 'zcp_val_accuracy': 0.9384014606475831}
| |
NASBench101_322352
|
NASBench101
|
322352
|
c30cd33cee1cd82ac53572e98621a0e5
|
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, 128x128x1x1]
%onnx::Conv_881[FLOAT, 128x128x3x3]
%onnx::Conv_884[FLOAT, 128x128x1x1]
%onnx::Conv_887[FLOAT, 128x128x1x1]
%onnx::Conv_890[FLOAT, 128x128x1x1]
%onnx::Conv_893[FLOAT, 128x128x1x1]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%onnx::Conv_899[FLOAT, 128x128x3x3]
%onnx::Conv_902[FLOAT, 128x128x1x1]
%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, 128x128x1x1]
%onnx::Conv_923[FLOAT, 128x128x1x1]
%onnx::Conv_926[FLOAT, 256x128x1x1]
%onnx::Conv_927[FLOAT, 256]
%onnx::Conv_929[FLOAT, 256x256x1x1]
%onnx::Conv_932[FLOAT, 256x128x1x1]
%onnx::Conv_935[FLOAT, 256x256x3x3]
%onnx::Conv_938[FLOAT, 256x256x1x1]
%onnx::Conv_941[FLOAT, 256x256x1x1]
%onnx::Conv_944[FLOAT, 256x256x1x1]
%onnx::Conv_947[FLOAT, 256x256x1x1]
%onnx::Conv_950[FLOAT, 256x256x1x1]
%onnx::Conv_953[FLOAT, 256x256x3x3]
%onnx::Conv_956[FLOAT, 256x256x1x1]
%onnx::Conv_959[FLOAT, 256x256x1x1]
%onnx::Conv_962[FLOAT, 256x256x1x1]
%onnx::Conv_965[FLOAT, 256x256x1x1]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 256x256x3x3]
%onnx::Conv_974[FLOAT, 256x256x1x1]
%onnx::Conv_977[FLOAT, 256x256x1x1]
%onnx::Conv_980[FLOAT, 512x256x1x1]
%onnx::Conv_981[FLOAT, 512]
%onnx::Conv_983[FLOAT, 512x512x1x1]
%onnx::Conv_986[FLOAT, 512x256x1x1]
%onnx::Conv_989[FLOAT, 512x512x3x3]
%onnx::Conv_992[FLOAT, 512x512x1x1]
%onnx::Conv_995[FLOAT, 512x512x1x1]
%onnx::Conv_998[FLOAT, 512x512x1x1]
%onnx::Conv_1001[FLOAT, 512x512x1x1]
%onnx::Conv_1004[FLOAT, 512x512x1x1]
%onnx::Conv_1007[FLOAT, 512x512x3x3]
%onnx::Conv_1010[FLOAT, 512x512x1x1]
%onnx::Conv_1013[FLOAT, 512x512x1x1]
%onnx::Conv_1016[FLOAT, 512x512x1x1]
%onnx::Conv_1019[FLOAT, 512x512x1x1]
%onnx::Conv_1022[FLOAT, 512x512x1x1]
%onnx::Conv_1025[FLOAT, 512x512x3x3]
%onnx::Conv_1028[FLOAT, 512x512x1x1]
%onnx::Conv_1031[FLOAT, 512x512x1x1]
) {
%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/input_op.2/conv_bn_relu/conv_bn_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/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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/Add_5_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/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_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.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_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/vertex_op.5/conv1x1/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/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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/Add_5_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/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_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.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_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/vertex_op.5/conv1x1/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/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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/Add_5_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/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_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.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_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/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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/Add_5_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/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_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.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_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/vertex_op.5/conv1x1/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/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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/Add_5_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/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_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.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_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/vertex_op.5/conv1x1/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/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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/Add_5_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/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_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.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_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/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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/Add_5_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/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_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.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_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/vertex_op.5/conv1x1/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/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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/Add_5_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/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_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.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_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/vertex_op.5/conv1x1/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/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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/Add_5_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/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_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)
%/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)
%867 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %867
}
|
val_accuracy
| 90.464741
| 4,201,916,416
| 14,164,106
|
{'zcp_epe_nas': 110.25621232928142, 'zcp_fisher': 61.053253173828125, 'zcp_flops': 67230662656.0, 'zcp_grad_norm': 181.84970092773438, 'zcp_grasp': 86.189453125, 'zcp_jacov': -16.05698393486628, 'zcp_l2_norm': 1242.635498046875, 'zcp_nwot': 235.35653994560448, 'zcp_params': 14164106.0, 'zcp_plain': 0.001542897429317, 'zcp_snip': 1277.47021484375, 'zcp_synflow': 122.29061147066342, 'zcp_zen': 101.43342590332031, 'zcp_val_accuracy': 0.906850934028625}
| |
NASBench101_201402
|
NASBench101
|
201402
|
79eff3db6f9c4d0337b21f287683fead
|
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, 128x128x1x1]
%onnx::Conv_785[FLOAT, 128x128x3x3]
%onnx::Conv_788[FLOAT, 128x128x3x3]
%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, 128x128x1x1]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 128x128x3x3]
%onnx::Conv_818[FLOAT, 128x128x3x3]
%onnx::Conv_821[FLOAT, 128x128x1x1]
%onnx::Conv_824[FLOAT, 128x128x1x1]
%onnx::Conv_827[FLOAT, 256x128x1x1]
%onnx::Conv_828[FLOAT, 256]
%onnx::Conv_830[FLOAT, 256x256x3x3]
%onnx::Conv_833[FLOAT, 256x256x3x3]
%onnx::Conv_836[FLOAT, 256x128x1x1]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x256x1x1]
%onnx::Conv_845[FLOAT, 256x256x3x3]
%onnx::Conv_848[FLOAT, 256x256x3x3]
%onnx::Conv_851[FLOAT, 256x256x1x1]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_857[FLOAT, 256x256x1x1]
%onnx::Conv_860[FLOAT, 256x256x3x3]
%onnx::Conv_863[FLOAT, 256x256x3x3]
%onnx::Conv_866[FLOAT, 256x256x1x1]
%onnx::Conv_869[FLOAT, 256x256x1x1]
%onnx::Conv_872[FLOAT, 512x256x1x1]
%onnx::Conv_873[FLOAT, 512]
%onnx::Conv_875[FLOAT, 512x512x3x3]
%onnx::Conv_878[FLOAT, 512x512x3x3]
%onnx::Conv_881[FLOAT, 512x256x1x1]
%onnx::Conv_884[FLOAT, 512x512x1x1]
%onnx::Conv_887[FLOAT, 512x512x1x1]
%onnx::Conv_890[FLOAT, 512x512x3x3]
%onnx::Conv_893[FLOAT, 512x512x3x3]
%onnx::Conv_896[FLOAT, 512x512x1x1]
%onnx::Conv_899[FLOAT, 512x512x1x1]
%onnx::Conv_902[FLOAT, 512x512x1x1]
%onnx::Conv_905[FLOAT, 512x512x3x3]
%onnx::Conv_908[FLOAT, 512x512x3x3]
%onnx::Conv_911[FLOAT, 512x512x1x1]
%onnx::Conv_914[FLOAT, 512x512x1x1]
) {
%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_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_780)
%onnx::Conv_822 = Identity(%onnx::Conv_780)
%onnx::Conv_819 = Identity(%onnx::Conv_780)
%onnx::Conv_816 = Identity(%onnx::Conv_780)
%onnx::Conv_813 = Identity(%onnx::Conv_780)
%onnx::Conv_810 = Identity(%onnx::Conv_780)
%onnx::Conv_807 = Identity(%onnx::Conv_780)
%onnx::Conv_804 = Identity(%onnx::Conv_780)
%onnx::Conv_801 = Identity(%onnx::Conv_780)
%onnx::Conv_798 = Identity(%onnx::Conv_780)
%onnx::Conv_795 = Identity(%onnx::Conv_780)
%onnx::Conv_792 = Identity(%onnx::Conv_780)
%onnx::Conv_789 = Identity(%onnx::Conv_780)
%onnx::Conv_786 = Identity(%onnx::Conv_780)
%onnx::Conv_783 = Identity(%onnx::Conv_780)
%/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/conv3x3/conv_bn_relu/conv_bn_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_785, %onnx::Conv_786)
%/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_788, %onnx::Conv_789)
%/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_791, %onnx::Conv_792)
%/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_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/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/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_6_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_800, %onnx::Conv_801)
%/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_803, %onnx::Conv_804)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/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_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/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/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_6_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_815, %onnx::Conv_816)
%/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_818, %onnx::Conv_819)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/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_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/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/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_6_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_830, %onnx::Conv_831)
%/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/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/conv3x3/conv_bn_relu/conv_bn_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_833, %onnx::Conv_834)
%/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_836, %onnx::Conv_837)
%/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_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/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/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_6_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_845, %onnx::Conv_846)
%/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/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/conv3x3/conv_bn_relu/conv_bn_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_848, %onnx::Conv_849)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/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_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/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/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_6_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_860, %onnx::Conv_861)
%/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/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/conv3x3/conv_bn_relu/conv_bn_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_863, %onnx::Conv_864)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/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_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/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/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_6_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_875, %onnx::Conv_876)
%/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_878, %onnx::Conv_879)
%/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_881, %onnx::Conv_882)
%/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_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/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/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_6_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_890, %onnx::Conv_891)
%/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_893, %onnx::Conv_894)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/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_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/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/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_6_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_905, %onnx::Conv_906)
%/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_908, %onnx::Conv_909)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/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_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/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/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_6_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/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)
%777 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %777
}
|
val_accuracy
| 93.719953
| 6,310,340,608
| 21,384,074
|
{'zcp_epe_nas': 63.10877123149728, 'zcp_fisher': 70.39704895019531, 'zcp_flops': 100965449728.0, 'zcp_grad_norm': 124.2232894897461, 'zcp_grasp': 4.3668212890625, 'zcp_jacov': -16.063270123992176, 'zcp_l2_norm': 1030.4815673828125, 'zcp_nwot': 232.11627938014917, 'zcp_params': 21384074.0, 'zcp_plain': 0.042402278631925, 'zcp_snip': 1039.872314453125, 'zcp_synflow': 135.88637088988602, 'zcp_zen': 102.6247329711914, 'zcp_val_accuracy': 0.905048072338104}
| |
NASBench101_42524
|
NASBench101
|
42524
|
19c81525f8ed1ce9b1e661dbe012ca09
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_707[FLOAT, 128x3x3x3]
%onnx::Conv_708[FLOAT, 128]
%onnx::Conv_710[FLOAT, 43x128x1x1]
%onnx::Conv_711[FLOAT, 43]
%onnx::Conv_713[FLOAT, 43x43x1x1]
%onnx::Conv_716[FLOAT, 43x43x1x1]
%onnx::Conv_719[FLOAT, 128x128x1x1]
%onnx::Conv_722[FLOAT, 43x128x1x1]
%onnx::Conv_725[FLOAT, 43x43x1x1]
%onnx::Conv_728[FLOAT, 43x43x1x1]
%onnx::Conv_731[FLOAT, 128x128x1x1]
%onnx::Conv_734[FLOAT, 43x128x1x1]
%onnx::Conv_737[FLOAT, 43x43x1x1]
%onnx::Conv_740[FLOAT, 43x43x1x1]
%onnx::Conv_743[FLOAT, 128x128x1x1]
%onnx::Conv_746[FLOAT, 86x128x1x1]
%onnx::Conv_747[FLOAT, 86]
%onnx::Conv_749[FLOAT, 86x86x1x1]
%onnx::Conv_752[FLOAT, 86x86x1x1]
%onnx::Conv_755[FLOAT, 256x128x1x1]
%onnx::Conv_756[FLOAT, 256]
%onnx::Conv_758[FLOAT, 86x256x1x1]
%onnx::Conv_761[FLOAT, 86x86x1x1]
%onnx::Conv_764[FLOAT, 86x86x1x1]
%onnx::Conv_767[FLOAT, 256x256x1x1]
%onnx::Conv_770[FLOAT, 86x256x1x1]
%onnx::Conv_773[FLOAT, 86x86x1x1]
%onnx::Conv_776[FLOAT, 86x86x1x1]
%onnx::Conv_779[FLOAT, 256x256x1x1]
%onnx::Conv_782[FLOAT, 171x256x1x1]
%onnx::Conv_783[FLOAT, 171]
%onnx::Conv_785[FLOAT, 171x171x1x1]
%onnx::Conv_788[FLOAT, 171x171x1x1]
%onnx::Conv_791[FLOAT, 512x256x1x1]
%onnx::Conv_792[FLOAT, 512]
%onnx::Conv_794[FLOAT, 171x512x1x1]
%onnx::Conv_797[FLOAT, 171x171x1x1]
%onnx::Conv_800[FLOAT, 171x171x1x1]
%onnx::Conv_803[FLOAT, 512x512x1x1]
%onnx::Conv_806[FLOAT, 171x512x1x1]
%onnx::Conv_809[FLOAT, 171x171x1x1]
%onnx::Conv_812[FLOAT, 171x171x1x1]
%onnx::Conv_815[FLOAT, 512x512x1x1]
) {
%onnx::Conv_816 = Identity(%onnx::Conv_792)
%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_792)
%onnx::Conv_801 = Identity(%onnx::Conv_783)
%onnx::Conv_798 = Identity(%onnx::Conv_783)
%onnx::Conv_795 = Identity(%onnx::Conv_783)
%onnx::Conv_789 = Identity(%onnx::Conv_783)
%onnx::Conv_786 = Identity(%onnx::Conv_783)
%onnx::Conv_780 = Identity(%onnx::Conv_756)
%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_756)
%onnx::Conv_765 = Identity(%onnx::Conv_747)
%onnx::Conv_762 = Identity(%onnx::Conv_747)
%onnx::Conv_759 = Identity(%onnx::Conv_747)
%onnx::Conv_753 = Identity(%onnx::Conv_747)
%onnx::Conv_750 = Identity(%onnx::Conv_747)
%onnx::Conv_744 = Identity(%onnx::Conv_708)
%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)
%/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_707, %onnx::Conv_708)
%/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_710, %onnx::Conv_711)
%/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_713, %onnx::Conv_714)
%/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_716, %onnx::Conv_717)
%/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.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_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.4/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/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/Slice_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.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_719, %onnx::Conv_720)
%/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_3_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_3_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/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_725, %onnx::Conv_726)
%/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_728, %onnx::Conv_729)
%/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.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_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.4/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/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/Slice_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.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_3_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/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_3_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_3_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/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_737, %onnx::Conv_738)
%/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_740, %onnx::Conv_741)
%/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.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_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.4/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/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/Slice_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.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_3_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/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_3_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_3_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_746, %onnx::Conv_747)
%/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_749, %onnx::Conv_750)
%/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_752, %onnx::Conv_753)
%/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 = <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.3/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.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/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.4/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_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_755, %onnx::Conv_756)
%/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_3_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_3_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/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_761, %onnx::Conv_762)
%/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_764, %onnx::Conv_765)
%/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 = <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.3/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.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/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.4/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_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_3_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/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_3_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_3_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/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_773, %onnx::Conv_774)
%/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_776, %onnx::Conv_777)
%/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 = <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.3/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.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/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.4/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_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_3_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/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_3_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_3_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_782, %onnx::Conv_783)
%/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_785, %onnx::Conv_786)
%/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_788, %onnx::Conv_789)
%/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.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_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.4/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/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/Slice_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.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_791, %onnx::Conv_792)
%/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_3_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_3_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/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_797, %onnx::Conv_798)
%/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_800, %onnx::Conv_801)
%/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.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_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.4/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/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/Slice_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.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_3_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/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_3_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_3_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/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_809, %onnx::Conv_810)
%/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_812, %onnx::Conv_813)
%/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.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_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.4/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/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/Slice_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)
%/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_3_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/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_3_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_3_output_0)
%705 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %705
}
|
val_accuracy
| 88.972354
| 445,532,416
| 1,409,318
|
{'zcp_epe_nas': 107.34674376443367, 'zcp_fisher': 36.39461898803711, 'zcp_flops': 7128518656.0, 'zcp_grad_norm': 132.42416381835938, 'zcp_grasp': -8.377197265625, 'zcp_jacov': -16.051720597024307, 'zcp_l2_norm': 641.6889038085938, 'zcp_nwot': 218.47733437262366, 'zcp_params': 1409318.0, 'zcp_plain': 0.13350073993206002, 'zcp_snip': 646.1454467773438, 'zcp_synflow': 78.94185328430937, 'zcp_zen': 58.103782653808594, 'zcp_val_accuracy': 0.933393418788909}
| |
NASBench101_296097
|
NASBench101
|
296097
|
b33dac8514b7d6cccf72fc71d0eef24c
|
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, 64x64x3x3]
%onnx::Conv_875[FLOAT, 64x64x1x1]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_884[FLOAT, 64x64x3x3]
%onnx::Conv_887[FLOAT, 64x128x1x1]
%onnx::Conv_890[FLOAT, 64x64x3x3]
%onnx::Conv_893[FLOAT, 64x64x1x1]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x128x1x1]
%onnx::Conv_908[FLOAT, 64x64x3x3]
%onnx::Conv_911[FLOAT, 64x64x1x1]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 128x128x1x1]
%onnx::Conv_920[FLOAT, 128x128x3x3]
%onnx::Conv_923[FLOAT, 128x128x1x1]
%onnx::Conv_926[FLOAT, 128x128x3x3]
%onnx::Conv_929[FLOAT, 128x128x1x1]
%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, 128x128x3x3]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 256x256x1x1]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x256x1x1]
%onnx::Conv_962[FLOAT, 128x128x3x3]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 256x256x1x1]
%onnx::Conv_974[FLOAT, 256x256x3x3]
%onnx::Conv_977[FLOAT, 256x256x1x1]
%onnx::Conv_980[FLOAT, 256x256x3x3]
%onnx::Conv_983[FLOAT, 256x256x1x1]
%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, 256x256x3x3]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 512x512x1x1]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x512x1x1]
%onnx::Conv_1016[FLOAT, 256x256x3x3]
%onnx::Conv_1019[FLOAT, 256x256x1x1]
%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/input_op.2/conv_bn_relu/conv_bn_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.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/conv3x3/conv_bn_relu/conv_bn_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_872, %onnx::Conv_873)
%/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.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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_875, %onnx::Conv_876)
%/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.3/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_878, %onnx::Conv_879)
%/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/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_6_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/input_op.2/conv_bn_relu/conv_bn_relu.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_887, %onnx::Conv_888)
%/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/conv3x3/conv_bn_relu/conv_bn_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_890, %onnx::Conv_891)
%/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.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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_893, %onnx::Conv_894)
%/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.3/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_6_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/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/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_6_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/input_op.2/conv_bn_relu/conv_bn_relu.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_905, %onnx::Conv_906)
%/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/conv3x3/conv_bn_relu/conv_bn_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_908, %onnx::Conv_909)
%/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.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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_911, %onnx::Conv_912)
%/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.3/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_6_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/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/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_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_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/input_op.2/conv_bn_relu/conv_bn_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.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/conv3x3/conv_bn_relu/conv_bn_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_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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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.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.3/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_932, %onnx::Conv_933)
%/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/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_6_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/input_op.2/conv_bn_relu/conv_bn_relu.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_941, %onnx::Conv_942)
%/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/conv3x3/conv_bn_relu/conv_bn_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_944, %onnx::Conv_945)
%/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.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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_947, %onnx::Conv_948)
%/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.3/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_6_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/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/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_6_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/input_op.2/conv_bn_relu/conv_bn_relu.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_959, %onnx::Conv_960)
%/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/conv3x3/conv_bn_relu/conv_bn_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_962, %onnx::Conv_963)
%/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.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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_965, %onnx::Conv_966)
%/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.3/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_6_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/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/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_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_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/input_op.2/conv_bn_relu/conv_bn_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.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/conv3x3/conv_bn_relu/conv_bn_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_980, %onnx::Conv_981)
%/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.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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_983, %onnx::Conv_984)
%/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.3/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_986, %onnx::Conv_987)
%/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/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_6_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/input_op.2/conv_bn_relu/conv_bn_relu.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_995, %onnx::Conv_996)
%/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/conv3x3/conv_bn_relu/conv_bn_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_998, %onnx::Conv_999)
%/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.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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_1001, %onnx::Conv_1002)
%/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.3/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_6_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/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/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_6_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/input_op.2/conv_bn_relu/conv_bn_relu.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_1013, %onnx::Conv_1014)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1016, %onnx::Conv_1017)
%/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.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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_1019, %onnx::Conv_1020)
%/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.3/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_6_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/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/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_6_output_0)
%858 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %858
}
|
val_accuracy
| 94.220752
| 1,998,727,168
| 6,667,274
|
{'zcp_epe_nas': 133.3574968094035, 'zcp_fisher': 1.876100659370422, 'zcp_flops': 31979634688.0, 'zcp_grad_norm': 34.0897102355957, 'zcp_grasp': -1.317039489746093, 'zcp_jacov': -16.041375362210044, 'zcp_l2_norm': 1041.1363525390625, 'zcp_nwot': 225.98624788409228, 'zcp_params': 6667274.0, 'zcp_plain': 0.030039666220545002, 'zcp_snip': 219.94517517089844, 'zcp_synflow': 117.66825263674677, 'zcp_zen': 107.21886444091797, 'zcp_val_accuracy': 0.888321340084075}
| |
NASBench101_212989
|
NASBench101
|
212989
|
810a68ecc22d2273d79aa61d20ac0a49
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_536[FLOAT, 128x3x3x3]
%onnx::Conv_537[FLOAT, 128]
%onnx::Conv_539[FLOAT, 43x128x1x1]
%onnx::Conv_540[FLOAT, 43]
%onnx::Conv_542[FLOAT, 43x43x3x3]
%onnx::Conv_545[FLOAT, 42x42x3x3]
%onnx::Conv_546[FLOAT, 42]
%onnx::Conv_548[FLOAT, 43x128x1x1]
%onnx::Conv_551[FLOAT, 43x43x3x3]
%onnx::Conv_554[FLOAT, 42x42x3x3]
%onnx::Conv_557[FLOAT, 43x128x1x1]
%onnx::Conv_560[FLOAT, 43x43x3x3]
%onnx::Conv_563[FLOAT, 42x42x3x3]
%onnx::Conv_566[FLOAT, 86x128x1x1]
%onnx::Conv_567[FLOAT, 86]
%onnx::Conv_569[FLOAT, 85x85x3x3]
%onnx::Conv_570[FLOAT, 85]
%onnx::Conv_572[FLOAT, 85x85x3x3]
%onnx::Conv_575[FLOAT, 86x256x1x1]
%onnx::Conv_578[FLOAT, 85x85x3x3]
%onnx::Conv_581[FLOAT, 85x85x3x3]
%onnx::Conv_584[FLOAT, 86x256x1x1]
%onnx::Conv_587[FLOAT, 85x85x3x3]
%onnx::Conv_590[FLOAT, 85x85x3x3]
%onnx::Conv_593[FLOAT, 171x256x1x1]
%onnx::Conv_594[FLOAT, 171]
%onnx::Conv_596[FLOAT, 171x171x3x3]
%onnx::Conv_599[FLOAT, 170x170x3x3]
%onnx::Conv_600[FLOAT, 170]
%onnx::Conv_602[FLOAT, 171x512x1x1]
%onnx::Conv_605[FLOAT, 171x171x3x3]
%onnx::Conv_608[FLOAT, 170x170x3x3]
%onnx::Conv_611[FLOAT, 171x512x1x1]
%onnx::Conv_614[FLOAT, 171x171x3x3]
%onnx::Conv_617[FLOAT, 170x170x3x3]
) {
%onnx::Conv_618 = Identity(%onnx::Conv_600)
%onnx::Conv_615 = Identity(%onnx::Conv_594)
%onnx::Conv_612 = Identity(%onnx::Conv_594)
%onnx::Conv_609 = Identity(%onnx::Conv_600)
%onnx::Conv_606 = Identity(%onnx::Conv_594)
%onnx::Conv_603 = Identity(%onnx::Conv_594)
%onnx::Conv_597 = Identity(%onnx::Conv_594)
%onnx::Conv_591 = Identity(%onnx::Conv_570)
%onnx::Conv_588 = Identity(%onnx::Conv_570)
%onnx::Conv_585 = Identity(%onnx::Conv_567)
%onnx::Conv_582 = Identity(%onnx::Conv_570)
%onnx::Conv_579 = Identity(%onnx::Conv_570)
%onnx::Conv_576 = Identity(%onnx::Conv_567)
%onnx::Conv_573 = Identity(%onnx::Conv_570)
%onnx::Conv_564 = Identity(%onnx::Conv_546)
%onnx::Conv_561 = Identity(%onnx::Conv_540)
%onnx::Conv_558 = Identity(%onnx::Conv_540)
%onnx::Conv_555 = Identity(%onnx::Conv_546)
%onnx::Conv_552 = Identity(%onnx::Conv_540)
%onnx::Conv_549 = Identity(%onnx::Conv_540)
%onnx::Conv_543 = Identity(%onnx::Conv_540)
%/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_536, %onnx::Conv_537)
%/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_539, %onnx::Conv_540)
%/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_542, %onnx::Conv_543)
%/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.2/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_545, %onnx::Conv_546)
%/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/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_548, %onnx::Conv_549)
%/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_551, %onnx::Conv_552)
%/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.2/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_554, %onnx::Conv_555)
%/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/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_557, %onnx::Conv_558)
%/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_560, %onnx::Conv_561)
%/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.2/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_563, %onnx::Conv_564)
%/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/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_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/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/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/Slice_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_569, %onnx::Conv_570)
%/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_572, %onnx::Conv_573)
%/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/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_575, %onnx::Conv_576)
%/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/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/Slice_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_578, %onnx::Conv_579)
%/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_581, %onnx::Conv_582)
%/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/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_584, %onnx::Conv_585)
%/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/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/Slice_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_587, %onnx::Conv_588)
%/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_590, %onnx::Conv_591)
%/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/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_593, %onnx::Conv_594)
%/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_596, %onnx::Conv_597)
%/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.2/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_599, %onnx::Conv_600)
%/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/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_602, %onnx::Conv_603)
%/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_605, %onnx::Conv_606)
%/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.2/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_608, %onnx::Conv_609)
%/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/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_611, %onnx::Conv_612)
%/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_614, %onnx::Conv_615)
%/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.2/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_617, %onnx::Conv_618)
%/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/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)
%534 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %534
}
|
val_accuracy
| 89.703524
| 704,131,968
| 2,362,158
|
{'zcp_epe_nas': 149.01139913555397, 'zcp_fisher': 2.8201816082000732, 'zcp_flops': 11266111488.0, 'zcp_grad_norm': 29.699522018432617, 'zcp_grasp': -0.45706176757812506, 'zcp_jacov': -16.049162785724583, 'zcp_l2_norm': 443.5763854980469, 'zcp_nwot': 207.5626840419917, 'zcp_params': 2362158.0, 'zcp_plain': 0.002213720232248, 'zcp_snip': 152.4501953125, 'zcp_synflow': 63.45717365918259, 'zcp_zen': 59.998374938964844, 'zcp_val_accuracy': 0.8558694124221801}
| |
NASBench101_118600
|
NASBench101
|
118600
|
479eca14f57508bd926e87a1ab5f76ae
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_905[FLOAT, 128x3x3x3]
%onnx::Conv_906[FLOAT, 128]
%onnx::Conv_908[FLOAT, 43x128x1x1]
%onnx::Conv_909[FLOAT, 43]
%onnx::Conv_911[FLOAT, 43x43x3x3]
%onnx::Conv_914[FLOAT, 43x43x3x3]
%onnx::Conv_917[FLOAT, 43x43x1x1]
%onnx::Conv_920[FLOAT, 42x128x1x1]
%onnx::Conv_921[FLOAT, 42]
%onnx::Conv_923[FLOAT, 42x42x3x3]
%onnx::Conv_926[FLOAT, 43x128x1x1]
%onnx::Conv_929[FLOAT, 43x43x3x3]
%onnx::Conv_932[FLOAT, 43x43x3x3]
%onnx::Conv_935[FLOAT, 43x43x1x1]
%onnx::Conv_938[FLOAT, 42x128x1x1]
%onnx::Conv_941[FLOAT, 42x42x3x3]
%onnx::Conv_944[FLOAT, 43x128x1x1]
%onnx::Conv_947[FLOAT, 43x43x3x3]
%onnx::Conv_950[FLOAT, 43x43x3x3]
%onnx::Conv_953[FLOAT, 43x43x1x1]
%onnx::Conv_956[FLOAT, 42x128x1x1]
%onnx::Conv_959[FLOAT, 42x42x3x3]
%onnx::Conv_962[FLOAT, 86x128x1x1]
%onnx::Conv_963[FLOAT, 86]
%onnx::Conv_965[FLOAT, 86x86x3x3]
%onnx::Conv_968[FLOAT, 85x85x3x3]
%onnx::Conv_969[FLOAT, 85]
%onnx::Conv_971[FLOAT, 85x85x1x1]
%onnx::Conv_974[FLOAT, 85x128x1x1]
%onnx::Conv_977[FLOAT, 85x85x3x3]
%onnx::Conv_980[FLOAT, 86x256x1x1]
%onnx::Conv_983[FLOAT, 86x86x3x3]
%onnx::Conv_986[FLOAT, 85x85x3x3]
%onnx::Conv_989[FLOAT, 85x85x1x1]
%onnx::Conv_992[FLOAT, 85x256x1x1]
%onnx::Conv_995[FLOAT, 85x85x3x3]
%onnx::Conv_998[FLOAT, 86x256x1x1]
%onnx::Conv_1001[FLOAT, 86x86x3x3]
%onnx::Conv_1004[FLOAT, 85x85x3x3]
%onnx::Conv_1007[FLOAT, 85x85x1x1]
%onnx::Conv_1010[FLOAT, 85x256x1x1]
%onnx::Conv_1013[FLOAT, 85x85x3x3]
%onnx::Conv_1016[FLOAT, 171x256x1x1]
%onnx::Conv_1017[FLOAT, 171]
%onnx::Conv_1019[FLOAT, 171x171x3x3]
%onnx::Conv_1022[FLOAT, 171x171x3x3]
%onnx::Conv_1025[FLOAT, 171x171x1x1]
%onnx::Conv_1028[FLOAT, 170x256x1x1]
%onnx::Conv_1029[FLOAT, 170]
%onnx::Conv_1031[FLOAT, 170x170x3x3]
%onnx::Conv_1034[FLOAT, 171x512x1x1]
%onnx::Conv_1037[FLOAT, 171x171x3x3]
%onnx::Conv_1040[FLOAT, 171x171x3x3]
%onnx::Conv_1043[FLOAT, 171x171x1x1]
%onnx::Conv_1046[FLOAT, 170x512x1x1]
%onnx::Conv_1049[FLOAT, 170x170x3x3]
%onnx::Conv_1052[FLOAT, 171x512x1x1]
%onnx::Conv_1055[FLOAT, 171x171x3x3]
%onnx::Conv_1058[FLOAT, 171x171x3x3]
%onnx::Conv_1061[FLOAT, 171x171x1x1]
%onnx::Conv_1064[FLOAT, 170x512x1x1]
%onnx::Conv_1067[FLOAT, 170x170x3x3]
) {
%onnx::Conv_1068 = Identity(%onnx::Conv_1029)
%onnx::Conv_1065 = Identity(%onnx::Conv_1029)
%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_1029)
%onnx::Conv_1047 = Identity(%onnx::Conv_1029)
%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_1029)
%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_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_963)
%onnx::Conv_999 = Identity(%onnx::Conv_963)
%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_963)
%onnx::Conv_981 = Identity(%onnx::Conv_963)
%onnx::Conv_978 = Identity(%onnx::Conv_969)
%onnx::Conv_975 = Identity(%onnx::Conv_969)
%onnx::Conv_972 = Identity(%onnx::Conv_969)
%onnx::Conv_966 = Identity(%onnx::Conv_963)
%onnx::Conv_960 = Identity(%onnx::Conv_921)
%onnx::Conv_957 = Identity(%onnx::Conv_921)
%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_921)
%onnx::Conv_939 = Identity(%onnx::Conv_921)
%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_921)
%onnx::Conv_918 = Identity(%onnx::Conv_909)
%onnx::Conv_915 = Identity(%onnx::Conv_909)
%onnx::Conv_912 = Identity(%onnx::Conv_909)
%/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_905, %onnx::Conv_906)
%/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_908, %onnx::Conv_909)
%/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_911, %onnx::Conv_912)
%/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_914, %onnx::Conv_915)
%/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_917, %onnx::Conv_918)
%/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/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 = <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/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_920, %onnx::Conv_921)
%/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/Slice_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_4_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/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_926, %onnx::Conv_927)
%/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_929, %onnx::Conv_930)
%/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_932, %onnx::Conv_933)
%/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_935, %onnx::Conv_936)
%/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/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 = <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/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_938, %onnx::Conv_939)
%/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/Slice_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_4_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/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_944, %onnx::Conv_945)
%/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_947, %onnx::Conv_948)
%/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_950, %onnx::Conv_951)
%/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_953, %onnx::Conv_954)
%/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/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 = <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/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_956, %onnx::Conv_957)
%/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/Slice_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_4_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/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_962, %onnx::Conv_963)
%/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_965, %onnx::Conv_966)
%/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_968, %onnx::Conv_969)
%/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_971, %onnx::Conv_972)
%/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/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_974, %onnx::Conv_975)
%/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/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_4_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/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_980, %onnx::Conv_981)
%/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_983, %onnx::Conv_984)
%/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_986, %onnx::Conv_987)
%/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_989, %onnx::Conv_990)
%/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/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/Concat_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/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/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_4_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/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_998, %onnx::Conv_999)
%/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_1001, %onnx::Conv_1002)
%/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_1004, %onnx::Conv_1005)
%/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_1007, %onnx::Conv_1008)
%/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/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/Concat_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/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/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_4_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/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_1016, %onnx::Conv_1017)
%/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_1019, %onnx::Conv_1020)
%/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_1022, %onnx::Conv_1023)
%/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_1025, %onnx::Conv_1026)
%/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/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 = <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/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_1028, %onnx::Conv_1029)
%/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/Slice_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_4_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/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_1034, %onnx::Conv_1035)
%/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_1037, %onnx::Conv_1038)
%/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_1040, %onnx::Conv_1041)
%/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_1043, %onnx::Conv_1044)
%/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/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 = <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/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_1046, %onnx::Conv_1047)
%/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/Slice_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_4_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/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_1052, %onnx::Conv_1053)
%/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_1055, %onnx::Conv_1056)
%/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_1058, %onnx::Conv_1059)
%/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_1061, %onnx::Conv_1062)
%/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/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 = <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/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_1064, %onnx::Conv_1065)
%/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/Slice_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_4_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/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)
%903 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %903
}
|
val_accuracy
| 92.107373
| 1,137,600,640
| 3,809,729
|
{'zcp_epe_nas': 130.23449189174855, 'zcp_fisher': 973.0967407226562, 'zcp_flops': 18201610240.0, 'zcp_grad_norm': 597.69677734375, 'zcp_grasp': -9853.31640625, 'zcp_jacov': -16.064497192943243, 'zcp_l2_norm': 883.428955078125, 'zcp_nwot': 218.3342450219096, 'zcp_params': 3809729.0, 'zcp_plain': 0.047523610293865, 'zcp_snip': 2700.74853515625, 'zcp_synflow': 141.13906880611245, 'zcp_zen': 99.80028533935547, 'zcp_val_accuracy': 0.863782048225402}
| |
NASBench101_37976
|
NASBench101
|
37976
|
170b467157d9fd6e67d895ca9f486b69
|
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, 64x64x1x1]
%onnx::Conv_860[FLOAT, 64x128x1x1]
%onnx::Conv_863[FLOAT, 64x64x1x1]
%onnx::Conv_866[FLOAT, 64x64x3x3]
%onnx::Conv_869[FLOAT, 64x64x3x3]
%onnx::Conv_872[FLOAT, 64x128x1x1]
%onnx::Conv_875[FLOAT, 64x64x1x1]
%onnx::Conv_878[FLOAT, 64x128x1x1]
%onnx::Conv_881[FLOAT, 64x64x1x1]
%onnx::Conv_884[FLOAT, 64x64x3x3]
%onnx::Conv_887[FLOAT, 64x64x3x3]
%onnx::Conv_890[FLOAT, 64x128x1x1]
%onnx::Conv_893[FLOAT, 64x64x1x1]
%onnx::Conv_896[FLOAT, 64x128x1x1]
%onnx::Conv_899[FLOAT, 64x64x1x1]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x64x3x3]
%onnx::Conv_908[FLOAT, 128x128x1x1]
%onnx::Conv_911[FLOAT, 128x128x1x1]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 128x128x1x1]
%onnx::Conv_920[FLOAT, 128x128x3x3]
%onnx::Conv_923[FLOAT, 128x128x3x3]
%onnx::Conv_926[FLOAT, 128x256x1x1]
%onnx::Conv_929[FLOAT, 128x128x1x1]
%onnx::Conv_932[FLOAT, 128x256x1x1]
%onnx::Conv_935[FLOAT, 128x128x1x1]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 128x128x3x3]
%onnx::Conv_944[FLOAT, 128x256x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x256x1x1]
%onnx::Conv_953[FLOAT, 128x128x1x1]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x128x3x3]
%onnx::Conv_962[FLOAT, 256x256x1x1]
%onnx::Conv_963[FLOAT, 256]
%onnx::Conv_965[FLOAT, 256x256x1x1]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 256x256x1x1]
%onnx::Conv_974[FLOAT, 256x256x3x3]
%onnx::Conv_977[FLOAT, 256x256x3x3]
%onnx::Conv_980[FLOAT, 256x512x1x1]
%onnx::Conv_983[FLOAT, 256x256x1x1]
%onnx::Conv_986[FLOAT, 256x512x1x1]
%onnx::Conv_989[FLOAT, 256x256x1x1]
%onnx::Conv_992[FLOAT, 256x256x3x3]
%onnx::Conv_995[FLOAT, 256x256x3x3]
%onnx::Conv_998[FLOAT, 256x512x1x1]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 256x512x1x1]
%onnx::Conv_1007[FLOAT, 256x256x1x1]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x256x3x3]
) {
%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_852)
%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_852)
%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_924 = 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_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/input_op.2/conv_bn_relu/conv_bn_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/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_863, %onnx::Conv_864)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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_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/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_6_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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.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_881, %onnx::Conv_882)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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_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/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_6_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_899, %onnx::Conv_900)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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_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/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_6_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_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/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_917, %onnx::Conv_918)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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_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/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_6_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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.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_935, %onnx::Conv_936)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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_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/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_6_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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 = <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/conv3x3/conv_bn_relu/conv_bn_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_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_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/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_6_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_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/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_971, %onnx::Conv_972)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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_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/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_6_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_989, %onnx::Conv_990)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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_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/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_6_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_1007, %onnx::Conv_1008)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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_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/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_6_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/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.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)
%849 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %849
}
|
val_accuracy
| 93.579727
| 1,803,036,672
| 6,054,282
|
{'zcp_epe_nas': 96.03772076630266, 'zcp_fisher': 4.188060283660889, 'zcp_flops': 28848586752.0, 'zcp_grad_norm': 47.286964416503906, 'zcp_grasp': 1.90081787109375, 'zcp_jacov': -16.073457128722637, 'zcp_l2_norm': 994.3119506835938, 'zcp_nwot': 224.32665050196186, 'zcp_params': 6054282.0, 'zcp_plain': 0.005462132394313, 'zcp_snip': 261.6492919921875, 'zcp_synflow': 140.91737566335942, 'zcp_zen': 99.6299057006836, 'zcp_val_accuracy': 0.882512032985687}
| |
NASBench101_340212
|
NASBench101
|
340212
|
cdb7dc815d37032d097f7392c4a98880
|
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, 128x128x1x1]
%onnx::Conv_578[FLOAT, 128x128x3x3]
%onnx::Conv_581[FLOAT, 128x128x1x1]
%onnx::Conv_584[FLOAT, 128x128x1x1]
%onnx::Conv_587[FLOAT, 128x128x3x3]
%onnx::Conv_590[FLOAT, 128x128x1x1]
%onnx::Conv_593[FLOAT, 128x128x1x1]
%onnx::Conv_596[FLOAT, 128x128x3x3]
%onnx::Conv_599[FLOAT, 128x128x1x1]
%onnx::Conv_602[FLOAT, 256x128x1x1]
%onnx::Conv_603[FLOAT, 256]
%onnx::Conv_605[FLOAT, 256x256x3x3]
%onnx::Conv_608[FLOAT, 256x128x1x1]
%onnx::Conv_611[FLOAT, 256x256x1x1]
%onnx::Conv_614[FLOAT, 256x256x3x3]
%onnx::Conv_617[FLOAT, 256x256x1x1]
%onnx::Conv_620[FLOAT, 256x256x1x1]
%onnx::Conv_623[FLOAT, 256x256x3x3]
%onnx::Conv_626[FLOAT, 256x256x1x1]
%onnx::Conv_629[FLOAT, 512x256x1x1]
%onnx::Conv_630[FLOAT, 512]
%onnx::Conv_632[FLOAT, 512x512x3x3]
%onnx::Conv_635[FLOAT, 512x256x1x1]
%onnx::Conv_638[FLOAT, 512x512x1x1]
%onnx::Conv_641[FLOAT, 512x512x3x3]
%onnx::Conv_644[FLOAT, 512x512x1x1]
%onnx::Conv_647[FLOAT, 512x512x1x1]
%onnx::Conv_650[FLOAT, 512x512x3x3]
%onnx::Conv_653[FLOAT, 512x512x1x1]
) {
%onnx::Conv_654 = Identity(%onnx::Conv_630)
%onnx::Conv_651 = Identity(%onnx::Conv_630)
%onnx::Conv_648 = Identity(%onnx::Conv_630)
%onnx::Conv_645 = Identity(%onnx::Conv_630)
%onnx::Conv_642 = Identity(%onnx::Conv_630)
%onnx::Conv_639 = Identity(%onnx::Conv_630)
%onnx::Conv_636 = Identity(%onnx::Conv_630)
%onnx::Conv_633 = Identity(%onnx::Conv_630)
%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_573)
%onnx::Conv_597 = Identity(%onnx::Conv_573)
%onnx::Conv_594 = Identity(%onnx::Conv_573)
%onnx::Conv_591 = Identity(%onnx::Conv_573)
%onnx::Conv_588 = Identity(%onnx::Conv_573)
%onnx::Conv_585 = Identity(%onnx::Conv_573)
%onnx::Conv_582 = Identity(%onnx::Conv_573)
%onnx::Conv_579 = Identity(%onnx::Conv_573)
%onnx::Conv_576 = Identity(%onnx::Conv_573)
%/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/conv3x3/conv_bn_relu/conv_bn_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_578, %onnx::Conv_579)
%/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/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/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/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/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/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_581, %onnx::Conv_582)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_587, %onnx::Conv_588)
%/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/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/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/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/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/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_590, %onnx::Conv_591)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_596, %onnx::Conv_597)
%/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/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/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/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/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/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_599, %onnx::Conv_600)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_605, %onnx::Conv_606)
%/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/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/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/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/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/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_608, %onnx::Conv_609)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_614, %onnx::Conv_615)
%/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/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/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/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/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/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_617, %onnx::Conv_618)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_623, %onnx::Conv_624)
%/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/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/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/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/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/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_626, %onnx::Conv_627)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_632, %onnx::Conv_633)
%/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/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/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/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/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/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_635, %onnx::Conv_636)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_641, %onnx::Conv_642)
%/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/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/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/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/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/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_644, %onnx::Conv_645)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_650, %onnx::Conv_651)
%/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/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/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/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/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/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_653, %onnx::Conv_654)
%/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)
%570 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %570
}
|
val_accuracy
| 89.813703
| 3,279,431,680
| 11,051,402
|
{'zcp_epe_nas': 71.56594873608925, 'zcp_fisher': 287.80517578125, 'zcp_flops': 52470906880.0, 'zcp_grad_norm': 201.84194946289062, 'zcp_grasp': -78.74072265625, 'zcp_jacov': -16.04974405474914, 'zcp_l2_norm': 606.4950561523438, 'zcp_nwot': 224.14871883353877, 'zcp_params': 11051402.0, 'zcp_plain': 0.402300596237182, 'zcp_snip': 1802.8026123046875, 'zcp_synflow': 73.47419078953189, 'zcp_zen': 69.49122619628906, 'zcp_val_accuracy': 0.9203726053237911}
| |
NASBench101_320888
|
NASBench101
|
320888
|
c229e9c38fb3589b9cf062f6c45e4ca0
|
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, 64x64x1x1]
%onnx::Conv_842[FLOAT, 64x64x1x1]
%onnx::Conv_845[FLOAT, 64x128x1x1]
%onnx::Conv_848[FLOAT, 64x64x1x1]
%onnx::Conv_851[FLOAT, 128x128x1x1]
%onnx::Conv_854[FLOAT, 64x128x1x1]
%onnx::Conv_857[FLOAT, 64x64x1x1]
%onnx::Conv_860[FLOAT, 64x64x1x1]
%onnx::Conv_863[FLOAT, 64x128x1x1]
%onnx::Conv_866[FLOAT, 64x64x1x1]
%onnx::Conv_869[FLOAT, 128x128x1x1]
%onnx::Conv_872[FLOAT, 64x128x1x1]
%onnx::Conv_875[FLOAT, 64x64x1x1]
%onnx::Conv_878[FLOAT, 64x64x1x1]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_884[FLOAT, 64x64x1x1]
%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, 128x128x1x1]
%onnx::Conv_905[FLOAT, 256x128x1x1]
%onnx::Conv_906[FLOAT, 256]
%onnx::Conv_908[FLOAT, 128x256x1x1]
%onnx::Conv_911[FLOAT, 128x128x1x1]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 128x256x1x1]
%onnx::Conv_920[FLOAT, 128x128x1x1]
%onnx::Conv_923[FLOAT, 256x256x1x1]
%onnx::Conv_926[FLOAT, 128x256x1x1]
%onnx::Conv_929[FLOAT, 128x128x1x1]
%onnx::Conv_932[FLOAT, 128x128x1x1]
%onnx::Conv_935[FLOAT, 128x256x1x1]
%onnx::Conv_938[FLOAT, 128x128x1x1]
%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, 256x256x1x1]
%onnx::Conv_959[FLOAT, 512x256x1x1]
%onnx::Conv_960[FLOAT, 512]
%onnx::Conv_962[FLOAT, 256x512x1x1]
%onnx::Conv_965[FLOAT, 256x256x1x1]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 256x512x1x1]
%onnx::Conv_974[FLOAT, 256x256x1x1]
%onnx::Conv_977[FLOAT, 512x512x1x1]
%onnx::Conv_980[FLOAT, 256x512x1x1]
%onnx::Conv_983[FLOAT, 256x256x1x1]
%onnx::Conv_986[FLOAT, 256x256x1x1]
%onnx::Conv_989[FLOAT, 256x512x1x1]
%onnx::Conv_992[FLOAT, 256x256x1x1]
%onnx::Conv_995[FLOAT, 512x512x1x1]
) {
%onnx::Conv_996 = Identity(%onnx::Conv_960)
%onnx::Conv_993 = Identity(%onnx::Conv_906)
%onnx::Conv_990 = Identity(%onnx::Conv_906)
%onnx::Conv_987 = Identity(%onnx::Conv_906)
%onnx::Conv_984 = Identity(%onnx::Conv_906)
%onnx::Conv_981 = Identity(%onnx::Conv_906)
%onnx::Conv_978 = Identity(%onnx::Conv_960)
%onnx::Conv_975 = Identity(%onnx::Conv_906)
%onnx::Conv_972 = Identity(%onnx::Conv_906)
%onnx::Conv_969 = Identity(%onnx::Conv_906)
%onnx::Conv_966 = Identity(%onnx::Conv_906)
%onnx::Conv_963 = Identity(%onnx::Conv_906)
%onnx::Conv_957 = Identity(%onnx::Conv_906)
%onnx::Conv_954 = Identity(%onnx::Conv_906)
%onnx::Conv_951 = Identity(%onnx::Conv_906)
%onnx::Conv_948 = Identity(%onnx::Conv_906)
%onnx::Conv_945 = Identity(%onnx::Conv_906)
%onnx::Conv_942 = Identity(%onnx::Conv_906)
%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_906)
%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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/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/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_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/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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_860, %onnx::Conv_861)
%/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_4_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/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/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_866, %onnx::Conv_867)
%/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/conv1x1/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_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/conv1x1/conv_bn_relu/conv_bn_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_878, %onnx::Conv_879)
%/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_4_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/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/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_884, %onnx::Conv_885)
%/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/conv1x1/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_896, %onnx::Conv_897)
%/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_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/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/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_902, %onnx::Conv_903)
%/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/conv1x1/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_914, %onnx::Conv_915)
%/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_4_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/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/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_920, %onnx::Conv_921)
%/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/conv1x1/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_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/conv1x1/conv_bn_relu/conv_bn_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/input_op.3/conv_bn_relu/conv_bn_relu.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_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/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/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_938, %onnx::Conv_939)
%/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/conv1x1/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_950, %onnx::Conv_951)
%/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_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/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/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_956, %onnx::Conv_957)
%/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/conv1x1/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_968, %onnx::Conv_969)
%/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_4_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/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/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_974, %onnx::Conv_975)
%/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/conv1x1/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_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/conv1x1/conv_bn_relu/conv_bn_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_986, %onnx::Conv_987)
%/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_4_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/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/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_992, %onnx::Conv_993)
%/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/conv1x1/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_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
| 90.825319
| 790,767,616
| 2,538,506
|
{'zcp_epe_nas': 100.53813700075898, 'zcp_fisher': 3.262568712234497, 'zcp_flops': 12652281856.0, 'zcp_grad_norm': 48.53803634643555, 'zcp_grasp': -1.704864501953125, 'zcp_jacov': -16.062241878869536, 'zcp_l2_norm': 1040.0335693359375, 'zcp_nwot': 227.26104193968945, 'zcp_params': 2538506.0, 'zcp_plain': 0.044969849288463, 'zcp_snip': 282.9956970214844, 'zcp_synflow': 98.29472272899662, 'zcp_zen': 87.15705108642578, 'zcp_val_accuracy': 0.890625}
| |
NASBench101_167529
|
NASBench101
|
167529
|
6564ec07d2570211fdb6ea3392e6bb3c
|
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, 64x64x3x3]
%onnx::Conv_806[FLOAT, 64x128x1x1]
%onnx::Conv_809[FLOAT, 64x64x3x3]
%onnx::Conv_812[FLOAT, 64x64x1x1]
%onnx::Conv_815[FLOAT, 64x64x1x1]
%onnx::Conv_818[FLOAT, 64x64x3x3]
%onnx::Conv_821[FLOAT, 64x128x1x1]
%onnx::Conv_824[FLOAT, 64x64x3x3]
%onnx::Conv_827[FLOAT, 64x64x1x1]
%onnx::Conv_830[FLOAT, 64x64x1x1]
%onnx::Conv_833[FLOAT, 64x64x3x3]
%onnx::Conv_836[FLOAT, 128x128x1x1]
%onnx::Conv_839[FLOAT, 128x128x3x3]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x3x3]
%onnx::Conv_851[FLOAT, 128x256x1x1]
%onnx::Conv_854[FLOAT, 128x128x3x3]
%onnx::Conv_857[FLOAT, 128x128x1x1]
%onnx::Conv_860[FLOAT, 128x128x1x1]
%onnx::Conv_863[FLOAT, 128x128x3x3]
%onnx::Conv_866[FLOAT, 128x256x1x1]
%onnx::Conv_869[FLOAT, 128x128x3x3]
%onnx::Conv_872[FLOAT, 128x128x1x1]
%onnx::Conv_875[FLOAT, 128x128x1x1]
%onnx::Conv_878[FLOAT, 128x128x3x3]
%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, 256x256x3x3]
%onnx::Conv_896[FLOAT, 256x512x1x1]
%onnx::Conv_899[FLOAT, 256x256x3x3]
%onnx::Conv_902[FLOAT, 256x256x1x1]
%onnx::Conv_905[FLOAT, 256x256x1x1]
%onnx::Conv_908[FLOAT, 256x256x3x3]
%onnx::Conv_911[FLOAT, 256x512x1x1]
%onnx::Conv_914[FLOAT, 256x256x3x3]
%onnx::Conv_917[FLOAT, 256x256x1x1]
%onnx::Conv_920[FLOAT, 256x256x1x1]
%onnx::Conv_923[FLOAT, 256x256x3x3]
) {
%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.1/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/conv3x3/conv_bn_relu/conv_bn_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_803, %onnx::Conv_804)
%/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/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_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.1/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/conv3x3/conv_bn_relu/conv_bn_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_818, %onnx::Conv_819)
%/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/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_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.1/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/conv3x3/conv_bn_relu/conv_bn_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_833, %onnx::Conv_834)
%/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/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_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.1/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/conv3x3/conv_bn_relu/conv_bn_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_848, %onnx::Conv_849)
%/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/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_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.1/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/conv3x3/conv_bn_relu/conv_bn_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_863, %onnx::Conv_864)
%/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/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_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.1/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/conv3x3/conv_bn_relu/conv_bn_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_878, %onnx::Conv_879)
%/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/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_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.1/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/conv3x3/conv_bn_relu/conv_bn_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_893, %onnx::Conv_894)
%/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/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_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.1/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/conv3x3/conv_bn_relu/conv_bn_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_908, %onnx::Conv_909)
%/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/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_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.1/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/conv3x3/conv_bn_relu/conv_bn_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_923, %onnx::Conv_924)
%/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/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)
%786 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %786
}
|
val_accuracy
| 91.516429
| 1,666,066,432
| 5,617,418
|
{'zcp_epe_nas': 72.75413057309304, 'zcp_fisher': 271.9139404296875, 'zcp_flops': 26657062912.0, 'zcp_grad_norm': 278.1956481933594, 'zcp_grasp': -233.5146484375, 'zcp_jacov': -16.0610164892584, 'zcp_l2_norm': 798.3115234375, 'zcp_nwot': 221.6859061480255, 'zcp_params': 5617418.0, 'zcp_plain': 0.046832095831632004, 'zcp_snip': 1545.3623046875, 'zcp_synflow': 146.47103577120663, 'zcp_zen': 87.4628677368164, 'zcp_val_accuracy': 0.797475934028625}
| |
NASBench101_142814
|
NASBench101
|
142814
|
566253a099b02924904b011aef61d04b
|
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, 64x64x3x3]
%onnx::Conv_755[FLOAT, 64x64x3x3]
%onnx::Conv_758[FLOAT, 128x128x1x1]
%onnx::Conv_761[FLOAT, 64x128x1x1]
%onnx::Conv_764[FLOAT, 64x64x1x1]
%onnx::Conv_767[FLOAT, 64x64x3x3]
%onnx::Conv_770[FLOAT, 64x64x3x3]
%onnx::Conv_773[FLOAT, 128x128x1x1]
%onnx::Conv_776[FLOAT, 64x128x1x1]
%onnx::Conv_779[FLOAT, 64x64x1x1]
%onnx::Conv_782[FLOAT, 64x64x3x3]
%onnx::Conv_785[FLOAT, 64x64x3x3]
%onnx::Conv_788[FLOAT, 128x128x1x1]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 128x128x1x1]
%onnx::Conv_797[FLOAT, 128x128x3x3]
%onnx::Conv_800[FLOAT, 128x128x3x3]
%onnx::Conv_803[FLOAT, 256x128x1x1]
%onnx::Conv_804[FLOAT, 256]
%onnx::Conv_806[FLOAT, 128x256x1x1]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x3x3]
%onnx::Conv_815[FLOAT, 128x128x3x3]
%onnx::Conv_818[FLOAT, 256x256x1x1]
%onnx::Conv_821[FLOAT, 128x256x1x1]
%onnx::Conv_824[FLOAT, 128x128x1x1]
%onnx::Conv_827[FLOAT, 128x128x3x3]
%onnx::Conv_830[FLOAT, 128x128x3x3]
%onnx::Conv_833[FLOAT, 256x256x1x1]
%onnx::Conv_836[FLOAT, 256x256x1x1]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x256x3x3]
%onnx::Conv_845[FLOAT, 256x256x3x3]
%onnx::Conv_848[FLOAT, 512x256x1x1]
%onnx::Conv_849[FLOAT, 512]
%onnx::Conv_851[FLOAT, 256x512x1x1]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_857[FLOAT, 256x256x3x3]
%onnx::Conv_860[FLOAT, 256x256x3x3]
%onnx::Conv_863[FLOAT, 512x512x1x1]
%onnx::Conv_866[FLOAT, 256x512x1x1]
%onnx::Conv_869[FLOAT, 256x256x1x1]
%onnx::Conv_872[FLOAT, 256x256x3x3]
%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/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.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_749, %onnx::Conv_750)
%/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/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_752, %onnx::Conv_753)
%/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_2_output_0 = Add(%/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.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_2_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/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/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.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_758, %onnx::Conv_759)
%/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_3_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_3_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/conv1x1/conv_bn_relu/conv_bn_relu.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_764, %onnx::Conv_765)
%/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/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_767, %onnx::Conv_768)
%/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_2_output_0 = Add(%/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.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_2_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/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/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.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_3_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/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_3_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_3_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/conv1x1/conv_bn_relu/conv_bn_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_779, %onnx::Conv_780)
%/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/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_782, %onnx::Conv_783)
%/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_2_output_0 = Add(%/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.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_2_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/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/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.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_3_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/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_3_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_3_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/conv1x1/conv_bn_relu/conv_bn_relu.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_794, %onnx::Conv_795)
%/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_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/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_797, %onnx::Conv_798)
%/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_2_output_0 = Add(%/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.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_2_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/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/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.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_803, %onnx::Conv_804)
%/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_3_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_3_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/conv1x1/conv_bn_relu/conv_bn_relu.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_809, %onnx::Conv_810)
%/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_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/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_812, %onnx::Conv_813)
%/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_2_output_0 = Add(%/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.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_2_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/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/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.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_3_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/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_3_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_3_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/conv1x1/conv_bn_relu/conv_bn_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_824, %onnx::Conv_825)
%/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_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/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_827, %onnx::Conv_828)
%/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_2_output_0 = Add(%/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.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_2_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/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/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.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_3_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/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_3_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_3_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/conv1x1/conv_bn_relu/conv_bn_relu.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_839, %onnx::Conv_840)
%/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/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_842, %onnx::Conv_843)
%/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_2_output_0 = Add(%/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.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_2_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/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/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.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_848, %onnx::Conv_849)
%/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_3_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_3_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/conv1x1/conv_bn_relu/conv_bn_relu.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_854, %onnx::Conv_855)
%/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/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_857, %onnx::Conv_858)
%/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_2_output_0 = Add(%/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.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_2_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/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/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.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_3_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/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_3_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_3_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/conv1x1/conv_bn_relu/conv_bn_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_869, %onnx::Conv_870)
%/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/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_872, %onnx::Conv_873)
%/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_2_output_0 = Add(%/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)
%/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_2_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/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/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)
%/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_3_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/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_3_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_3_output_0)
%741 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %741
}
|
val_accuracy
| 92.668271
| 1,861,756,928
| 6,230,410
|
{'zcp_epe_nas': 112.08070542289681, 'zcp_fisher': 17.21065330505371, 'zcp_flops': 29788110848.0, 'zcp_grad_norm': 84.6889877319336, 'zcp_grasp': -1.40350341796875, 'zcp_jacov': -16.05494111670965, 'zcp_l2_norm': 844.630615234375, 'zcp_nwot': 224.14943363892445, 'zcp_params': 6230410.0, 'zcp_plain': -0.004783042240887, 'zcp_snip': 553.02978515625, 'zcp_synflow': 117.48112599050089, 'zcp_zen': 94.83171081542969, 'zcp_val_accuracy': 0.918469548225402}
| |
NASBench101_375647
|
NASBench101
|
375647
|
e315301edbfc81eae012d04886ca1e21
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_698[FLOAT, 128x3x3x3]
%onnx::Conv_699[FLOAT, 128]
%onnx::Conv_701[FLOAT, 43x128x1x1]
%onnx::Conv_702[FLOAT, 43]
%onnx::Conv_704[FLOAT, 43x43x1x1]
%onnx::Conv_707[FLOAT, 43x128x1x1]
%onnx::Conv_710[FLOAT, 43x43x1x1]
%onnx::Conv_713[FLOAT, 43x128x1x1]
%onnx::Conv_716[FLOAT, 43x43x1x1]
%onnx::Conv_719[FLOAT, 43x128x1x1]
%onnx::Conv_722[FLOAT, 43x43x1x1]
%onnx::Conv_725[FLOAT, 43x128x1x1]
%onnx::Conv_728[FLOAT, 43x43x1x1]
%onnx::Conv_731[FLOAT, 43x128x1x1]
%onnx::Conv_734[FLOAT, 43x43x1x1]
%onnx::Conv_737[FLOAT, 86x128x1x1]
%onnx::Conv_738[FLOAT, 86]
%onnx::Conv_740[FLOAT, 86x86x1x1]
%onnx::Conv_743[FLOAT, 85x128x1x1]
%onnx::Conv_744[FLOAT, 85]
%onnx::Conv_746[FLOAT, 85x85x1x1]
%onnx::Conv_749[FLOAT, 86x256x1x1]
%onnx::Conv_752[FLOAT, 86x86x1x1]
%onnx::Conv_755[FLOAT, 85x256x1x1]
%onnx::Conv_758[FLOAT, 85x85x1x1]
%onnx::Conv_761[FLOAT, 86x256x1x1]
%onnx::Conv_764[FLOAT, 86x86x1x1]
%onnx::Conv_767[FLOAT, 85x256x1x1]
%onnx::Conv_770[FLOAT, 85x85x1x1]
%onnx::Conv_773[FLOAT, 171x256x1x1]
%onnx::Conv_774[FLOAT, 171]
%onnx::Conv_776[FLOAT, 171x171x1x1]
%onnx::Conv_779[FLOAT, 171x256x1x1]
%onnx::Conv_782[FLOAT, 171x171x1x1]
%onnx::Conv_785[FLOAT, 171x512x1x1]
%onnx::Conv_788[FLOAT, 171x171x1x1]
%onnx::Conv_791[FLOAT, 171x512x1x1]
%onnx::Conv_794[FLOAT, 171x171x1x1]
%onnx::Conv_797[FLOAT, 171x512x1x1]
%onnx::Conv_800[FLOAT, 171x171x1x1]
%onnx::Conv_803[FLOAT, 171x512x1x1]
%onnx::Conv_806[FLOAT, 171x171x1x1]
) {
%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)
%onnx::Conv_771 = Identity(%onnx::Conv_744)
%onnx::Conv_768 = Identity(%onnx::Conv_744)
%onnx::Conv_765 = Identity(%onnx::Conv_738)
%onnx::Conv_762 = Identity(%onnx::Conv_738)
%onnx::Conv_759 = Identity(%onnx::Conv_744)
%onnx::Conv_756 = Identity(%onnx::Conv_744)
%onnx::Conv_753 = Identity(%onnx::Conv_738)
%onnx::Conv_750 = Identity(%onnx::Conv_738)
%onnx::Conv_747 = Identity(%onnx::Conv_744)
%onnx::Conv_741 = Identity(%onnx::Conv_738)
%onnx::Conv_735 = Identity(%onnx::Conv_702)
%onnx::Conv_732 = Identity(%onnx::Conv_702)
%onnx::Conv_729 = Identity(%onnx::Conv_702)
%onnx::Conv_726 = Identity(%onnx::Conv_702)
%onnx::Conv_723 = Identity(%onnx::Conv_702)
%onnx::Conv_720 = Identity(%onnx::Conv_702)
%onnx::Conv_717 = Identity(%onnx::Conv_702)
%onnx::Conv_714 = Identity(%onnx::Conv_702)
%onnx::Conv_711 = Identity(%onnx::Conv_702)
%onnx::Conv_708 = Identity(%onnx::Conv_702)
%onnx::Conv_705 = Identity(%onnx::Conv_702)
%/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_698, %onnx::Conv_699)
%/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_701, %onnx::Conv_702)
%/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_704, %onnx::Conv_705)
%/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_707, %onnx::Conv_708)
%/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/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_710, %onnx::Conv_711)
%/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_4_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_4_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/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_713, %onnx::Conv_714)
%/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_716, %onnx::Conv_717)
%/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_719, %onnx::Conv_720)
%/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/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_722, %onnx::Conv_723)
%/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_4_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_4_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/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_725, %onnx::Conv_726)
%/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_728, %onnx::Conv_729)
%/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_731, %onnx::Conv_732)
%/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/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_734, %onnx::Conv_735)
%/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_4_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_4_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/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_737, %onnx::Conv_738)
%/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_740, %onnx::Conv_741)
%/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_743, %onnx::Conv_744)
%/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 = <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/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/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_746, %onnx::Conv_747)
%/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/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/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/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_749, %onnx::Conv_750)
%/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_752, %onnx::Conv_753)
%/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_755, %onnx::Conv_756)
%/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 = <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/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/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_758, %onnx::Conv_759)
%/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/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/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/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_761, %onnx::Conv_762)
%/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_764, %onnx::Conv_765)
%/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_767, %onnx::Conv_768)
%/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 = <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/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/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_770, %onnx::Conv_771)
%/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/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/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/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_773, %onnx::Conv_774)
%/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_776, %onnx::Conv_777)
%/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_779, %onnx::Conv_780)
%/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/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_782, %onnx::Conv_783)
%/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_4_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_4_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/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_785, %onnx::Conv_786)
%/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_788, %onnx::Conv_789)
%/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_791, %onnx::Conv_792)
%/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/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_794, %onnx::Conv_795)
%/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_4_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_4_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/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_797, %onnx::Conv_798)
%/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_800, %onnx::Conv_801)
%/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_803, %onnx::Conv_804)
%/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/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_806, %onnx::Conv_807)
%/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_4_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_4_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/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%696 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %696
}
|
val_accuracy
| 89.483172
| 262,850,816
| 826,657
|
{'zcp_epe_nas': 79.04759433971668, 'zcp_fisher': 6.904917240142822, 'zcp_flops': 4205613056.0, 'zcp_grad_norm': 53.06684112548828, 'zcp_grasp': -4.380859375, 'zcp_jacov': -16.056685864252334, 'zcp_l2_norm': 640.4620971679688, 'zcp_nwot': 212.86796583308853, 'zcp_params': 826657.0, 'zcp_plain': 0.006478746421635001, 'zcp_snip': 249.16510009765625, 'zcp_synflow': 76.32813795409452, 'zcp_zen': 54.41768264770508, 'zcp_val_accuracy': 0.09505208581686}
| |
NASBench101_171154
|
NASBench101
|
171154
|
67a6221413ab9fbd4264b32ca092b233
|
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, 64x64x3x3]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x64x1x1]
%onnx::Conv_905[FLOAT, 64x64x1x1]
%onnx::Conv_908[FLOAT, 64x128x1x1]
%onnx::Conv_911[FLOAT, 64x64x1x1]
%onnx::Conv_914[FLOAT, 64x64x3x3]
%onnx::Conv_917[FLOAT, 64x128x1x1]
%onnx::Conv_920[FLOAT, 64x64x1x1]
%onnx::Conv_923[FLOAT, 64x64x1x1]
%onnx::Conv_926[FLOAT, 64x128x1x1]
%onnx::Conv_929[FLOAT, 64x64x1x1]
%onnx::Conv_932[FLOAT, 64x64x3x3]
%onnx::Conv_935[FLOAT, 64x128x1x1]
%onnx::Conv_938[FLOAT, 64x64x1x1]
%onnx::Conv_941[FLOAT, 64x64x1x1]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x128x3x3]
%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, 128x128x3x3]
%onnx::Conv_971[FLOAT, 128x256x1x1]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 128x256x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x128x3x3]
%onnx::Conv_989[FLOAT, 128x256x1x1]
%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, 256x256x3x3]
%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, 256x256x3x3]
%onnx::Conv_1025[FLOAT, 256x512x1x1]
%onnx::Conv_1028[FLOAT, 256x256x1x1]
%onnx::Conv_1031[FLOAT, 256x256x1x1]
%onnx::Conv_1034[FLOAT, 256x512x1x1]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 256x256x3x3]
%onnx::Conv_1043[FLOAT, 256x512x1x1]
%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/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_896, %onnx::Conv_897)
%/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_899, %onnx::Conv_900)
%/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/input_op.4/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_3_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_4_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_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.2/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/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_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/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_914, %onnx::Conv_915)
%/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_917, %onnx::Conv_918)
%/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/input_op.4/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_3_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_4_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_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.2/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/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_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/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_932, %onnx::Conv_933)
%/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_935, %onnx::Conv_936)
%/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/input_op.4/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_3_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_4_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_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.2/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/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_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/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_950, %onnx::Conv_951)
%/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_953, %onnx::Conv_954)
%/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/input_op.4/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_3_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_4_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_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.2/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/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_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/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_968, %onnx::Conv_969)
%/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_971, %onnx::Conv_972)
%/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/input_op.4/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_3_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_4_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_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.2/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/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_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/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_986, %onnx::Conv_987)
%/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_989, %onnx::Conv_990)
%/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/input_op.4/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_3_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_4_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_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.2/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/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_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/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_1004, %onnx::Conv_1005)
%/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_1007, %onnx::Conv_1008)
%/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/input_op.4/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_3_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_4_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_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.2/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/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_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/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_1022, %onnx::Conv_1023)
%/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_1025, %onnx::Conv_1026)
%/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/input_op.4/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_3_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_4_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_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.2/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/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_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/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_1040, %onnx::Conv_1041)
%/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_1043, %onnx::Conv_1044)
%/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/input_op.4/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_3_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_4_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_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.2/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/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_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
| 91.195911
| 1,199,056,896
| 3,989,898
|
{'zcp_epe_nas': 174.4453895159412, 'zcp_fisher': 121.83509063720703, 'zcp_flops': 19184910336.0, 'zcp_grad_norm': 217.85052490234375, 'zcp_grasp': 60.0478515625, 'zcp_jacov': -16.055924240756408, 'zcp_l2_norm': 993.9157104492188, 'zcp_nwot': 224.58444701880518, 'zcp_params': 3989898.0, 'zcp_plain': 0.011571493931114, 'zcp_snip': 1162.5845947265625, 'zcp_synflow': 108.11282882764921, 'zcp_zen': 88.90792083740234, 'zcp_val_accuracy': 0.8842147588729851}
| |
NASBench101_294883
|
NASBench101
|
294883
|
b28707bd26e52ffff2fc51f48061c828
|
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, 64x128x1x1]
%onnx::Conv_648[FLOAT, 64]
%onnx::Conv_650[FLOAT, 64x64x1x1]
%onnx::Conv_653[FLOAT, 64x64x1x1]
%onnx::Conv_656[FLOAT, 64x64x3x3]
%onnx::Conv_659[FLOAT, 64x128x1x1]
%onnx::Conv_662[FLOAT, 64x64x1x1]
%onnx::Conv_665[FLOAT, 64x64x1x1]
%onnx::Conv_668[FLOAT, 64x64x3x3]
%onnx::Conv_671[FLOAT, 64x128x1x1]
%onnx::Conv_674[FLOAT, 64x64x1x1]
%onnx::Conv_677[FLOAT, 64x64x1x1]
%onnx::Conv_680[FLOAT, 64x64x3x3]
%onnx::Conv_683[FLOAT, 128x128x1x1]
%onnx::Conv_686[FLOAT, 128x128x1x1]
%onnx::Conv_689[FLOAT, 128x128x1x1]
%onnx::Conv_692[FLOAT, 128x128x3x3]
%onnx::Conv_695[FLOAT, 128x256x1x1]
%onnx::Conv_698[FLOAT, 128x128x1x1]
%onnx::Conv_701[FLOAT, 128x128x1x1]
%onnx::Conv_704[FLOAT, 128x128x3x3]
%onnx::Conv_707[FLOAT, 128x256x1x1]
%onnx::Conv_710[FLOAT, 128x128x1x1]
%onnx::Conv_713[FLOAT, 128x128x1x1]
%onnx::Conv_716[FLOAT, 128x128x3x3]
%onnx::Conv_719[FLOAT, 256x256x1x1]
%onnx::Conv_720[FLOAT, 256]
%onnx::Conv_722[FLOAT, 256x256x1x1]
%onnx::Conv_725[FLOAT, 256x256x1x1]
%onnx::Conv_728[FLOAT, 256x256x3x3]
%onnx::Conv_731[FLOAT, 256x512x1x1]
%onnx::Conv_734[FLOAT, 256x256x1x1]
%onnx::Conv_737[FLOAT, 256x256x1x1]
%onnx::Conv_740[FLOAT, 256x256x3x3]
%onnx::Conv_743[FLOAT, 256x512x1x1]
%onnx::Conv_746[FLOAT, 256x256x1x1]
%onnx::Conv_749[FLOAT, 256x256x1x1]
%onnx::Conv_752[FLOAT, 256x256x3x3]
) {
%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_645)
%onnx::Conv_714 = Identity(%onnx::Conv_645)
%onnx::Conv_711 = Identity(%onnx::Conv_645)
%onnx::Conv_708 = Identity(%onnx::Conv_645)
%onnx::Conv_705 = Identity(%onnx::Conv_645)
%onnx::Conv_702 = Identity(%onnx::Conv_645)
%onnx::Conv_699 = Identity(%onnx::Conv_645)
%onnx::Conv_696 = Identity(%onnx::Conv_645)
%onnx::Conv_693 = Identity(%onnx::Conv_645)
%onnx::Conv_690 = Identity(%onnx::Conv_645)
%onnx::Conv_687 = Identity(%onnx::Conv_645)
%onnx::Conv_684 = Identity(%onnx::Conv_645)
%onnx::Conv_681 = Identity(%onnx::Conv_648)
%onnx::Conv_678 = Identity(%onnx::Conv_648)
%onnx::Conv_675 = Identity(%onnx::Conv_648)
%onnx::Conv_672 = Identity(%onnx::Conv_648)
%onnx::Conv_669 = Identity(%onnx::Conv_648)
%onnx::Conv_666 = Identity(%onnx::Conv_648)
%onnx::Conv_663 = Identity(%onnx::Conv_648)
%onnx::Conv_660 = Identity(%onnx::Conv_648)
%onnx::Conv_657 = Identity(%onnx::Conv_648)
%onnx::Conv_654 = Identity(%onnx::Conv_648)
%onnx::Conv_651 = Identity(%onnx::Conv_648)
%/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/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.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_650, %onnx::Conv_651)
%/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_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/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_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/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.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_656, %onnx::Conv_657)
%/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_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/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.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_662, %onnx::Conv_663)
%/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_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/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_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/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.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_668, %onnx::Conv_669)
%/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_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/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_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_674, %onnx::Conv_675)
%/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_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/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_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/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.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_680, %onnx::Conv_681)
%/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_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/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.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_686, %onnx::Conv_687)
%/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_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/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_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/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.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_692, %onnx::Conv_693)
%/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_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/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.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_698, %onnx::Conv_699)
%/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_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/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_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/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.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_704, %onnx::Conv_705)
%/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_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/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_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_710, %onnx::Conv_711)
%/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_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/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_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/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.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_716, %onnx::Conv_717)
%/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_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/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.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_722, %onnx::Conv_723)
%/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_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/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_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/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.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_728, %onnx::Conv_729)
%/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_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/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.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_734, %onnx::Conv_735)
%/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_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/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_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/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.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_740, %onnx::Conv_741)
%/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_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/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_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_746, %onnx::Conv_747)
%/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_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/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_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/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.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_752, %onnx::Conv_753)
%/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)
%642 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %642
}
|
val_accuracy
| 90.054089
| 983,836,672
| 3,292,298
|
{'zcp_epe_nas': 114.90068434427118, 'zcp_fisher': 3.9120147228240962, 'zcp_flops': 15741386752.0, 'zcp_grad_norm': 32.7361946105957, 'zcp_grasp': -3.133888244628906, 'zcp_jacov': -16.048949135531572, 'zcp_l2_norm': 648.0806274414062, 'zcp_nwot': 217.97010363418332, 'zcp_params': 3292298.0, 'zcp_plain': 0.11735127121210001, 'zcp_snip': 210.69610595703125, 'zcp_synflow': 107.3537713686072, 'zcp_zen': 69.89779663085938, 'zcp_val_accuracy': 0.87109375}
| |
NASBench101_251385
|
NASBench101
|
251385
|
983661b0010f9264853abef19a3edc64
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_836[FLOAT, 128x3x3x3]
%onnx::Conv_837[FLOAT, 128]
%onnx::Conv_839[FLOAT, 43x128x1x1]
%onnx::Conv_840[FLOAT, 43]
%onnx::Conv_842[FLOAT, 43x43x3x3]
%onnx::Conv_845[FLOAT, 43x43x1x1]
%onnx::Conv_848[FLOAT, 42x42x1x1]
%onnx::Conv_849[FLOAT, 42]
%onnx::Conv_851[FLOAT, 42x42x3x3]
%onnx::Conv_854[FLOAT, 43x128x1x1]
%onnx::Conv_857[FLOAT, 43x43x3x3]
%onnx::Conv_860[FLOAT, 43x43x1x1]
%onnx::Conv_863[FLOAT, 42x42x1x1]
%onnx::Conv_866[FLOAT, 42x42x3x3]
%onnx::Conv_869[FLOAT, 43x128x1x1]
%onnx::Conv_872[FLOAT, 43x43x3x3]
%onnx::Conv_875[FLOAT, 43x43x1x1]
%onnx::Conv_878[FLOAT, 42x42x1x1]
%onnx::Conv_881[FLOAT, 42x42x3x3]
%onnx::Conv_884[FLOAT, 86x128x1x1]
%onnx::Conv_885[FLOAT, 86]
%onnx::Conv_887[FLOAT, 86x86x3x3]
%onnx::Conv_890[FLOAT, 85x85x1x1]
%onnx::Conv_891[FLOAT, 85]
%onnx::Conv_893[FLOAT, 85x85x1x1]
%onnx::Conv_896[FLOAT, 85x85x3x3]
%onnx::Conv_899[FLOAT, 86x256x1x1]
%onnx::Conv_902[FLOAT, 86x86x3x3]
%onnx::Conv_905[FLOAT, 85x85x1x1]
%onnx::Conv_908[FLOAT, 85x85x1x1]
%onnx::Conv_911[FLOAT, 85x85x3x3]
%onnx::Conv_914[FLOAT, 86x256x1x1]
%onnx::Conv_917[FLOAT, 86x86x3x3]
%onnx::Conv_920[FLOAT, 85x85x1x1]
%onnx::Conv_923[FLOAT, 85x85x1x1]
%onnx::Conv_926[FLOAT, 85x85x3x3]
%onnx::Conv_929[FLOAT, 171x256x1x1]
%onnx::Conv_930[FLOAT, 171]
%onnx::Conv_932[FLOAT, 171x171x3x3]
%onnx::Conv_935[FLOAT, 171x171x1x1]
%onnx::Conv_938[FLOAT, 170x170x1x1]
%onnx::Conv_939[FLOAT, 170]
%onnx::Conv_941[FLOAT, 170x170x3x3]
%onnx::Conv_944[FLOAT, 171x512x1x1]
%onnx::Conv_947[FLOAT, 171x171x3x3]
%onnx::Conv_950[FLOAT, 171x171x1x1]
%onnx::Conv_953[FLOAT, 170x170x1x1]
%onnx::Conv_956[FLOAT, 170x170x3x3]
%onnx::Conv_959[FLOAT, 171x512x1x1]
%onnx::Conv_962[FLOAT, 171x171x3x3]
%onnx::Conv_965[FLOAT, 171x171x1x1]
%onnx::Conv_968[FLOAT, 170x170x1x1]
%onnx::Conv_971[FLOAT, 170x170x3x3]
) {
%onnx::Conv_972 = Identity(%onnx::Conv_939)
%onnx::Conv_969 = Identity(%onnx::Conv_939)
%onnx::Conv_966 = Identity(%onnx::Conv_930)
%onnx::Conv_963 = Identity(%onnx::Conv_930)
%onnx::Conv_960 = Identity(%onnx::Conv_930)
%onnx::Conv_957 = Identity(%onnx::Conv_939)
%onnx::Conv_954 = Identity(%onnx::Conv_939)
%onnx::Conv_951 = Identity(%onnx::Conv_930)
%onnx::Conv_948 = Identity(%onnx::Conv_930)
%onnx::Conv_945 = Identity(%onnx::Conv_930)
%onnx::Conv_942 = Identity(%onnx::Conv_939)
%onnx::Conv_936 = Identity(%onnx::Conv_930)
%onnx::Conv_933 = Identity(%onnx::Conv_930)
%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_885)
%onnx::Conv_915 = Identity(%onnx::Conv_885)
%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_885)
%onnx::Conv_900 = Identity(%onnx::Conv_885)
%onnx::Conv_897 = Identity(%onnx::Conv_891)
%onnx::Conv_894 = Identity(%onnx::Conv_891)
%onnx::Conv_888 = Identity(%onnx::Conv_885)
%onnx::Conv_882 = Identity(%onnx::Conv_849)
%onnx::Conv_879 = Identity(%onnx::Conv_849)
%onnx::Conv_876 = Identity(%onnx::Conv_840)
%onnx::Conv_873 = Identity(%onnx::Conv_840)
%onnx::Conv_870 = Identity(%onnx::Conv_840)
%onnx::Conv_867 = Identity(%onnx::Conv_849)
%onnx::Conv_864 = Identity(%onnx::Conv_849)
%onnx::Conv_861 = Identity(%onnx::Conv_840)
%onnx::Conv_858 = Identity(%onnx::Conv_840)
%onnx::Conv_855 = Identity(%onnx::Conv_840)
%onnx::Conv_852 = Identity(%onnx::Conv_849)
%onnx::Conv_846 = Identity(%onnx::Conv_840)
%onnx::Conv_843 = Identity(%onnx::Conv_840)
%/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_836, %onnx::Conv_837)
%/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_839, %onnx::Conv_840)
%/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_842, %onnx::Conv_843)
%/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_845, %onnx::Conv_846)
%/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.3/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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_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/conv1x1/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/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_851, %onnx::Conv_852)
%/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.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_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/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_860, %onnx::Conv_861)
%/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.3/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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_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/conv1x1/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/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_866, %onnx::Conv_867)
%/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.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_869, %onnx::Conv_870)
%/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_872, %onnx::Conv_873)
%/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_875, %onnx::Conv_876)
%/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.3/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_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_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_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/conv1x1/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/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_881, %onnx::Conv_882)
%/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.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_884, %onnx::Conv_885)
%/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_887, %onnx::Conv_888)
%/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/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.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_890, %onnx::Conv_891)
%/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_2_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_6_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_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_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/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_896, %onnx::Conv_897)
%/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.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_899, %onnx::Conv_900)
%/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_902, %onnx::Conv_903)
%/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/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.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_905, %onnx::Conv_906)
%/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_2_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_6_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_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_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/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_911, %onnx::Conv_912)
%/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.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_914, %onnx::Conv_915)
%/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_917, %onnx::Conv_918)
%/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/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_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_920, %onnx::Conv_921)
%/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_2_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_6_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_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_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/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_926, %onnx::Conv_927)
%/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.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_929, %onnx::Conv_930)
%/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_932, %onnx::Conv_933)
%/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_935, %onnx::Conv_936)
%/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.3/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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_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/conv1x1/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/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_941, %onnx::Conv_942)
%/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.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_944, %onnx::Conv_945)
%/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_947, %onnx::Conv_948)
%/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_950, %onnx::Conv_951)
%/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.3/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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_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/conv1x1/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/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_956, %onnx::Conv_957)
%/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.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_959, %onnx::Conv_960)
%/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_962, %onnx::Conv_963)
%/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_965, %onnx::Conv_966)
%/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.3/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_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_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_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/conv1x1/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/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_971, %onnx::Conv_972)
%/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.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)
%834 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %834
}
|
val_accuracy
| 91.105771
| 776,878,848
| 2,598,969
|
{'zcp_epe_nas': 99.33198768180998, 'zcp_fisher': 240.39427185058594, 'zcp_flops': 12430061568.0, 'zcp_grad_norm': 261.4103698730469, 'zcp_grasp': -289.5888671875, 'zcp_jacov': -16.044199424811293, 'zcp_l2_norm': 687.749755859375, 'zcp_nwot': 215.85925865725693, 'zcp_params': 2598969.0, 'zcp_plain': 0.012890567071735, 'zcp_snip': 1170.6424560546875, 'zcp_synflow': 131.83370876411303, 'zcp_zen': 77.05843353271484, 'zcp_val_accuracy': 0.9300881624221801}
| |
NASBench101_418114
|
NASBench101
|
418114
|
fcac203fe19954c8053bde4643feac28
|
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, 64x128x1x1]
%onnx::Conv_794[FLOAT, 64x64x3x3]
%onnx::Conv_797[FLOAT, 64x128x1x1]
%onnx::Conv_800[FLOAT, 64x64x1x1]
%onnx::Conv_803[FLOAT, 64x64x1x1]
%onnx::Conv_806[FLOAT, 64x128x1x1]
%onnx::Conv_809[FLOAT, 64x64x3x3]
%onnx::Conv_812[FLOAT, 64x128x1x1]
%onnx::Conv_815[FLOAT, 64x64x1x1]
%onnx::Conv_818[FLOAT, 64x64x1x1]
%onnx::Conv_821[FLOAT, 64x128x1x1]
%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, 128x256x1x1]
%onnx::Conv_854[FLOAT, 128x128x3x3]
%onnx::Conv_857[FLOAT, 128x256x1x1]
%onnx::Conv_860[FLOAT, 128x128x1x1]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%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, 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, 256x512x1x1]
%onnx::Conv_899[FLOAT, 256x256x3x3]
%onnx::Conv_902[FLOAT, 256x512x1x1]
%onnx::Conv_905[FLOAT, 256x256x1x1]
%onnx::Conv_908[FLOAT, 256x256x1x1]
%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/conv1x1/conv_bn_relu/conv_bn_relu.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.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/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_3_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_791, %onnx::Conv_792)
%/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/input_op.4/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/Add_5_output_0 = Add(%/layers.1/vertex_op.3/maxpool/MaxPool_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_794, %onnx::Conv_795)
%/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.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_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.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/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_3_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_806, %onnx::Conv_807)
%/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/input_op.4/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/Add_5_output_0 = Add(%/layers.2/vertex_op.3/maxpool/MaxPool_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_809, %onnx::Conv_810)
%/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.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_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.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/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_3_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_821, %onnx::Conv_822)
%/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/input_op.4/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/Add_5_output_0 = Add(%/layers.3/vertex_op.3/maxpool/MaxPool_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_824, %onnx::Conv_825)
%/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.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_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.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/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_3_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_836, %onnx::Conv_837)
%/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/input_op.4/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/Add_5_output_0 = Add(%/layers.5/vertex_op.3/maxpool/MaxPool_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_839, %onnx::Conv_840)
%/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.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_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.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/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_3_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_851, %onnx::Conv_852)
%/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/input_op.4/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/Add_5_output_0 = Add(%/layers.6/vertex_op.3/maxpool/MaxPool_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_854, %onnx::Conv_855)
%/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.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_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.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/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_3_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_866, %onnx::Conv_867)
%/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/input_op.4/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/Add_5_output_0 = Add(%/layers.7/vertex_op.3/maxpool/MaxPool_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_869, %onnx::Conv_870)
%/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.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_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.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/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_3_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_881, %onnx::Conv_882)
%/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/input_op.4/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/Add_5_output_0 = Add(%/layers.9/vertex_op.3/maxpool/MaxPool_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_884, %onnx::Conv_885)
%/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.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_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.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/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_3_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_896, %onnx::Conv_897)
%/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/input_op.4/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/Add_5_output_0 = Add(%/layers.10/vertex_op.3/maxpool/MaxPool_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_899, %onnx::Conv_900)
%/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.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_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.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/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_3_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_911, %onnx::Conv_912)
%/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/input_op.4/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/Add_5_output_0 = Add(%/layers.11/vertex_op.3/maxpool/MaxPool_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_914, %onnx::Conv_915)
%/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.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)
%777 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %777
}
|
val_accuracy
| 92.477965
| 1,120,806,912
| 3,729,162
|
{'zcp_epe_nas': 125.13348858253893, 'zcp_fisher': 10.347593307495117, 'zcp_flops': 17932910592.0, 'zcp_grad_norm': 62.61726760864258, 'zcp_grasp': 2.6639404296875, 'zcp_jacov': -16.04940216479155, 'zcp_l2_norm': 843.7510375976562, 'zcp_nwot': 221.28047032005347, 'zcp_params': 3729162.0, 'zcp_plain': 0.045525632798671, 'zcp_snip': 336.20184326171875, 'zcp_synflow': 108.13585546806995, 'zcp_zen': 79.78152465820312, 'zcp_val_accuracy': 0.932391822338104}
| |
NASBench101_322881
|
NASBench101
|
322881
|
c3585f700c6edce8f9c8e05cd921cfde
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_824[FLOAT, 128x3x3x3]
%onnx::Conv_825[FLOAT, 128]
%onnx::Conv_827[FLOAT, 64x128x1x1]
%onnx::Conv_828[FLOAT, 64]
%onnx::Conv_830[FLOAT, 64x64x1x1]
%onnx::Conv_833[FLOAT, 64x128x1x1]
%onnx::Conv_836[FLOAT, 64x128x1x1]
%onnx::Conv_839[FLOAT, 64x64x3x3]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 64x128x1x1]
%onnx::Conv_848[FLOAT, 64x64x1x1]
%onnx::Conv_851[FLOAT, 64x128x1x1]
%onnx::Conv_854[FLOAT, 64x128x1x1]
%onnx::Conv_857[FLOAT, 64x64x3x3]
%onnx::Conv_860[FLOAT, 128x128x1x1]
%onnx::Conv_863[FLOAT, 64x128x1x1]
%onnx::Conv_866[FLOAT, 64x64x1x1]
%onnx::Conv_869[FLOAT, 64x128x1x1]
%onnx::Conv_872[FLOAT, 64x128x1x1]
%onnx::Conv_875[FLOAT, 64x64x3x3]
%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, 256x128x1x1]
%onnx::Conv_897[FLOAT, 256]
%onnx::Conv_899[FLOAT, 128x256x1x1]
%onnx::Conv_902[FLOAT, 128x128x1x1]
%onnx::Conv_905[FLOAT, 128x256x1x1]
%onnx::Conv_908[FLOAT, 128x256x1x1]
%onnx::Conv_911[FLOAT, 128x128x3x3]
%onnx::Conv_914[FLOAT, 256x256x1x1]
%onnx::Conv_917[FLOAT, 128x256x1x1]
%onnx::Conv_920[FLOAT, 128x128x1x1]
%onnx::Conv_923[FLOAT, 128x256x1x1]
%onnx::Conv_926[FLOAT, 128x256x1x1]
%onnx::Conv_929[FLOAT, 128x128x3x3]
%onnx::Conv_932[FLOAT, 256x256x1x1]
%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, 512x256x1x1]
%onnx::Conv_951[FLOAT, 512]
%onnx::Conv_953[FLOAT, 256x512x1x1]
%onnx::Conv_956[FLOAT, 256x256x1x1]
%onnx::Conv_959[FLOAT, 256x512x1x1]
%onnx::Conv_962[FLOAT, 256x512x1x1]
%onnx::Conv_965[FLOAT, 256x256x3x3]
%onnx::Conv_968[FLOAT, 512x512x1x1]
%onnx::Conv_971[FLOAT, 256x512x1x1]
%onnx::Conv_974[FLOAT, 256x256x1x1]
%onnx::Conv_977[FLOAT, 256x512x1x1]
%onnx::Conv_980[FLOAT, 256x512x1x1]
%onnx::Conv_983[FLOAT, 256x256x3x3]
%onnx::Conv_986[FLOAT, 512x512x1x1]
) {
%onnx::Conv_987 = Identity(%onnx::Conv_951)
%onnx::Conv_984 = Identity(%onnx::Conv_897)
%onnx::Conv_981 = Identity(%onnx::Conv_897)
%onnx::Conv_978 = Identity(%onnx::Conv_897)
%onnx::Conv_975 = Identity(%onnx::Conv_897)
%onnx::Conv_972 = Identity(%onnx::Conv_897)
%onnx::Conv_969 = Identity(%onnx::Conv_951)
%onnx::Conv_966 = Identity(%onnx::Conv_897)
%onnx::Conv_963 = Identity(%onnx::Conv_897)
%onnx::Conv_960 = Identity(%onnx::Conv_897)
%onnx::Conv_957 = Identity(%onnx::Conv_897)
%onnx::Conv_954 = Identity(%onnx::Conv_897)
%onnx::Conv_948 = Identity(%onnx::Conv_897)
%onnx::Conv_945 = Identity(%onnx::Conv_897)
%onnx::Conv_942 = Identity(%onnx::Conv_897)
%onnx::Conv_939 = Identity(%onnx::Conv_897)
%onnx::Conv_936 = Identity(%onnx::Conv_897)
%onnx::Conv_933 = Identity(%onnx::Conv_897)
%onnx::Conv_930 = Identity(%onnx::Conv_825)
%onnx::Conv_927 = Identity(%onnx::Conv_825)
%onnx::Conv_924 = Identity(%onnx::Conv_825)
%onnx::Conv_921 = Identity(%onnx::Conv_825)
%onnx::Conv_918 = Identity(%onnx::Conv_825)
%onnx::Conv_915 = Identity(%onnx::Conv_897)
%onnx::Conv_912 = Identity(%onnx::Conv_825)
%onnx::Conv_909 = Identity(%onnx::Conv_825)
%onnx::Conv_906 = Identity(%onnx::Conv_825)
%onnx::Conv_903 = Identity(%onnx::Conv_825)
%onnx::Conv_900 = Identity(%onnx::Conv_825)
%onnx::Conv_894 = Identity(%onnx::Conv_825)
%onnx::Conv_891 = Identity(%onnx::Conv_825)
%onnx::Conv_888 = Identity(%onnx::Conv_825)
%onnx::Conv_885 = Identity(%onnx::Conv_825)
%onnx::Conv_882 = Identity(%onnx::Conv_825)
%onnx::Conv_879 = Identity(%onnx::Conv_825)
%onnx::Conv_876 = Identity(%onnx::Conv_828)
%onnx::Conv_873 = Identity(%onnx::Conv_828)
%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_825)
%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_825)
%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)
%/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_824, %onnx::Conv_825)
%/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_827, %onnx::Conv_828)
%/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_830, %onnx::Conv_831)
%/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_833, %onnx::Conv_834)
%/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/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_836, %onnx::Conv_837)
%/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.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/conv3x3/conv_bn_relu/conv_bn_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_839, %onnx::Conv_840)
%/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.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_842, %onnx::Conv_843)
%/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/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_3_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/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_848, %onnx::Conv_849)
%/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_3_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/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/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_3_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/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.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/conv3x3/conv_bn_relu/conv_bn_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_857, %onnx::Conv_858)
%/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.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_3_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/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/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_3_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/Add_3_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/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/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_3_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/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.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/conv3x3/conv_bn_relu/conv_bn_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/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.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_3_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/Add_3_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_3_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/conv1x1/conv_bn_relu/conv_bn_relu.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_884, %onnx::Conv_885)
%/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_887, %onnx::Conv_888)
%/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/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_890, %onnx::Conv_891)
%/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.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/conv3x3/conv_bn_relu/conv_bn_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_893, %onnx::Conv_894)
%/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.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_896, %onnx::Conv_897)
%/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/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_3_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/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_902, %onnx::Conv_903)
%/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_3_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/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/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_3_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/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.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/conv3x3/conv_bn_relu/conv_bn_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_911, %onnx::Conv_912)
%/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.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_3_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/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/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_3_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/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_920, %onnx::Conv_921)
%/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_3_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/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/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_3_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/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.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/conv3x3/conv_bn_relu/conv_bn_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_929, %onnx::Conv_930)
%/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.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_3_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/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/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_3_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_935, %onnx::Conv_936)
%/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_938, %onnx::Conv_939)
%/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_941, %onnx::Conv_942)
%/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/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_944, %onnx::Conv_945)
%/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.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/conv3x3/conv_bn_relu/conv_bn_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_947, %onnx::Conv_948)
%/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.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_950, %onnx::Conv_951)
%/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/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_3_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/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_956, %onnx::Conv_957)
%/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_3_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/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/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_3_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/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.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/conv3x3/conv_bn_relu/conv_bn_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_965, %onnx::Conv_966)
%/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.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_3_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/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/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_3_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/conv1x1/conv_bn_relu/conv_bn_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_974, %onnx::Conv_975)
%/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_3_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/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/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_3_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/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.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/conv3x3/conv_bn_relu/conv_bn_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_983, %onnx::Conv_984)
%/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.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_3_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/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/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_3_output_0)
%822 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %822
}
|
val_accuracy
| 93.69992
| 1,453,467,648
| 4,779,018
|
{'zcp_epe_nas': 68.42897242438363, 'zcp_fisher': 0.987722516059875, 'zcp_flops': 23255482368.0, 'zcp_grad_norm': 22.336713790893555, 'zcp_grasp': -1.586605072021484, 'zcp_jacov': -16.048725883348343, 'zcp_l2_norm': 1085.8817138671875, 'zcp_nwot': 226.59736575233143, 'zcp_params': 4779018.0, 'zcp_plain': 0.056283824145793006, 'zcp_snip': 145.57595825195312, 'zcp_synflow': 68.46005024215764, 'zcp_zen': 100.299072265625, 'zcp_val_accuracy': 0.930188298225402}
| |
NASBench101_246506
|
NASBench101
|
246506
|
9539af7e34082f03a2d3bba7a0dcb574
|
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, 43x43x1x1]
%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, 43x43x1x1]
%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, 43x43x1x1]
%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, 86x86x1x1]
%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, 86x86x1x1]
%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, 86x86x1x1]
%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, 171x171x1x1]
%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, 171x171x1x1]
%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, 171x171x1x1]
%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/conv1x1/conv_bn_relu/conv_bn_relu.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_929, %onnx::Conv_930)
%/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_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/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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_relu.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_947, %onnx::Conv_948)
%/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_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/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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_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_965, %onnx::Conv_966)
%/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_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/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_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_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/conv1x1/conv_bn_relu/conv_bn_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/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_relu.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_983, %onnx::Conv_984)
%/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 = <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/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.2/conv3x3/conv_bn_relu/conv_bn_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/input_op.3/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_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_3_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/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_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/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1001, %onnx::Conv_1002)
%/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 = <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/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.2/conv3x3/conv_bn_relu/conv_bn_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/input_op.3/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_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_3_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/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_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/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_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_1019, %onnx::Conv_1020)
%/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 = <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/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.2/conv3x3/conv_bn_relu/conv_bn_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/input_op.3/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_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_3_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/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_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/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1037, %onnx::Conv_1038)
%/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_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/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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1055, %onnx::Conv_1056)
%/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_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/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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_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_1073, %onnx::Conv_1074)
%/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_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/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_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_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/conv1x1/conv_bn_relu/conv_bn_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/conv1x1/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
| 90.835339
| 603,398,144
| 1,979,695
|
{'zcp_epe_nas': 98.44579188909178, 'zcp_fisher': 77.89031219482422, 'zcp_flops': 9654370304.0, 'zcp_grad_norm': 233.37167358398438, 'zcp_grasp': 603.796875, 'zcp_jacov': -16.053103072763385, 'zcp_l2_norm': 884.5720825195312, 'zcp_nwot': 218.99069261106084, 'zcp_params': 1979695.0, 'zcp_plain': 0.018614945933222, 'zcp_snip': 929.0988159179688, 'zcp_synflow': 106.37739555478251, 'zcp_zen': 79.43924713134766, 'zcp_val_accuracy': 0.878605782985687}
| |
NASBench101_359728
|
NASBench101
|
359728
|
d96e6ae3c702dccbdc1e0a91255844ce
|
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, 43x128x1x1]
%onnx::Conv_824[FLOAT, 43x43x3x3]
%onnx::Conv_827[FLOAT, 42x42x1x1]
%onnx::Conv_828[FLOAT, 42]
%onnx::Conv_830[FLOAT, 43x128x1x1]
%onnx::Conv_833[FLOAT, 43x43x3x3]
%onnx::Conv_836[FLOAT, 43x128x1x1]
%onnx::Conv_839[FLOAT, 43x43x3x3]
%onnx::Conv_842[FLOAT, 42x42x1x1]
%onnx::Conv_845[FLOAT, 43x128x1x1]
%onnx::Conv_848[FLOAT, 43x43x3x3]
%onnx::Conv_851[FLOAT, 43x128x1x1]
%onnx::Conv_854[FLOAT, 43x43x3x3]
%onnx::Conv_857[FLOAT, 42x42x1x1]
%onnx::Conv_860[FLOAT, 86x128x1x1]
%onnx::Conv_861[FLOAT, 86]
%onnx::Conv_863[FLOAT, 86x86x3x3]
%onnx::Conv_866[FLOAT, 85x128x1x1]
%onnx::Conv_867[FLOAT, 85]
%onnx::Conv_869[FLOAT, 85x85x3x3]
%onnx::Conv_872[FLOAT, 85x85x1x1]
%onnx::Conv_875[FLOAT, 86x256x1x1]
%onnx::Conv_878[FLOAT, 86x86x3x3]
%onnx::Conv_881[FLOAT, 85x256x1x1]
%onnx::Conv_884[FLOAT, 85x85x3x3]
%onnx::Conv_887[FLOAT, 85x85x1x1]
%onnx::Conv_890[FLOAT, 86x256x1x1]
%onnx::Conv_893[FLOAT, 86x86x3x3]
%onnx::Conv_896[FLOAT, 85x256x1x1]
%onnx::Conv_899[FLOAT, 85x85x3x3]
%onnx::Conv_902[FLOAT, 85x85x1x1]
%onnx::Conv_905[FLOAT, 171x256x1x1]
%onnx::Conv_906[FLOAT, 171]
%onnx::Conv_908[FLOAT, 171x171x3x3]
%onnx::Conv_911[FLOAT, 171x256x1x1]
%onnx::Conv_914[FLOAT, 171x171x3x3]
%onnx::Conv_917[FLOAT, 170x170x1x1]
%onnx::Conv_918[FLOAT, 170]
%onnx::Conv_920[FLOAT, 171x512x1x1]
%onnx::Conv_923[FLOAT, 171x171x3x3]
%onnx::Conv_926[FLOAT, 171x512x1x1]
%onnx::Conv_929[FLOAT, 171x171x3x3]
%onnx::Conv_932[FLOAT, 170x170x1x1]
%onnx::Conv_935[FLOAT, 171x512x1x1]
%onnx::Conv_938[FLOAT, 171x171x3x3]
%onnx::Conv_941[FLOAT, 171x512x1x1]
%onnx::Conv_944[FLOAT, 171x171x3x3]
%onnx::Conv_947[FLOAT, 170x170x1x1]
) {
%onnx::Conv_948 = Identity(%onnx::Conv_918)
%onnx::Conv_945 = Identity(%onnx::Conv_906)
%onnx::Conv_942 = Identity(%onnx::Conv_906)
%onnx::Conv_939 = Identity(%onnx::Conv_906)
%onnx::Conv_936 = Identity(%onnx::Conv_906)
%onnx::Conv_933 = Identity(%onnx::Conv_918)
%onnx::Conv_930 = Identity(%onnx::Conv_906)
%onnx::Conv_927 = Identity(%onnx::Conv_906)
%onnx::Conv_924 = Identity(%onnx::Conv_906)
%onnx::Conv_921 = Identity(%onnx::Conv_906)
%onnx::Conv_915 = Identity(%onnx::Conv_906)
%onnx::Conv_912 = Identity(%onnx::Conv_906)
%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_828)
%onnx::Conv_855 = Identity(%onnx::Conv_816)
%onnx::Conv_852 = Identity(%onnx::Conv_816)
%onnx::Conv_849 = Identity(%onnx::Conv_816)
%onnx::Conv_846 = Identity(%onnx::Conv_816)
%onnx::Conv_843 = Identity(%onnx::Conv_828)
%onnx::Conv_840 = Identity(%onnx::Conv_816)
%onnx::Conv_837 = Identity(%onnx::Conv_816)
%onnx::Conv_834 = Identity(%onnx::Conv_816)
%onnx::Conv_831 = Identity(%onnx::Conv_816)
%onnx::Conv_825 = Identity(%onnx::Conv_816)
%onnx::Conv_822 = Identity(%onnx::Conv_816)
%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/conv3x3/conv_bn_relu/conv_bn_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_818, %onnx::Conv_819)
%/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/input_op.3/conv_bn_relu/conv_bn_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_821, %onnx::Conv_822)
%/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_824, %onnx::Conv_825)
%/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 = <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_3_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_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_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/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/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/conv3x3/conv_bn_relu/conv_bn_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_833, %onnx::Conv_834)
%/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/input_op.3/conv_bn_relu/conv_bn_relu.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_836, %onnx::Conv_837)
%/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_839, %onnx::Conv_840)
%/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 = <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_3_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_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_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/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/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/conv3x3/conv_bn_relu/conv_bn_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_848, %onnx::Conv_849)
%/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/input_op.3/conv_bn_relu/conv_bn_relu.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_851, %onnx::Conv_852)
%/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_854, %onnx::Conv_855)
%/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 = <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_3_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_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_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/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/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/conv3x3/conv_bn_relu/conv_bn_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_863, %onnx::Conv_864)
%/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/input_op.3/conv_bn_relu/conv_bn_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_866, %onnx::Conv_867)
%/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/Slice_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_869, %onnx::Conv_870)
%/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_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_3_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_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_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/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/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/conv3x3/conv_bn_relu/conv_bn_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_878, %onnx::Conv_879)
%/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/input_op.3/conv_bn_relu/conv_bn_relu.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_881, %onnx::Conv_882)
%/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/Slice_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_884, %onnx::Conv_885)
%/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_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_3_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_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_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/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/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/conv3x3/conv_bn_relu/conv_bn_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_893, %onnx::Conv_894)
%/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/input_op.3/conv_bn_relu/conv_bn_relu.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_896, %onnx::Conv_897)
%/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/Slice_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_899, %onnx::Conv_900)
%/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_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_3_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_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_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/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/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/conv3x3/conv_bn_relu/conv_bn_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_908, %onnx::Conv_909)
%/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/input_op.3/conv_bn_relu/conv_bn_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_911, %onnx::Conv_912)
%/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_914, %onnx::Conv_915)
%/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 = <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_3_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_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_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/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/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/conv3x3/conv_bn_relu/conv_bn_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_923, %onnx::Conv_924)
%/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/input_op.3/conv_bn_relu/conv_bn_relu.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_926, %onnx::Conv_927)
%/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_929, %onnx::Conv_930)
%/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 = <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_3_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_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_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/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/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/conv3x3/conv_bn_relu/conv_bn_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_938, %onnx::Conv_939)
%/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/input_op.3/conv_bn_relu/conv_bn_relu.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_941, %onnx::Conv_942)
%/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_944, %onnx::Conv_945)
%/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 = <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_3_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_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_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/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/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
| 92.117387
| 838,783,232
| 2,785,330
|
{'zcp_epe_nas': 76.89993601213699, 'zcp_fisher': 28.156742095947266, 'zcp_flops': 13420531712.0, 'zcp_grad_norm': 91.7581558227539, 'zcp_grasp': -13.5675048828125, 'zcp_jacov': -16.065750285355342, 'zcp_l2_norm': 762.1968383789062, 'zcp_nwot': 215.7262268943098, 'zcp_params': 2785330.0, 'zcp_plain': 0.056171402335166, 'zcp_snip': 476.6947326660156, 'zcp_synflow': 91.46731895161402, 'zcp_zen': 83.38207244873047, 'zcp_val_accuracy': 0.920472741127014}
| |
NASBench101_149977
|
NASBench101
|
149977
|
5ab7169ec53aa4a09ac46f438965af04
|
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, 64x64x3x3]
%onnx::Conv_1001[FLOAT, 64x64x1x1]
%onnx::Conv_1004[FLOAT, 64x128x1x1]
%onnx::Conv_1007[FLOAT, 64x64x1x1]
%onnx::Conv_1010[FLOAT, 64x128x1x1]
%onnx::Conv_1013[FLOAT, 64x64x3x3]
%onnx::Conv_1016[FLOAT, 64x128x1x1]
%onnx::Conv_1019[FLOAT, 64x64x3x3]
%onnx::Conv_1022[FLOAT, 64x64x1x1]
%onnx::Conv_1025[FLOAT, 64x128x1x1]
%onnx::Conv_1028[FLOAT, 64x64x1x1]
%onnx::Conv_1031[FLOAT, 64x128x1x1]
%onnx::Conv_1034[FLOAT, 64x64x3x3]
%onnx::Conv_1037[FLOAT, 64x128x1x1]
%onnx::Conv_1040[FLOAT, 64x64x3x3]
%onnx::Conv_1043[FLOAT, 64x64x1x1]
%onnx::Conv_1046[FLOAT, 64x128x1x1]
%onnx::Conv_1049[FLOAT, 64x64x1x1]
%onnx::Conv_1052[FLOAT, 128x128x1x1]
%onnx::Conv_1055[FLOAT, 128x128x3x3]
%onnx::Conv_1058[FLOAT, 128x128x1x1]
%onnx::Conv_1061[FLOAT, 128x128x3x3]
%onnx::Conv_1064[FLOAT, 128x128x1x1]
%onnx::Conv_1067[FLOAT, 128x128x1x1]
%onnx::Conv_1070[FLOAT, 128x128x1x1]
%onnx::Conv_1073[FLOAT, 128x256x1x1]
%onnx::Conv_1076[FLOAT, 128x128x3x3]
%onnx::Conv_1079[FLOAT, 128x256x1x1]
%onnx::Conv_1082[FLOAT, 128x128x3x3]
%onnx::Conv_1085[FLOAT, 128x128x1x1]
%onnx::Conv_1088[FLOAT, 128x256x1x1]
%onnx::Conv_1091[FLOAT, 128x128x1x1]
%onnx::Conv_1094[FLOAT, 128x256x1x1]
%onnx::Conv_1097[FLOAT, 128x128x3x3]
%onnx::Conv_1100[FLOAT, 128x256x1x1]
%onnx::Conv_1103[FLOAT, 128x128x3x3]
%onnx::Conv_1106[FLOAT, 128x128x1x1]
%onnx::Conv_1109[FLOAT, 128x256x1x1]
%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, 256x256x3x3]
%onnx::Conv_1127[FLOAT, 256x256x1x1]
%onnx::Conv_1130[FLOAT, 256x256x1x1]
%onnx::Conv_1133[FLOAT, 256x256x1x1]
%onnx::Conv_1136[FLOAT, 256x512x1x1]
%onnx::Conv_1139[FLOAT, 256x256x3x3]
%onnx::Conv_1142[FLOAT, 256x512x1x1]
%onnx::Conv_1145[FLOAT, 256x256x3x3]
%onnx::Conv_1148[FLOAT, 256x256x1x1]
%onnx::Conv_1151[FLOAT, 256x512x1x1]
%onnx::Conv_1154[FLOAT, 256x256x1x1]
%onnx::Conv_1157[FLOAT, 256x512x1x1]
%onnx::Conv_1160[FLOAT, 256x256x3x3]
%onnx::Conv_1163[FLOAT, 256x512x1x1]
%onnx::Conv_1166[FLOAT, 256x256x3x3]
%onnx::Conv_1169[FLOAT, 256x256x1x1]
%onnx::Conv_1172[FLOAT, 256x512x1x1]
%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/conv3x3/conv_bn_relu/conv_bn_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/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_1001, %onnx::Conv_1002)
%/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_1004, %onnx::Conv_1005)
%/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 = <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_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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/conv3x3/conv_bn_relu/conv_bn_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/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_1022, %onnx::Conv_1023)
%/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_1025, %onnx::Conv_1026)
%/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 = <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_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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/conv3x3/conv_bn_relu/conv_bn_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/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_1043, %onnx::Conv_1044)
%/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_1046, %onnx::Conv_1047)
%/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 = <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_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/conv1x1/conv_bn_relu/conv_bn_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.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_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/conv3x3/conv_bn_relu/conv_bn_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 = <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_1064, %onnx::Conv_1065)
%/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_1067, %onnx::Conv_1068)
%/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/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/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/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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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 = <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_1085, %onnx::Conv_1086)
%/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_1088, %onnx::Conv_1089)
%/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/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/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/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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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 = <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_1106, %onnx::Conv_1107)
%/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_1109, %onnx::Conv_1110)
%/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/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/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/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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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/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_1127, %onnx::Conv_1128)
%/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_1130, %onnx::Conv_1131)
%/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 = <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_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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/conv3x3/conv_bn_relu/conv_bn_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/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_1148, %onnx::Conv_1149)
%/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_1151, %onnx::Conv_1152)
%/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 = <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_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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/conv3x3/conv_bn_relu/conv_bn_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/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_1169, %onnx::Conv_1170)
%/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_1172, %onnx::Conv_1173)
%/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 = <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_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/conv1x1/conv_bn_relu/conv_bn_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.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)
%984 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %984
}
|
val_accuracy
| 93.129009
| 1,940,006,912
| 6,491,146
|
{'zcp_epe_nas': 88.48800902705261, 'zcp_fisher': 11.660444259643555, 'zcp_flops': 31040110592.0, 'zcp_grad_norm': 76.98271942138672, 'zcp_grasp': -6.190673828125, 'zcp_jacov': -16.069599259285766, 'zcp_l2_norm': 1188.5946044921875, 'zcp_nwot': 226.62429016820178, 'zcp_params': 6491146.0, 'zcp_plain': 0.047624215483665, 'zcp_snip': 477.750244140625, 'zcp_synflow': 108.08559620161391, 'zcp_zen': 108.80288696289062, 'zcp_val_accuracy': 0.926482379436492}
| |
NASBench101_418107
|
NASBench101
|
418107
|
fcaafe583035839d41ff48fc12381e9b
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_938[FLOAT, 128x3x3x3]
%onnx::Conv_939[FLOAT, 128]
%onnx::Conv_941[FLOAT, 43x128x1x1]
%onnx::Conv_942[FLOAT, 43]
%onnx::Conv_944[FLOAT, 43x43x3x3]
%onnx::Conv_947[FLOAT, 43x43x1x1]
%onnx::Conv_950[FLOAT, 42x128x1x1]
%onnx::Conv_951[FLOAT, 42]
%onnx::Conv_953[FLOAT, 42x42x1x1]
%onnx::Conv_956[FLOAT, 42x42x3x3]
%onnx::Conv_959[FLOAT, 43x128x1x1]
%onnx::Conv_962[FLOAT, 43x43x3x3]
%onnx::Conv_965[FLOAT, 43x43x1x1]
%onnx::Conv_968[FLOAT, 42x128x1x1]
%onnx::Conv_971[FLOAT, 42x42x1x1]
%onnx::Conv_974[FLOAT, 42x42x3x3]
%onnx::Conv_977[FLOAT, 43x128x1x1]
%onnx::Conv_980[FLOAT, 43x43x3x3]
%onnx::Conv_983[FLOAT, 43x43x1x1]
%onnx::Conv_986[FLOAT, 42x128x1x1]
%onnx::Conv_989[FLOAT, 42x42x1x1]
%onnx::Conv_992[FLOAT, 42x42x3x3]
%onnx::Conv_995[FLOAT, 86x128x1x1]
%onnx::Conv_996[FLOAT, 86]
%onnx::Conv_998[FLOAT, 86x86x3x3]
%onnx::Conv_1001[FLOAT, 86x86x1x1]
%onnx::Conv_1004[FLOAT, 85x128x1x1]
%onnx::Conv_1005[FLOAT, 85]
%onnx::Conv_1007[FLOAT, 85x85x1x1]
%onnx::Conv_1010[FLOAT, 85x85x3x3]
%onnx::Conv_1013[FLOAT, 86x256x1x1]
%onnx::Conv_1016[FLOAT, 86x86x3x3]
%onnx::Conv_1019[FLOAT, 86x86x1x1]
%onnx::Conv_1022[FLOAT, 85x256x1x1]
%onnx::Conv_1025[FLOAT, 85x85x1x1]
%onnx::Conv_1028[FLOAT, 85x85x3x3]
%onnx::Conv_1031[FLOAT, 86x256x1x1]
%onnx::Conv_1034[FLOAT, 86x86x3x3]
%onnx::Conv_1037[FLOAT, 86x86x1x1]
%onnx::Conv_1040[FLOAT, 85x256x1x1]
%onnx::Conv_1043[FLOAT, 85x85x1x1]
%onnx::Conv_1046[FLOAT, 85x85x3x3]
%onnx::Conv_1049[FLOAT, 171x256x1x1]
%onnx::Conv_1050[FLOAT, 171]
%onnx::Conv_1052[FLOAT, 171x171x3x3]
%onnx::Conv_1055[FLOAT, 171x171x1x1]
%onnx::Conv_1058[FLOAT, 170x256x1x1]
%onnx::Conv_1059[FLOAT, 170]
%onnx::Conv_1061[FLOAT, 170x170x1x1]
%onnx::Conv_1064[FLOAT, 170x170x3x3]
%onnx::Conv_1067[FLOAT, 171x512x1x1]
%onnx::Conv_1070[FLOAT, 171x171x3x3]
%onnx::Conv_1073[FLOAT, 171x171x1x1]
%onnx::Conv_1076[FLOAT, 170x512x1x1]
%onnx::Conv_1079[FLOAT, 170x170x1x1]
%onnx::Conv_1082[FLOAT, 170x170x3x3]
%onnx::Conv_1085[FLOAT, 171x512x1x1]
%onnx::Conv_1088[FLOAT, 171x171x3x3]
%onnx::Conv_1091[FLOAT, 171x171x1x1]
%onnx::Conv_1094[FLOAT, 170x512x1x1]
%onnx::Conv_1097[FLOAT, 170x170x1x1]
%onnx::Conv_1100[FLOAT, 170x170x3x3]
) {
%onnx::Conv_1101 = Identity(%onnx::Conv_1059)
%onnx::Conv_1098 = Identity(%onnx::Conv_1059)
%onnx::Conv_1095 = Identity(%onnx::Conv_1059)
%onnx::Conv_1092 = Identity(%onnx::Conv_1050)
%onnx::Conv_1089 = Identity(%onnx::Conv_1050)
%onnx::Conv_1086 = Identity(%onnx::Conv_1050)
%onnx::Conv_1083 = Identity(%onnx::Conv_1059)
%onnx::Conv_1080 = Identity(%onnx::Conv_1059)
%onnx::Conv_1077 = Identity(%onnx::Conv_1059)
%onnx::Conv_1074 = Identity(%onnx::Conv_1050)
%onnx::Conv_1071 = Identity(%onnx::Conv_1050)
%onnx::Conv_1068 = Identity(%onnx::Conv_1050)
%onnx::Conv_1065 = Identity(%onnx::Conv_1059)
%onnx::Conv_1062 = Identity(%onnx::Conv_1059)
%onnx::Conv_1056 = Identity(%onnx::Conv_1050)
%onnx::Conv_1053 = Identity(%onnx::Conv_1050)
%onnx::Conv_1047 = Identity(%onnx::Conv_1005)
%onnx::Conv_1044 = Identity(%onnx::Conv_1005)
%onnx::Conv_1041 = Identity(%onnx::Conv_1005)
%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_1005)
%onnx::Conv_1026 = Identity(%onnx::Conv_1005)
%onnx::Conv_1023 = Identity(%onnx::Conv_1005)
%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_1005)
%onnx::Conv_1008 = Identity(%onnx::Conv_1005)
%onnx::Conv_1002 = Identity(%onnx::Conv_996)
%onnx::Conv_999 = Identity(%onnx::Conv_996)
%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_942)
%onnx::Conv_981 = Identity(%onnx::Conv_942)
%onnx::Conv_978 = Identity(%onnx::Conv_942)
%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_942)
%onnx::Conv_963 = Identity(%onnx::Conv_942)
%onnx::Conv_960 = Identity(%onnx::Conv_942)
%onnx::Conv_957 = Identity(%onnx::Conv_951)
%onnx::Conv_954 = Identity(%onnx::Conv_951)
%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_938, %onnx::Conv_939)
%/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_941, %onnx::Conv_942)
%/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_944, %onnx::Conv_945)
%/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_947, %onnx::Conv_948)
%/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_950, %onnx::Conv_951)
%/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/input_op.4/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_3_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/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.2/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_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/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_956, %onnx::Conv_957)
%/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.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_959, %onnx::Conv_960)
%/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_962, %onnx::Conv_963)
%/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_965, %onnx::Conv_966)
%/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/Concat_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/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/input_op.4/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_3_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/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.2/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_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/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_974, %onnx::Conv_975)
%/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.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_977, %onnx::Conv_978)
%/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_980, %onnx::Conv_981)
%/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_983, %onnx::Conv_984)
%/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/Concat_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/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/input_op.4/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_3_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/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.2/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_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/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_992, %onnx::Conv_993)
%/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.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_995, %onnx::Conv_996)
%/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_998, %onnx::Conv_999)
%/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_1001, %onnx::Conv_1002)
%/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/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_1004, %onnx::Conv_1005)
%/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/input_op.4/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_1007, %onnx::Conv_1008)
%/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.2/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/conv3x3/conv_bn_relu/conv_bn_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_1010, %onnx::Conv_1011)
%/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.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_1013, %onnx::Conv_1014)
%/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_1016, %onnx::Conv_1017)
%/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_1019, %onnx::Conv_1020)
%/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/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_1022, %onnx::Conv_1023)
%/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/input_op.4/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_1025, %onnx::Conv_1026)
%/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.2/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/conv3x3/conv_bn_relu/conv_bn_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_1028, %onnx::Conv_1029)
%/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.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_1031, %onnx::Conv_1032)
%/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_1034, %onnx::Conv_1035)
%/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_1037, %onnx::Conv_1038)
%/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/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_1040, %onnx::Conv_1041)
%/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/input_op.4/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_1043, %onnx::Conv_1044)
%/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.2/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/conv3x3/conv_bn_relu/conv_bn_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_1046, %onnx::Conv_1047)
%/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.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_1049, %onnx::Conv_1050)
%/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_1052, %onnx::Conv_1053)
%/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_1055, %onnx::Conv_1056)
%/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_1058, %onnx::Conv_1059)
%/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/input_op.4/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_3_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/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.2/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_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/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_1064, %onnx::Conv_1065)
%/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.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_1067, %onnx::Conv_1068)
%/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_1070, %onnx::Conv_1071)
%/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_1073, %onnx::Conv_1074)
%/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/Concat_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/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/input_op.4/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_3_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/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.2/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_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/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_1082, %onnx::Conv_1083)
%/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.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_1085, %onnx::Conv_1086)
%/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_1088, %onnx::Conv_1089)
%/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_1091, %onnx::Conv_1092)
%/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/Concat_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/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/input_op.4/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_3_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/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.2/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_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/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_1100, %onnx::Conv_1101)
%/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.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)
%936 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %936
}
|
val_accuracy
| 91.786861
| 867,698,944
| 2,889,398
|
{'zcp_epe_nas': 79.51922195009908, 'zcp_fisher': 170.05397033691406, 'zcp_flops': 13883183104.0, 'zcp_grad_norm': 225.7913360595703, 'zcp_grasp': -59.4716796875, 'zcp_jacov': -16.054555051882627, 'zcp_l2_norm': 884.6383666992188, 'zcp_nwot': 218.55879332924206, 'zcp_params': 2889398.0, 'zcp_plain': 0.037572089582681004, 'zcp_snip': 1132.99072265625, 'zcp_synflow': 110.00268253954724, 'zcp_zen': 88.70643615722656, 'zcp_val_accuracy': 0.916866958141326}
| |
NASBench101_213964
|
NASBench101
|
213964
|
81a2a2585bdef98b8e449795c87ad9a9
|
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, 64x128x1x1]
%onnx::Conv_875[FLOAT, 64x64x1x1]
%onnx::Conv_878[FLOAT, 64x64x1x1]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_884[FLOAT, 64x64x3x3]
%onnx::Conv_887[FLOAT, 64x128x1x1]
%onnx::Conv_890[FLOAT, 64x128x1x1]
%onnx::Conv_893[FLOAT, 64x64x1x1]
%onnx::Conv_896[FLOAT, 64x64x1x1]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x128x1x1]
%onnx::Conv_908[FLOAT, 64x128x1x1]
%onnx::Conv_911[FLOAT, 64x64x1x1]
%onnx::Conv_914[FLOAT, 64x64x1x1]
%onnx::Conv_917[FLOAT, 128x128x1x1]
%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, 128x256x1x1]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 128x256x1x1]
%onnx::Conv_944[FLOAT, 128x256x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x256x1x1]
%onnx::Conv_962[FLOAT, 128x256x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x128x1x1]
%onnx::Conv_971[FLOAT, 256x256x1x1]
%onnx::Conv_972[FLOAT, 256]
%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, 256x512x1x1]
%onnx::Conv_992[FLOAT, 256x256x3x3]
%onnx::Conv_995[FLOAT, 256x512x1x1]
%onnx::Conv_998[FLOAT, 256x512x1x1]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 256x256x1x1]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x512x1x1]
%onnx::Conv_1016[FLOAT, 256x512x1x1]
%onnx::Conv_1019[FLOAT, 256x256x1x1]
%onnx::Conv_1022[FLOAT, 256x256x1x1]
) {
%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_861)
%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_861)
%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_933 = 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_864)
%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_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)
%/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/input_op.2/conv_bn_relu/conv_bn_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.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_872, %onnx::Conv_873)
%/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_875, %onnx::Conv_876)
%/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/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_878, %onnx::Conv_879)
%/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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.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_890, %onnx::Conv_891)
%/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_893, %onnx::Conv_894)
%/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/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_896, %onnx::Conv_897)
%/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_905, %onnx::Conv_906)
%/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_908, %onnx::Conv_909)
%/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_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/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/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/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/conv1x1/conv_bn_relu/conv_bn_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_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.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/input_op.2/conv_bn_relu/conv_bn_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.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_926, %onnx::Conv_927)
%/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_929, %onnx::Conv_930)
%/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/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_932, %onnx::Conv_933)
%/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_941, %onnx::Conv_942)
%/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_944, %onnx::Conv_945)
%/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_947, %onnx::Conv_948)
%/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/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_950, %onnx::Conv_951)
%/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_959, %onnx::Conv_960)
%/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_962, %onnx::Conv_963)
%/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_965, %onnx::Conv_966)
%/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/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/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/conv1x1/conv_bn_relu/conv_bn_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_968, %onnx::Conv_969)
%/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_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/input_op.2/conv_bn_relu/conv_bn_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.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_980, %onnx::Conv_981)
%/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_983, %onnx::Conv_984)
%/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/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_986, %onnx::Conv_987)
%/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_995, %onnx::Conv_996)
%/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_998, %onnx::Conv_999)
%/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_1001, %onnx::Conv_1002)
%/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/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1004, %onnx::Conv_1005)
%/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_1013, %onnx::Conv_1014)
%/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_1016, %onnx::Conv_1017)
%/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_1019, %onnx::Conv_1020)
%/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/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/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/conv1x1/conv_bn_relu/conv_bn_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_1022, %onnx::Conv_1023)
%/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)
%858 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %858
}
|
val_accuracy
| 93.259215
| 1,257,777,152
| 4,166,026
|
{'zcp_epe_nas': 67.25056575661449, 'zcp_fisher': 6.134082794189453, 'zcp_flops': 20124434432.0, 'zcp_grad_norm': 57.68089294433594, 'zcp_grasp': -2.556060791015625, 'zcp_jacov': -16.051225363219576, 'zcp_l2_norm': 1040.322265625, 'zcp_nwot': 224.57679361700463, 'zcp_params': 4166026.0, 'zcp_plain': 0.018658960238099, 'zcp_snip': 353.6246032714844, 'zcp_synflow': 81.9026972336974, 'zcp_zen': 91.85665893554688, 'zcp_val_accuracy': 0.9189703464508051}
| |
NASBench101_52321
|
NASBench101
|
52321
|
1fd2b867bd401a478869666a896b463e
|
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, 64x128x1x1]
%onnx::Conv_791[FLOAT, 64x64x3x3]
%onnx::Conv_794[FLOAT, 64x64x1x1]
%onnx::Conv_797[FLOAT, 64x128x1x1]
%onnx::Conv_800[FLOAT, 64x64x1x1]
%onnx::Conv_803[FLOAT, 64x128x1x1]
%onnx::Conv_806[FLOAT, 64x64x3x3]
%onnx::Conv_809[FLOAT, 64x64x1x1]
%onnx::Conv_812[FLOAT, 64x128x1x1]
%onnx::Conv_815[FLOAT, 64x64x1x1]
%onnx::Conv_818[FLOAT, 64x128x1x1]
%onnx::Conv_821[FLOAT, 64x64x3x3]
%onnx::Conv_824[FLOAT, 64x64x1x1]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 128x128x1x1]
%onnx::Conv_833[FLOAT, 128x128x1x1]
%onnx::Conv_836[FLOAT, 128x128x3x3]
%onnx::Conv_839[FLOAT, 128x128x1x1]
%onnx::Conv_842[FLOAT, 128x256x1x1]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x256x1x1]
%onnx::Conv_851[FLOAT, 128x128x3x3]
%onnx::Conv_854[FLOAT, 128x128x1x1]
%onnx::Conv_857[FLOAT, 128x256x1x1]
%onnx::Conv_860[FLOAT, 128x128x1x1]
%onnx::Conv_863[FLOAT, 128x256x1x1]
%onnx::Conv_866[FLOAT, 128x128x3x3]
%onnx::Conv_869[FLOAT, 128x128x1x1]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_873[FLOAT, 256]
%onnx::Conv_875[FLOAT, 256x256x1x1]
%onnx::Conv_878[FLOAT, 256x256x1x1]
%onnx::Conv_881[FLOAT, 256x256x3x3]
%onnx::Conv_884[FLOAT, 256x256x1x1]
%onnx::Conv_887[FLOAT, 256x512x1x1]
%onnx::Conv_890[FLOAT, 256x256x1x1]
%onnx::Conv_893[FLOAT, 256x512x1x1]
%onnx::Conv_896[FLOAT, 256x256x3x3]
%onnx::Conv_899[FLOAT, 256x256x1x1]
%onnx::Conv_902[FLOAT, 256x512x1x1]
%onnx::Conv_905[FLOAT, 256x256x1x1]
%onnx::Conv_908[FLOAT, 256x512x1x1]
%onnx::Conv_911[FLOAT, 256x256x3x3]
%onnx::Conv_914[FLOAT, 256x256x1x1]
) {
%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/input_op.2/conv_bn_relu/conv_bn_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_788, %onnx::Conv_789)
%/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_791, %onnx::Conv_792)
%/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.3/conv3x3/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_2_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/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_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/maxpool/MaxPool_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.1/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/input_op.2/conv_bn_relu/conv_bn_relu.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_803, %onnx::Conv_804)
%/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_806, %onnx::Conv_807)
%/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.3/conv3x3/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_2_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/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_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/maxpool/MaxPool_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.1/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/input_op.2/conv_bn_relu/conv_bn_relu.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_818, %onnx::Conv_819)
%/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_821, %onnx::Conv_822)
%/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.3/conv3x3/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_2_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/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_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/maxpool/MaxPool_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.1/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/input_op.2/conv_bn_relu/conv_bn_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_833, %onnx::Conv_834)
%/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_836, %onnx::Conv_837)
%/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.3/conv3x3/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_2_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/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_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/maxpool/MaxPool_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.1/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/input_op.2/conv_bn_relu/conv_bn_relu.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_848, %onnx::Conv_849)
%/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_851, %onnx::Conv_852)
%/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.3/conv3x3/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_2_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/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_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/maxpool/MaxPool_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.1/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/input_op.2/conv_bn_relu/conv_bn_relu.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_863, %onnx::Conv_864)
%/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_866, %onnx::Conv_867)
%/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.3/conv3x3/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_2_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/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_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/maxpool/MaxPool_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.1/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/input_op.2/conv_bn_relu/conv_bn_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_878, %onnx::Conv_879)
%/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_881, %onnx::Conv_882)
%/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.3/conv3x3/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_2_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/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_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/maxpool/MaxPool_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.1/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/input_op.2/conv_bn_relu/conv_bn_relu.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_893, %onnx::Conv_894)
%/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_896, %onnx::Conv_897)
%/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.3/conv3x3/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_2_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/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_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/maxpool/MaxPool_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.1/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/input_op.2/conv_bn_relu/conv_bn_relu.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_908, %onnx::Conv_909)
%/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_911, %onnx::Conv_912)
%/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.3/conv3x3/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_2_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/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_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/maxpool/MaxPool_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.1/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
| 89.773637
| 1,120,806,912
| 3,729,162
|
{'zcp_epe_nas': 84.4844952922393, 'zcp_fisher': 25.622631072998047, 'zcp_flops': 17932910592.0, 'zcp_grad_norm': 109.71258544921875, 'zcp_grasp': -55.798828125, 'zcp_jacov': -16.049482143889932, 'zcp_l2_norm': 843.6360473632812, 'zcp_nwot': 221.59065255359477, 'zcp_params': 3729162.0, 'zcp_plain': 0.24645850062370303, 'zcp_snip': 590.4683227539062, 'zcp_synflow': 84.66523922847473, 'zcp_zen': 80.64154052734375, 'zcp_val_accuracy': 0.9221754670143121}
| |
NASBench101_333882
|
NASBench101
|
333882
|
c9e4b8ead692aa47b54fd5107d04e121
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_938[FLOAT, 128x3x3x3]
%onnx::Conv_939[FLOAT, 128]
%onnx::Conv_941[FLOAT, 43x128x1x1]
%onnx::Conv_942[FLOAT, 43]
%onnx::Conv_944[FLOAT, 43x43x1x1]
%onnx::Conv_947[FLOAT, 43x128x1x1]
%onnx::Conv_950[FLOAT, 43x43x1x1]
%onnx::Conv_953[FLOAT, 43x43x1x1]
%onnx::Conv_956[FLOAT, 42x42x1x1]
%onnx::Conv_957[FLOAT, 42]
%onnx::Conv_959[FLOAT, 43x128x1x1]
%onnx::Conv_962[FLOAT, 43x43x1x1]
%onnx::Conv_965[FLOAT, 43x128x1x1]
%onnx::Conv_968[FLOAT, 43x43x1x1]
%onnx::Conv_971[FLOAT, 43x43x1x1]
%onnx::Conv_974[FLOAT, 42x42x1x1]
%onnx::Conv_977[FLOAT, 43x128x1x1]
%onnx::Conv_980[FLOAT, 43x43x1x1]
%onnx::Conv_983[FLOAT, 43x128x1x1]
%onnx::Conv_986[FLOAT, 43x43x1x1]
%onnx::Conv_989[FLOAT, 43x43x1x1]
%onnx::Conv_992[FLOAT, 42x42x1x1]
%onnx::Conv_995[FLOAT, 86x128x1x1]
%onnx::Conv_996[FLOAT, 86]
%onnx::Conv_998[FLOAT, 86x86x1x1]
%onnx::Conv_1001[FLOAT, 85x128x1x1]
%onnx::Conv_1002[FLOAT, 85]
%onnx::Conv_1004[FLOAT, 85x85x1x1]
%onnx::Conv_1007[FLOAT, 85x85x1x1]
%onnx::Conv_1010[FLOAT, 85x85x1x1]
%onnx::Conv_1013[FLOAT, 86x256x1x1]
%onnx::Conv_1016[FLOAT, 86x86x1x1]
%onnx::Conv_1019[FLOAT, 85x256x1x1]
%onnx::Conv_1022[FLOAT, 85x85x1x1]
%onnx::Conv_1025[FLOAT, 85x85x1x1]
%onnx::Conv_1028[FLOAT, 85x85x1x1]
%onnx::Conv_1031[FLOAT, 86x256x1x1]
%onnx::Conv_1034[FLOAT, 86x86x1x1]
%onnx::Conv_1037[FLOAT, 85x256x1x1]
%onnx::Conv_1040[FLOAT, 85x85x1x1]
%onnx::Conv_1043[FLOAT, 85x85x1x1]
%onnx::Conv_1046[FLOAT, 85x85x1x1]
%onnx::Conv_1049[FLOAT, 171x256x1x1]
%onnx::Conv_1050[FLOAT, 171]
%onnx::Conv_1052[FLOAT, 171x171x1x1]
%onnx::Conv_1055[FLOAT, 171x256x1x1]
%onnx::Conv_1058[FLOAT, 171x171x1x1]
%onnx::Conv_1061[FLOAT, 171x171x1x1]
%onnx::Conv_1064[FLOAT, 170x170x1x1]
%onnx::Conv_1065[FLOAT, 170]
%onnx::Conv_1067[FLOAT, 171x512x1x1]
%onnx::Conv_1070[FLOAT, 171x171x1x1]
%onnx::Conv_1073[FLOAT, 171x512x1x1]
%onnx::Conv_1076[FLOAT, 171x171x1x1]
%onnx::Conv_1079[FLOAT, 171x171x1x1]
%onnx::Conv_1082[FLOAT, 170x170x1x1]
%onnx::Conv_1085[FLOAT, 171x512x1x1]
%onnx::Conv_1088[FLOAT, 171x171x1x1]
%onnx::Conv_1091[FLOAT, 171x512x1x1]
%onnx::Conv_1094[FLOAT, 171x171x1x1]
%onnx::Conv_1097[FLOAT, 171x171x1x1]
%onnx::Conv_1100[FLOAT, 170x170x1x1]
) {
%onnx::Conv_1101 = Identity(%onnx::Conv_1065)
%onnx::Conv_1098 = Identity(%onnx::Conv_1050)
%onnx::Conv_1095 = Identity(%onnx::Conv_1050)
%onnx::Conv_1092 = Identity(%onnx::Conv_1050)
%onnx::Conv_1089 = Identity(%onnx::Conv_1050)
%onnx::Conv_1086 = Identity(%onnx::Conv_1050)
%onnx::Conv_1083 = Identity(%onnx::Conv_1065)
%onnx::Conv_1080 = Identity(%onnx::Conv_1050)
%onnx::Conv_1077 = Identity(%onnx::Conv_1050)
%onnx::Conv_1074 = Identity(%onnx::Conv_1050)
%onnx::Conv_1071 = Identity(%onnx::Conv_1050)
%onnx::Conv_1068 = Identity(%onnx::Conv_1050)
%onnx::Conv_1062 = Identity(%onnx::Conv_1050)
%onnx::Conv_1059 = Identity(%onnx::Conv_1050)
%onnx::Conv_1056 = Identity(%onnx::Conv_1050)
%onnx::Conv_1053 = Identity(%onnx::Conv_1050)
%onnx::Conv_1047 = Identity(%onnx::Conv_1002)
%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_996)
%onnx::Conv_1032 = Identity(%onnx::Conv_996)
%onnx::Conv_1029 = Identity(%onnx::Conv_1002)
%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_996)
%onnx::Conv_1014 = Identity(%onnx::Conv_996)
%onnx::Conv_1011 = Identity(%onnx::Conv_1002)
%onnx::Conv_1008 = Identity(%onnx::Conv_1002)
%onnx::Conv_1005 = Identity(%onnx::Conv_1002)
%onnx::Conv_999 = Identity(%onnx::Conv_996)
%onnx::Conv_993 = Identity(%onnx::Conv_957)
%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_957)
%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_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_938, %onnx::Conv_939)
%/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_941, %onnx::Conv_942)
%/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_944, %onnx::Conv_945)
%/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_947, %onnx::Conv_948)
%/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_950, %onnx::Conv_951)
%/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_953, %onnx::Conv_954)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_956, %onnx::Conv_957)
%/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.2/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.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.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_959, %onnx::Conv_960)
%/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_962, %onnx::Conv_963)
%/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_965, %onnx::Conv_966)
%/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_968, %onnx::Conv_969)
%/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_971, %onnx::Conv_972)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_974, %onnx::Conv_975)
%/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.2/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.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.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_977, %onnx::Conv_978)
%/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_980, %onnx::Conv_981)
%/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_983, %onnx::Conv_984)
%/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_986, %onnx::Conv_987)
%/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_989, %onnx::Conv_990)
%/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/conv1x1/conv_bn_relu/conv_bn_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_992, %onnx::Conv_993)
%/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.2/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.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.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_995, %onnx::Conv_996)
%/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_998, %onnx::Conv_999)
%/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_1001, %onnx::Conv_1002)
%/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_1004, %onnx::Conv_1005)
%/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_1007, %onnx::Conv_1008)
%/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.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_3_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/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_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/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.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.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_1013, %onnx::Conv_1014)
%/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_1016, %onnx::Conv_1017)
%/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_1019, %onnx::Conv_1020)
%/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_1022, %onnx::Conv_1023)
%/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_1025, %onnx::Conv_1026)
%/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.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_3_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/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_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/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.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.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_1031, %onnx::Conv_1032)
%/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_1034, %onnx::Conv_1035)
%/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_1037, %onnx::Conv_1038)
%/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_1040, %onnx::Conv_1041)
%/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_1043, %onnx::Conv_1044)
%/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.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_3_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/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_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/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.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.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_1049, %onnx::Conv_1050)
%/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_1052, %onnx::Conv_1053)
%/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_1055, %onnx::Conv_1056)
%/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_1058, %onnx::Conv_1059)
%/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_1061, %onnx::Conv_1062)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1064, %onnx::Conv_1065)
%/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.2/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.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.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_1067, %onnx::Conv_1068)
%/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_1070, %onnx::Conv_1071)
%/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_1073, %onnx::Conv_1074)
%/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_1076, %onnx::Conv_1077)
%/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_1079, %onnx::Conv_1080)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1082, %onnx::Conv_1083)
%/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.2/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.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.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_1085, %onnx::Conv_1086)
%/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_1088, %onnx::Conv_1089)
%/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_1091, %onnx::Conv_1092)
%/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_1094, %onnx::Conv_1095)
%/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_1097, %onnx::Conv_1098)
%/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/conv1x1/conv_bn_relu/conv_bn_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_1100, %onnx::Conv_1101)
%/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.2/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.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.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%936 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %936
}
|
val_accuracy
| 86.097759
| 333,227,648
| 1,058,845
|
{'zcp_epe_nas': 108.68675641392929, 'zcp_fisher': 61.08475875854492, 'zcp_flops': 5331642368.0, 'zcp_grad_norm': 175.77748107910156, 'zcp_grasp': -210.23583984375, 'zcp_jacov': -16.050352935768267, 'zcp_l2_norm': 883.32177734375, 'zcp_nwot': 218.81834036953038, 'zcp_params': 1058845.0, 'zcp_plain': -0.0062976740300650005, 'zcp_snip': 745.61962890625, 'zcp_synflow': 91.12963308152763, 'zcp_zen': 70.57489013671875, 'zcp_val_accuracy': 0.9055488705635071}
| |
NASBench101_152023
|
NASBench101
|
152023
|
5bf9802e98a61c76d83898c37957affe
|
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, 43x43x1x1]
%onnx::Conv_1022[FLOAT, 43x43x3x3]
%onnx::Conv_1025[FLOAT, 43x43x1x1]
%onnx::Conv_1028[FLOAT, 42x128x1x1]
%onnx::Conv_1029[FLOAT, 42]
%onnx::Conv_1031[FLOAT, 42x42x3x3]
%onnx::Conv_1034[FLOAT, 42x42x1x1]
%onnx::Conv_1037[FLOAT, 43x128x1x1]
%onnx::Conv_1040[FLOAT, 43x43x1x1]
%onnx::Conv_1043[FLOAT, 43x43x3x3]
%onnx::Conv_1046[FLOAT, 43x43x1x1]
%onnx::Conv_1049[FLOAT, 42x128x1x1]
%onnx::Conv_1052[FLOAT, 42x42x3x3]
%onnx::Conv_1055[FLOAT, 42x42x1x1]
%onnx::Conv_1058[FLOAT, 43x128x1x1]
%onnx::Conv_1061[FLOAT, 43x43x1x1]
%onnx::Conv_1064[FLOAT, 43x43x3x3]
%onnx::Conv_1067[FLOAT, 43x43x1x1]
%onnx::Conv_1070[FLOAT, 42x128x1x1]
%onnx::Conv_1073[FLOAT, 42x42x3x3]
%onnx::Conv_1076[FLOAT, 42x42x1x1]
%onnx::Conv_1079[FLOAT, 86x128x1x1]
%onnx::Conv_1080[FLOAT, 86]
%onnx::Conv_1082[FLOAT, 86x86x1x1]
%onnx::Conv_1085[FLOAT, 86x86x3x3]
%onnx::Conv_1088[FLOAT, 85x85x1x1]
%onnx::Conv_1089[FLOAT, 85]
%onnx::Conv_1091[FLOAT, 85x128x1x1]
%onnx::Conv_1094[FLOAT, 85x85x3x3]
%onnx::Conv_1097[FLOAT, 85x85x1x1]
%onnx::Conv_1100[FLOAT, 86x256x1x1]
%onnx::Conv_1103[FLOAT, 86x86x1x1]
%onnx::Conv_1106[FLOAT, 86x86x3x3]
%onnx::Conv_1109[FLOAT, 85x85x1x1]
%onnx::Conv_1112[FLOAT, 85x256x1x1]
%onnx::Conv_1115[FLOAT, 85x85x3x3]
%onnx::Conv_1118[FLOAT, 85x85x1x1]
%onnx::Conv_1121[FLOAT, 86x256x1x1]
%onnx::Conv_1124[FLOAT, 86x86x1x1]
%onnx::Conv_1127[FLOAT, 86x86x3x3]
%onnx::Conv_1130[FLOAT, 85x85x1x1]
%onnx::Conv_1133[FLOAT, 85x256x1x1]
%onnx::Conv_1136[FLOAT, 85x85x3x3]
%onnx::Conv_1139[FLOAT, 85x85x1x1]
%onnx::Conv_1142[FLOAT, 171x256x1x1]
%onnx::Conv_1143[FLOAT, 171]
%onnx::Conv_1145[FLOAT, 171x171x1x1]
%onnx::Conv_1148[FLOAT, 171x171x3x3]
%onnx::Conv_1151[FLOAT, 171x171x1x1]
%onnx::Conv_1154[FLOAT, 170x256x1x1]
%onnx::Conv_1155[FLOAT, 170]
%onnx::Conv_1157[FLOAT, 170x170x3x3]
%onnx::Conv_1160[FLOAT, 170x170x1x1]
%onnx::Conv_1163[FLOAT, 171x512x1x1]
%onnx::Conv_1166[FLOAT, 171x171x1x1]
%onnx::Conv_1169[FLOAT, 171x171x3x3]
%onnx::Conv_1172[FLOAT, 171x171x1x1]
%onnx::Conv_1175[FLOAT, 170x512x1x1]
%onnx::Conv_1178[FLOAT, 170x170x3x3]
%onnx::Conv_1181[FLOAT, 170x170x1x1]
%onnx::Conv_1184[FLOAT, 171x512x1x1]
%onnx::Conv_1187[FLOAT, 171x171x1x1]
%onnx::Conv_1190[FLOAT, 171x171x3x3]
%onnx::Conv_1193[FLOAT, 171x171x1x1]
%onnx::Conv_1196[FLOAT, 170x512x1x1]
%onnx::Conv_1199[FLOAT, 170x170x3x3]
%onnx::Conv_1202[FLOAT, 170x170x1x1]
) {
%onnx::Conv_1203 = Identity(%onnx::Conv_1155)
%onnx::Conv_1200 = Identity(%onnx::Conv_1155)
%onnx::Conv_1197 = Identity(%onnx::Conv_1155)
%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_1155)
%onnx::Conv_1179 = Identity(%onnx::Conv_1155)
%onnx::Conv_1176 = Identity(%onnx::Conv_1155)
%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_1161 = Identity(%onnx::Conv_1155)
%onnx::Conv_1158 = Identity(%onnx::Conv_1155)
%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_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_1080)
%onnx::Conv_1125 = Identity(%onnx::Conv_1080)
%onnx::Conv_1122 = Identity(%onnx::Conv_1080)
%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_1080)
%onnx::Conv_1104 = Identity(%onnx::Conv_1080)
%onnx::Conv_1101 = Identity(%onnx::Conv_1080)
%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_1080)
%onnx::Conv_1083 = Identity(%onnx::Conv_1080)
%onnx::Conv_1077 = Identity(%onnx::Conv_1029)
%onnx::Conv_1074 = Identity(%onnx::Conv_1029)
%onnx::Conv_1071 = Identity(%onnx::Conv_1029)
%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_1029)
%onnx::Conv_1053 = Identity(%onnx::Conv_1029)
%onnx::Conv_1050 = Identity(%onnx::Conv_1029)
%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_1029)
%onnx::Conv_1032 = Identity(%onnx::Conv_1029)
%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/conv1x1/conv_bn_relu/conv_bn_relu.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_1019, %onnx::Conv_1020)
%/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_1022, %onnx::Conv_1023)
%/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_1025, %onnx::Conv_1026)
%/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_1028, %onnx::Conv_1029)
%/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/input_op.4/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_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/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_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/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_1034, %onnx::Conv_1035)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1040, %onnx::Conv_1041)
%/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_1043, %onnx::Conv_1044)
%/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_1046, %onnx::Conv_1047)
%/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_1049, %onnx::Conv_1050)
%/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/input_op.4/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_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/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_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/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_1055, %onnx::Conv_1056)
%/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_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/conv1x1/conv_bn_relu/conv_bn_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_1061, %onnx::Conv_1062)
%/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_1064, %onnx::Conv_1065)
%/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_1067, %onnx::Conv_1068)
%/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_1070, %onnx::Conv_1071)
%/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/input_op.4/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_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/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_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/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_1076, %onnx::Conv_1077)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1082, %onnx::Conv_1083)
%/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_1085, %onnx::Conv_1086)
%/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_1088, %onnx::Conv_1089)
%/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_1091, %onnx::Conv_1092)
%/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/input_op.4/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_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_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_1097, %onnx::Conv_1098)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1103, %onnx::Conv_1104)
%/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_1106, %onnx::Conv_1107)
%/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_1109, %onnx::Conv_1110)
%/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_1112, %onnx::Conv_1113)
%/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/input_op.4/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_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_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_1118, %onnx::Conv_1119)
%/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_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/conv1x1/conv_bn_relu/conv_bn_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_1124, %onnx::Conv_1125)
%/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_1127, %onnx::Conv_1128)
%/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_1130, %onnx::Conv_1131)
%/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_1133, %onnx::Conv_1134)
%/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/input_op.4/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_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_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_1139, %onnx::Conv_1140)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1145, %onnx::Conv_1146)
%/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_1148, %onnx::Conv_1149)
%/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_1151, %onnx::Conv_1152)
%/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_1154, %onnx::Conv_1155)
%/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/input_op.4/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_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/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_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/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_1160, %onnx::Conv_1161)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1166, %onnx::Conv_1167)
%/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_1169, %onnx::Conv_1170)
%/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_1172, %onnx::Conv_1173)
%/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_1175, %onnx::Conv_1176)
%/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/input_op.4/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_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/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_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/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_1181, %onnx::Conv_1182)
%/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_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/conv1x1/conv_bn_relu/conv_bn_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_1187, %onnx::Conv_1188)
%/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_1190, %onnx::Conv_1191)
%/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_1193, %onnx::Conv_1194)
%/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_1196, %onnx::Conv_1197)
%/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/input_op.4/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_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/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_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/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_1202, %onnx::Conv_1203)
%/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)
%1011 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %1011
}
|
val_accuracy
| 92.608172
| 903,227,008
| 3,006,137
|
{'zcp_epe_nas': 111.65553126554731, 'zcp_fisher': 52.44292068481445, 'zcp_flops': 14451632128.0, 'zcp_grad_norm': 145.7139892578125, 'zcp_grasp': 29.13916015625, 'zcp_jacov': -16.061570687783313, 'zcp_l2_norm': 1006.1624755859375, 'zcp_nwot': 220.9535671253597, 'zcp_params': 3006137.0, 'zcp_plain': 0.05754850432276701, 'zcp_snip': 653.2103271484375, 'zcp_synflow': 121.8770829674315, 'zcp_zen': 94.85254669189453, 'zcp_val_accuracy': 0.935096144676208}
| |
NASBench101_279248
|
NASBench101
|
279248
|
a905464fcc0e5860d2775a8c161968b1
|
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, 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, 128x128x1x1]
%onnx::Conv_686[FLOAT, 128x128x1x1]
%onnx::Conv_689[FLOAT, 128x128x1x1]
%onnx::Conv_692[FLOAT, 256x128x1x1]
%onnx::Conv_693[FLOAT, 256]
%onnx::Conv_695[FLOAT, 256x256x1x1]
%onnx::Conv_698[FLOAT, 256x256x1x1]
%onnx::Conv_701[FLOAT, 256x128x1x1]
%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, 256x256x1x1]
%onnx::Conv_722[FLOAT, 256x256x1x1]
%onnx::Conv_725[FLOAT, 256x256x1x1]
%onnx::Conv_728[FLOAT, 512x256x1x1]
%onnx::Conv_729[FLOAT, 512]
%onnx::Conv_731[FLOAT, 512x512x1x1]
%onnx::Conv_734[FLOAT, 512x512x1x1]
%onnx::Conv_737[FLOAT, 512x256x1x1]
%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_755[FLOAT, 512x512x1x1]
%onnx::Conv_758[FLOAT, 512x512x1x1]
%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/conv1x1/conv_bn_relu/conv_bn_relu.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/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_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_1_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.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_662, %onnx::Conv_663)
%/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_665, %onnx::Conv_666)
%/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/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_4_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/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_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_1_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.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_674, %onnx::Conv_675)
%/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_4_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/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/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_4_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/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_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_1_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.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_686, %onnx::Conv_687)
%/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_4_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/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/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_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_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/Add_1_output_0 = Add(%/layers.5/vertex_op.1/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_1_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.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_698, %onnx::Conv_699)
%/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_701, %onnx::Conv_702)
%/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/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_4_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/Add_1_output_0 = Add(%/layers.6/vertex_op.1/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_1_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.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_710, %onnx::Conv_711)
%/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_4_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/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/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_4_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/Add_1_output_0 = Add(%/layers.7/vertex_op.1/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_1_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.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_722, %onnx::Conv_723)
%/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_4_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/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/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_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_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/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_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_1_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.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_734, %onnx::Conv_735)
%/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_737, %onnx::Conv_738)
%/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/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_4_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/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_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_1_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.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_746, %onnx::Conv_747)
%/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_4_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/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/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_4_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/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_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_1_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.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_758, %onnx::Conv_759)
%/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_4_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/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/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_4_output_0)
%651 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %651
}
|
val_accuracy
| 90.905446
| 1,171,007,488
| 3,831,434
|
{'zcp_epe_nas': 142.02796642682165, 'zcp_fisher': 4.941379070281982, 'zcp_flops': 18736119808.0, 'zcp_grad_norm': 45.62977600097656, 'zcp_grasp': -0.41328430175781206, 'zcp_jacov': -16.053949693246725, 'zcp_l2_norm': 817.843017578125, 'zcp_nwot': 228.64521815134924, 'zcp_params': 3831434.0, 'zcp_plain': 0.010875087231397, 'zcp_snip': 349.53973388671875, 'zcp_synflow': 84.6572018195571, 'zcp_zen': 73.01097869873047, 'zcp_val_accuracy': 0.9324919581413261}
| |
NASBench101_399068
|
NASBench101
|
399068
|
f13645d002f74ae6a9b6abc16e288cae
|
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, 64x128x1x1]
%onnx::Conv_680[FLOAT, 64x64x3x3]
%onnx::Conv_683[FLOAT, 64x64x3x3]
%onnx::Conv_686[FLOAT, 64x128x1x1]
%onnx::Conv_689[FLOAT, 64x128x1x1]
%onnx::Conv_692[FLOAT, 64x64x3x3]
%onnx::Conv_695[FLOAT, 64x64x3x3]
%onnx::Conv_698[FLOAT, 64x128x1x1]
%onnx::Conv_701[FLOAT, 64x128x1x1]
%onnx::Conv_704[FLOAT, 64x64x3x3]
%onnx::Conv_707[FLOAT, 64x64x3x3]
%onnx::Conv_710[FLOAT, 128x128x1x1]
%onnx::Conv_713[FLOAT, 128x128x1x1]
%onnx::Conv_716[FLOAT, 128x128x3x3]
%onnx::Conv_719[FLOAT, 128x128x3x3]
%onnx::Conv_722[FLOAT, 128x256x1x1]
%onnx::Conv_725[FLOAT, 128x256x1x1]
%onnx::Conv_728[FLOAT, 128x128x3x3]
%onnx::Conv_731[FLOAT, 128x128x3x3]
%onnx::Conv_734[FLOAT, 128x256x1x1]
%onnx::Conv_737[FLOAT, 128x256x1x1]
%onnx::Conv_740[FLOAT, 128x128x3x3]
%onnx::Conv_743[FLOAT, 128x128x3x3]
%onnx::Conv_746[FLOAT, 256x256x1x1]
%onnx::Conv_747[FLOAT, 256]
%onnx::Conv_749[FLOAT, 256x256x1x1]
%onnx::Conv_752[FLOAT, 256x256x3x3]
%onnx::Conv_755[FLOAT, 256x256x3x3]
%onnx::Conv_758[FLOAT, 256x512x1x1]
%onnx::Conv_761[FLOAT, 256x512x1x1]
%onnx::Conv_764[FLOAT, 256x256x3x3]
%onnx::Conv_767[FLOAT, 256x256x3x3]
%onnx::Conv_770[FLOAT, 256x512x1x1]
%onnx::Conv_773[FLOAT, 256x512x1x1]
%onnx::Conv_776[FLOAT, 256x256x3x3]
%onnx::Conv_779[FLOAT, 256x256x3x3]
) {
%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/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_677, %onnx::Conv_678)
%/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_680, %onnx::Conv_681)
%/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 = <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/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/conv3x3/conv_bn_relu/conv_bn_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_683, %onnx::Conv_684)
%/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/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.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_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/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_689, %onnx::Conv_690)
%/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_692, %onnx::Conv_693)
%/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 = <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/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/conv3x3/conv_bn_relu/conv_bn_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_695, %onnx::Conv_696)
%/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/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.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_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/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_701, %onnx::Conv_702)
%/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_704, %onnx::Conv_705)
%/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 = <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/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/conv3x3/conv_bn_relu/conv_bn_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_707, %onnx::Conv_708)
%/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/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.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_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/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_713, %onnx::Conv_714)
%/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/conv3x3/conv_bn_relu/conv_bn_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_716, %onnx::Conv_717)
%/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/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/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.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_719, %onnx::Conv_720)
%/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/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.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_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/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/Concat_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/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/conv3x3/conv_bn_relu/conv_bn_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_728, %onnx::Conv_729)
%/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/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/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.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_731, %onnx::Conv_732)
%/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/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.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_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/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/Concat_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/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/conv3x3/conv_bn_relu/conv_bn_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_740, %onnx::Conv_741)
%/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/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/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.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_743, %onnx::Conv_744)
%/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/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.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_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/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_749, %onnx::Conv_750)
%/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_752, %onnx::Conv_753)
%/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 = <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/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/conv3x3/conv_bn_relu/conv_bn_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_755, %onnx::Conv_756)
%/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/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.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_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/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_761, %onnx::Conv_762)
%/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_764, %onnx::Conv_765)
%/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 = <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/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/conv3x3/conv_bn_relu/conv_bn_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_767, %onnx::Conv_768)
%/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/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.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_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/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_773, %onnx::Conv_774)
%/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_776, %onnx::Conv_777)
%/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 = <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/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/conv3x3/conv_bn_relu/conv_bn_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_779, %onnx::Conv_780)
%/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/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.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)
%669 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %669
}
|
val_accuracy
| 90.404648
| 1,646,536,704
| 5,532,810
|
{'zcp_epe_nas': 98.71137714763269, 'zcp_fisher': 30.606002807617188, 'zcp_flops': 26344587264.0, 'zcp_grad_norm': 87.19548797607422, 'zcp_grasp': -7.74713134765625, 'zcp_jacov': -16.049317069769867, 'zcp_l2_norm': 695.7271118164062, 'zcp_nwot': 217.4697598878357, 'zcp_params': 5532810.0, 'zcp_plain': 0.053926363587379005, 'zcp_snip': 554.9628295898438, 'zcp_synflow': 106.48504233482875, 'zcp_zen': 82.109619140625, 'zcp_val_accuracy': 0.8646835088729851}
| |
NASBench101_119301
|
NASBench101
|
119301
|
480a4f21c393746746c126a75c248ca2
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_617[FLOAT, 128x3x3x3]
%onnx::Conv_618[FLOAT, 128]
%onnx::Conv_620[FLOAT, 64x128x1x1]
%onnx::Conv_621[FLOAT, 64]
%onnx::Conv_623[FLOAT, 64x128x1x1]
%onnx::Conv_626[FLOAT, 64x64x3x3]
%onnx::Conv_629[FLOAT, 64x64x1x1]
%onnx::Conv_632[FLOAT, 64x128x1x1]
%onnx::Conv_635[FLOAT, 64x128x1x1]
%onnx::Conv_638[FLOAT, 64x64x3x3]
%onnx::Conv_641[FLOAT, 64x64x1x1]
%onnx::Conv_644[FLOAT, 64x128x1x1]
%onnx::Conv_647[FLOAT, 64x128x1x1]
%onnx::Conv_650[FLOAT, 64x64x3x3]
%onnx::Conv_653[FLOAT, 64x64x1x1]
%onnx::Conv_656[FLOAT, 128x128x1x1]
%onnx::Conv_659[FLOAT, 128x128x1x1]
%onnx::Conv_662[FLOAT, 128x128x3x3]
%onnx::Conv_665[FLOAT, 128x128x1x1]
%onnx::Conv_668[FLOAT, 128x256x1x1]
%onnx::Conv_671[FLOAT, 128x256x1x1]
%onnx::Conv_674[FLOAT, 128x128x3x3]
%onnx::Conv_677[FLOAT, 128x128x1x1]
%onnx::Conv_680[FLOAT, 128x256x1x1]
%onnx::Conv_683[FLOAT, 128x256x1x1]
%onnx::Conv_686[FLOAT, 128x128x3x3]
%onnx::Conv_689[FLOAT, 128x128x1x1]
%onnx::Conv_692[FLOAT, 256x256x1x1]
%onnx::Conv_693[FLOAT, 256]
%onnx::Conv_695[FLOAT, 256x256x1x1]
%onnx::Conv_698[FLOAT, 256x256x3x3]
%onnx::Conv_701[FLOAT, 256x256x1x1]
%onnx::Conv_704[FLOAT, 256x512x1x1]
%onnx::Conv_707[FLOAT, 256x512x1x1]
%onnx::Conv_710[FLOAT, 256x256x3x3]
%onnx::Conv_713[FLOAT, 256x256x1x1]
%onnx::Conv_716[FLOAT, 256x512x1x1]
%onnx::Conv_719[FLOAT, 256x512x1x1]
%onnx::Conv_722[FLOAT, 256x256x3x3]
%onnx::Conv_725[FLOAT, 256x256x1x1]
) {
%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_618)
%onnx::Conv_687 = Identity(%onnx::Conv_618)
%onnx::Conv_684 = Identity(%onnx::Conv_618)
%onnx::Conv_681 = Identity(%onnx::Conv_618)
%onnx::Conv_678 = Identity(%onnx::Conv_618)
%onnx::Conv_675 = Identity(%onnx::Conv_618)
%onnx::Conv_672 = Identity(%onnx::Conv_618)
%onnx::Conv_669 = Identity(%onnx::Conv_618)
%onnx::Conv_666 = Identity(%onnx::Conv_618)
%onnx::Conv_663 = Identity(%onnx::Conv_618)
%onnx::Conv_660 = Identity(%onnx::Conv_618)
%onnx::Conv_657 = Identity(%onnx::Conv_618)
%onnx::Conv_654 = Identity(%onnx::Conv_621)
%onnx::Conv_651 = Identity(%onnx::Conv_621)
%onnx::Conv_648 = Identity(%onnx::Conv_621)
%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)
%/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_617, %onnx::Conv_618)
%/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_620, %onnx::Conv_621)
%/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_623, %onnx::Conv_624)
%/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/maxpool/MaxPool_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/conv3x3/conv_bn_relu/conv_bn_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_626, %onnx::Conv_627)
%/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_3_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/conv1x1/conv_bn_relu/conv_bn_relu.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_629, %onnx::Conv_630)
%/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.3/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_632, %onnx::Conv_633)
%/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_635, %onnx::Conv_636)
%/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/maxpool/MaxPool_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/conv3x3/conv_bn_relu/conv_bn_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_638, %onnx::Conv_639)
%/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_3_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/conv1x1/conv_bn_relu/conv_bn_relu.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_641, %onnx::Conv_642)
%/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.3/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_644, %onnx::Conv_645)
%/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_647, %onnx::Conv_648)
%/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/maxpool/MaxPool_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/conv3x3/conv_bn_relu/conv_bn_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_650, %onnx::Conv_651)
%/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_3_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/conv1x1/conv_bn_relu/conv_bn_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_653, %onnx::Conv_654)
%/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.3/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_656, %onnx::Conv_657)
%/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_659, %onnx::Conv_660)
%/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/maxpool/MaxPool_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/conv3x3/conv_bn_relu/conv_bn_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_662, %onnx::Conv_663)
%/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_3_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/conv1x1/conv_bn_relu/conv_bn_relu.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_665, %onnx::Conv_666)
%/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.3/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_668, %onnx::Conv_669)
%/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_671, %onnx::Conv_672)
%/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/maxpool/MaxPool_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/conv3x3/conv_bn_relu/conv_bn_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_674, %onnx::Conv_675)
%/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_3_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/conv1x1/conv_bn_relu/conv_bn_relu.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_677, %onnx::Conv_678)
%/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.3/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_680, %onnx::Conv_681)
%/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_683, %onnx::Conv_684)
%/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/maxpool/MaxPool_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/conv3x3/conv_bn_relu/conv_bn_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_686, %onnx::Conv_687)
%/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_3_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/conv1x1/conv_bn_relu/conv_bn_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_689, %onnx::Conv_690)
%/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.3/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_692, %onnx::Conv_693)
%/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_695, %onnx::Conv_696)
%/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/maxpool/MaxPool_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/conv3x3/conv_bn_relu/conv_bn_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_698, %onnx::Conv_699)
%/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_3_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/conv1x1/conv_bn_relu/conv_bn_relu.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_701, %onnx::Conv_702)
%/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.3/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_704, %onnx::Conv_705)
%/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_707, %onnx::Conv_708)
%/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/maxpool/MaxPool_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/conv3x3/conv_bn_relu/conv_bn_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_710, %onnx::Conv_711)
%/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_3_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/conv1x1/conv_bn_relu/conv_bn_relu.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_713, %onnx::Conv_714)
%/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.3/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_716, %onnx::Conv_717)
%/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_719, %onnx::Conv_720)
%/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/maxpool/MaxPool_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/conv3x3/conv_bn_relu/conv_bn_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_722, %onnx::Conv_723)
%/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_3_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/conv1x1/conv_bn_relu/conv_bn_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_725, %onnx::Conv_726)
%/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.3/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)
%615 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %615
}
|
val_accuracy
| 91.175884
| 1,042,556,928
| 3,468,426
|
{'zcp_epe_nas': 63.96472660679823, 'zcp_fisher': 4.089583396911621, 'zcp_flops': 16680910848.0, 'zcp_grad_norm': 33.276859283447266, 'zcp_grasp': -0.44438934326171803, 'zcp_jacov': -16.04966936405296, 'zcp_l2_norm': 694.5416259765625, 'zcp_nwot': 217.85460404480335, 'zcp_params': 3468426.0, 'zcp_plain': -0.0022867457009850003, 'zcp_snip': 218.31777954101562, 'zcp_synflow': 94.62338003470103, 'zcp_zen': 74.23592376708984, 'zcp_val_accuracy': 0.927584111690521}
| |
NASBench101_211560
|
NASBench101
|
211560
|
8022cc8d8256eb19e9a019105b99bf3d
|
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, 128x128x3x3]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 128x128x1x1]
%onnx::Conv_818[FLOAT, 128x128x1x1]
%onnx::Conv_821[FLOAT, 128x128x1x1]
%onnx::Conv_824[FLOAT, 128x128x3x3]
%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, 128x128x1x1]
%onnx::Conv_845[FLOAT, 256x128x1x1]
%onnx::Conv_846[FLOAT, 256]
%onnx::Conv_848[FLOAT, 256x256x1x1]
%onnx::Conv_851[FLOAT, 256x128x1x1]
%onnx::Conv_854[FLOAT, 256x256x3x3]
%onnx::Conv_857[FLOAT, 256x256x1x1]
%onnx::Conv_860[FLOAT, 256x256x1x1]
%onnx::Conv_863[FLOAT, 256x256x1x1]
%onnx::Conv_866[FLOAT, 256x256x1x1]
%onnx::Conv_869[FLOAT, 256x256x3x3]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_875[FLOAT, 256x256x1x1]
%onnx::Conv_878[FLOAT, 256x256x1x1]
%onnx::Conv_881[FLOAT, 256x256x1x1]
%onnx::Conv_884[FLOAT, 256x256x3x3]
%onnx::Conv_887[FLOAT, 256x256x1x1]
%onnx::Conv_890[FLOAT, 512x256x1x1]
%onnx::Conv_891[FLOAT, 512]
%onnx::Conv_893[FLOAT, 512x512x1x1]
%onnx::Conv_896[FLOAT, 512x256x1x1]
%onnx::Conv_899[FLOAT, 512x512x3x3]
%onnx::Conv_902[FLOAT, 512x512x1x1]
%onnx::Conv_905[FLOAT, 512x512x1x1]
%onnx::Conv_908[FLOAT, 512x512x1x1]
%onnx::Conv_911[FLOAT, 512x512x1x1]
%onnx::Conv_914[FLOAT, 512x512x3x3]
%onnx::Conv_917[FLOAT, 512x512x1x1]
%onnx::Conv_920[FLOAT, 512x512x1x1]
%onnx::Conv_923[FLOAT, 512x512x1x1]
%onnx::Conv_926[FLOAT, 512x512x1x1]
%onnx::Conv_929[FLOAT, 512x512x3x3]
%onnx::Conv_932[FLOAT, 512x512x1x1]
) {
%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/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/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_809, %onnx::Conv_810)
%/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_812, %onnx::Conv_813)
%/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.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.2/maxpool/MaxPool_output_0)
%/layers.1/Add_7_output_0 = Add(%/layers.1/Add_6_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_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/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/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_824, %onnx::Conv_825)
%/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_827, %onnx::Conv_828)
%/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.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.2/maxpool/MaxPool_output_0)
%/layers.2/Add_7_output_0 = Add(%/layers.2/Add_6_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_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/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/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_839, %onnx::Conv_840)
%/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_842, %onnx::Conv_843)
%/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.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.2/maxpool/MaxPool_output_0)
%/layers.3/Add_7_output_0 = Add(%/layers.3/Add_6_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_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/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/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_854, %onnx::Conv_855)
%/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_857, %onnx::Conv_858)
%/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.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.2/maxpool/MaxPool_output_0)
%/layers.5/Add_7_output_0 = Add(%/layers.5/Add_6_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_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/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/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_869, %onnx::Conv_870)
%/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_872, %onnx::Conv_873)
%/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.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.2/maxpool/MaxPool_output_0)
%/layers.6/Add_7_output_0 = Add(%/layers.6/Add_6_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_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/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/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_884, %onnx::Conv_885)
%/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_887, %onnx::Conv_888)
%/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.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.2/maxpool/MaxPool_output_0)
%/layers.7/Add_7_output_0 = Add(%/layers.7/Add_6_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_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/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/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_899, %onnx::Conv_900)
%/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_902, %onnx::Conv_903)
%/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.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.2/maxpool/MaxPool_output_0)
%/layers.9/Add_7_output_0 = Add(%/layers.9/Add_6_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_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/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/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_914, %onnx::Conv_915)
%/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_917, %onnx::Conv_918)
%/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.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.2/maxpool/MaxPool_output_0)
%/layers.10/Add_7_output_0 = Add(%/layers.10/Add_6_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_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/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/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_929, %onnx::Conv_930)
%/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_932, %onnx::Conv_933)
%/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.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.2/maxpool/MaxPool_output_0)
%/layers.11/Add_7_output_0 = Add(%/layers.11/Add_6_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_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
| 9.505209
| 3,894,421,504
| 13,126,538
|
{'zcp_epe_nas': 81.2573171476806, 'zcp_fisher': 231.79129028320312, 'zcp_flops': 62310744064.0, 'zcp_grad_norm': 305.51519775390625, 'zcp_grasp': -359.46875, 'zcp_jacov': -16.050894828005134, 'zcp_l2_norm': 1029.7779541015625, 'zcp_nwot': 232.65940385124483, 'zcp_params': 13126538.0, 'zcp_plain': 0.338708966970443, 'zcp_snip': 2411.4423828125, 'zcp_synflow': 119.90281834320398, 'zcp_zen': 96.11467742919922, 'zcp_val_accuracy': 0.927383840084075}
| |
NASBench101_259979
|
NASBench101
|
259979
|
9d7066dc5c8468260a4c317f9fa80f3b
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_740[FLOAT, 128x3x3x3]
%onnx::Conv_741[FLOAT, 128]
%onnx::Conv_743[FLOAT, 43x128x1x1]
%onnx::Conv_744[FLOAT, 43]
%onnx::Conv_746[FLOAT, 43x43x1x1]
%onnx::Conv_749[FLOAT, 43x43x3x3]
%onnx::Conv_752[FLOAT, 43x43x3x3]
%onnx::Conv_755[FLOAT, 43x128x1x1]
%onnx::Conv_758[FLOAT, 43x43x1x1]
%onnx::Conv_761[FLOAT, 43x43x3x3]
%onnx::Conv_764[FLOAT, 43x43x3x3]
%onnx::Conv_767[FLOAT, 43x128x1x1]
%onnx::Conv_770[FLOAT, 43x43x1x1]
%onnx::Conv_773[FLOAT, 43x43x3x3]
%onnx::Conv_776[FLOAT, 43x43x3x3]
%onnx::Conv_779[FLOAT, 86x128x1x1]
%onnx::Conv_780[FLOAT, 86]
%onnx::Conv_782[FLOAT, 86x86x1x1]
%onnx::Conv_785[FLOAT, 86x86x3x3]
%onnx::Conv_788[FLOAT, 86x86x3x3]
%onnx::Conv_791[FLOAT, 86x256x1x1]
%onnx::Conv_794[FLOAT, 86x86x1x1]
%onnx::Conv_797[FLOAT, 86x86x3x3]
%onnx::Conv_800[FLOAT, 86x86x3x3]
%onnx::Conv_803[FLOAT, 86x256x1x1]
%onnx::Conv_806[FLOAT, 86x86x1x1]
%onnx::Conv_809[FLOAT, 86x86x3x3]
%onnx::Conv_812[FLOAT, 86x86x3x3]
%onnx::Conv_815[FLOAT, 171x256x1x1]
%onnx::Conv_816[FLOAT, 171]
%onnx::Conv_818[FLOAT, 171x171x1x1]
%onnx::Conv_821[FLOAT, 171x171x3x3]
%onnx::Conv_824[FLOAT, 171x171x3x3]
%onnx::Conv_827[FLOAT, 171x512x1x1]
%onnx::Conv_830[FLOAT, 171x171x1x1]
%onnx::Conv_833[FLOAT, 171x171x3x3]
%onnx::Conv_836[FLOAT, 171x171x3x3]
%onnx::Conv_839[FLOAT, 171x512x1x1]
%onnx::Conv_842[FLOAT, 171x171x1x1]
%onnx::Conv_845[FLOAT, 171x171x3x3]
%onnx::Conv_848[FLOAT, 171x171x3x3]
) {
%onnx::Conv_849 = Identity(%onnx::Conv_816)
%onnx::Conv_846 = Identity(%onnx::Conv_816)
%onnx::Conv_843 = Identity(%onnx::Conv_816)
%onnx::Conv_840 = Identity(%onnx::Conv_816)
%onnx::Conv_837 = Identity(%onnx::Conv_816)
%onnx::Conv_834 = Identity(%onnx::Conv_816)
%onnx::Conv_831 = Identity(%onnx::Conv_816)
%onnx::Conv_828 = Identity(%onnx::Conv_816)
%onnx::Conv_825 = Identity(%onnx::Conv_816)
%onnx::Conv_822 = Identity(%onnx::Conv_816)
%onnx::Conv_819 = Identity(%onnx::Conv_816)
%onnx::Conv_813 = Identity(%onnx::Conv_780)
%onnx::Conv_810 = Identity(%onnx::Conv_780)
%onnx::Conv_807 = Identity(%onnx::Conv_780)
%onnx::Conv_804 = Identity(%onnx::Conv_780)
%onnx::Conv_801 = Identity(%onnx::Conv_780)
%onnx::Conv_798 = Identity(%onnx::Conv_780)
%onnx::Conv_795 = Identity(%onnx::Conv_780)
%onnx::Conv_792 = Identity(%onnx::Conv_780)
%onnx::Conv_789 = Identity(%onnx::Conv_780)
%onnx::Conv_786 = Identity(%onnx::Conv_780)
%onnx::Conv_783 = Identity(%onnx::Conv_780)
%onnx::Conv_777 = Identity(%onnx::Conv_744)
%onnx::Conv_774 = Identity(%onnx::Conv_744)
%onnx::Conv_771 = Identity(%onnx::Conv_744)
%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)
%/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_740, %onnx::Conv_741)
%/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_743, %onnx::Conv_744)
%/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_746, %onnx::Conv_747)
%/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_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/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_752, %onnx::Conv_753)
%/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 = <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_4_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_4_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/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_755, %onnx::Conv_756)
%/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_758, %onnx::Conv_759)
%/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_761, %onnx::Conv_762)
%/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_764, %onnx::Conv_765)
%/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 = <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_4_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_4_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/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_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/conv1x1/conv_bn_relu/conv_bn_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_770, %onnx::Conv_771)
%/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_773, %onnx::Conv_774)
%/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_776, %onnx::Conv_777)
%/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 = <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_4_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_4_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/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_779, %onnx::Conv_780)
%/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_782, %onnx::Conv_783)
%/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_785, %onnx::Conv_786)
%/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_788, %onnx::Conv_789)
%/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 = <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/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/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_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/conv3x3/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/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.3/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/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_791, %onnx::Conv_792)
%/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_794, %onnx::Conv_795)
%/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_797, %onnx::Conv_798)
%/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_800, %onnx::Conv_801)
%/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 = <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/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/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_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/conv3x3/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/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.3/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/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_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/conv1x1/conv_bn_relu/conv_bn_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_806, %onnx::Conv_807)
%/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_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/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_812, %onnx::Conv_813)
%/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 = <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/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/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_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/conv3x3/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/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.3/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/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_815, %onnx::Conv_816)
%/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_818, %onnx::Conv_819)
%/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_821, %onnx::Conv_822)
%/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_824, %onnx::Conv_825)
%/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 = <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_4_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_4_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/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_827, %onnx::Conv_828)
%/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_830, %onnx::Conv_831)
%/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_833, %onnx::Conv_834)
%/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_836, %onnx::Conv_837)
%/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 = <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_4_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_4_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/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_839, %onnx::Conv_840)
%/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_842, %onnx::Conv_843)
%/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_845, %onnx::Conv_846)
%/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_848, %onnx::Conv_849)
%/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 = <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_4_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_4_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/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%738 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %738
}
|
val_accuracy
| 87.890625
| 750,573,696
| 2,500,176
|
{'zcp_epe_nas': 108.09383500103672, 'zcp_fisher': 2572.583740234375, 'zcp_flops': 12009179136.0, 'zcp_grad_norm': 894.2652587890625, 'zcp_grasp': 1931.234375, 'zcp_jacov': -16.060092518652574, 'zcp_l2_norm': 567.4613647460938, 'zcp_nwot': 212.70268159043604, 'zcp_params': 2500176.0, 'zcp_plain': 0.007841853424906, 'zcp_snip': 3725.4658203125, 'zcp_synflow': 119.72933684504687, 'zcp_zen': 65.02940368652344, 'zcp_val_accuracy': 0.911959111690521}
| |
NASBench101_75054
|
NASBench101
|
75054
|
2d7f39e49ba637d6ece88f3c2b0c825d
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_866[FLOAT, 128x3x3x3]
%onnx::Conv_867[FLOAT, 128]
%onnx::Conv_869[FLOAT, 43x128x1x1]
%onnx::Conv_870[FLOAT, 43]
%onnx::Conv_872[FLOAT, 43x43x3x3]
%onnx::Conv_875[FLOAT, 43x43x3x3]
%onnx::Conv_878[FLOAT, 42x42x3x3]
%onnx::Conv_879[FLOAT, 42]
%onnx::Conv_881[FLOAT, 42x42x3x3]
%onnx::Conv_884[FLOAT, 43x128x1x1]
%onnx::Conv_887[FLOAT, 43x43x3x3]
%onnx::Conv_890[FLOAT, 43x43x3x3]
%onnx::Conv_893[FLOAT, 42x42x3x3]
%onnx::Conv_896[FLOAT, 42x42x3x3]
%onnx::Conv_899[FLOAT, 43x128x1x1]
%onnx::Conv_902[FLOAT, 43x43x3x3]
%onnx::Conv_905[FLOAT, 43x43x3x3]
%onnx::Conv_908[FLOAT, 42x42x3x3]
%onnx::Conv_911[FLOAT, 42x42x3x3]
%onnx::Conv_914[FLOAT, 86x128x1x1]
%onnx::Conv_915[FLOAT, 86]
%onnx::Conv_917[FLOAT, 86x86x3x3]
%onnx::Conv_920[FLOAT, 85x85x3x3]
%onnx::Conv_921[FLOAT, 85]
%onnx::Conv_923[FLOAT, 85x85x3x3]
%onnx::Conv_926[FLOAT, 85x85x3x3]
%onnx::Conv_929[FLOAT, 86x256x1x1]
%onnx::Conv_932[FLOAT, 86x86x3x3]
%onnx::Conv_935[FLOAT, 85x85x3x3]
%onnx::Conv_938[FLOAT, 85x85x3x3]
%onnx::Conv_941[FLOAT, 85x85x3x3]
%onnx::Conv_944[FLOAT, 86x256x1x1]
%onnx::Conv_947[FLOAT, 86x86x3x3]
%onnx::Conv_950[FLOAT, 85x85x3x3]
%onnx::Conv_953[FLOAT, 85x85x3x3]
%onnx::Conv_956[FLOAT, 85x85x3x3]
%onnx::Conv_959[FLOAT, 171x256x1x1]
%onnx::Conv_960[FLOAT, 171]
%onnx::Conv_962[FLOAT, 171x171x3x3]
%onnx::Conv_965[FLOAT, 171x171x3x3]
%onnx::Conv_968[FLOAT, 170x170x3x3]
%onnx::Conv_969[FLOAT, 170]
%onnx::Conv_971[FLOAT, 170x170x3x3]
%onnx::Conv_974[FLOAT, 171x512x1x1]
%onnx::Conv_977[FLOAT, 171x171x3x3]
%onnx::Conv_980[FLOAT, 171x171x3x3]
%onnx::Conv_983[FLOAT, 170x170x3x3]
%onnx::Conv_986[FLOAT, 170x170x3x3]
%onnx::Conv_989[FLOAT, 171x512x1x1]
%onnx::Conv_992[FLOAT, 171x171x3x3]
%onnx::Conv_995[FLOAT, 171x171x3x3]
%onnx::Conv_998[FLOAT, 170x170x3x3]
%onnx::Conv_1001[FLOAT, 170x170x3x3]
) {
%onnx::Conv_1002 = Identity(%onnx::Conv_969)
%onnx::Conv_999 = Identity(%onnx::Conv_969)
%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_969)
%onnx::Conv_984 = Identity(%onnx::Conv_969)
%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_969)
%onnx::Conv_966 = Identity(%onnx::Conv_960)
%onnx::Conv_963 = Identity(%onnx::Conv_960)
%onnx::Conv_957 = Identity(%onnx::Conv_921)
%onnx::Conv_954 = Identity(%onnx::Conv_921)
%onnx::Conv_951 = Identity(%onnx::Conv_921)
%onnx::Conv_948 = Identity(%onnx::Conv_915)
%onnx::Conv_945 = Identity(%onnx::Conv_915)
%onnx::Conv_942 = Identity(%onnx::Conv_921)
%onnx::Conv_939 = Identity(%onnx::Conv_921)
%onnx::Conv_936 = Identity(%onnx::Conv_921)
%onnx::Conv_933 = Identity(%onnx::Conv_915)
%onnx::Conv_930 = Identity(%onnx::Conv_915)
%onnx::Conv_927 = Identity(%onnx::Conv_921)
%onnx::Conv_924 = Identity(%onnx::Conv_921)
%onnx::Conv_918 = Identity(%onnx::Conv_915)
%onnx::Conv_912 = Identity(%onnx::Conv_879)
%onnx::Conv_909 = Identity(%onnx::Conv_879)
%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_879)
%onnx::Conv_894 = Identity(%onnx::Conv_879)
%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_879)
%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_866, %onnx::Conv_867)
%/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_869, %onnx::Conv_870)
%/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_872, %onnx::Conv_873)
%/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_875, %onnx::Conv_876)
%/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.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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_878, %onnx::Conv_879)
%/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_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/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_881, %onnx::Conv_882)
%/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.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_884, %onnx::Conv_885)
%/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_887, %onnx::Conv_888)
%/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_890, %onnx::Conv_891)
%/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.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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_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/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/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_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.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/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_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/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_905, %onnx::Conv_906)
%/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.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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_908, %onnx::Conv_909)
%/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_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/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_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.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_914, %onnx::Conv_915)
%/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_917, %onnx::Conv_918)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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.2/maxpool/MaxPool_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_1_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/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_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/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_926, %onnx::Conv_927)
%/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.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_929, %onnx::Conv_930)
%/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_932, %onnx::Conv_933)
%/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/conv3x3/conv_bn_relu/conv_bn_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_935, %onnx::Conv_936)
%/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 = <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.2/maxpool/MaxPool_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_1_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_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/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_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.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/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_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/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/conv3x3/conv_bn_relu/conv_bn_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_950, %onnx::Conv_951)
%/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 = <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.2/maxpool/MaxPool_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_1_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/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_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/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_956, %onnx::Conv_957)
%/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.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_959, %onnx::Conv_960)
%/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_962, %onnx::Conv_963)
%/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_965, %onnx::Conv_966)
%/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.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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_968, %onnx::Conv_969)
%/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_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/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_971, %onnx::Conv_972)
%/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.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_974, %onnx::Conv_975)
%/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_977, %onnx::Conv_978)
%/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_980, %onnx::Conv_981)
%/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.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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_983, %onnx::Conv_984)
%/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_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/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_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.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/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/conv3x3/conv_bn_relu/conv_bn_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_992, %onnx::Conv_993)
%/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_995, %onnx::Conv_996)
%/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.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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_998, %onnx::Conv_999)
%/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_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/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_1001, %onnx::Conv_1002)
%/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.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)
%864 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %864
}
|
val_accuracy
| 91.586536
| 1,310,635,776
| 4,427,865
|
{'zcp_epe_nas': 84.9134479372138, 'zcp_fisher': 50.42637252807617, 'zcp_flops': 20970172416.0, 'zcp_grad_norm': 137.08746337890625, 'zcp_grasp': 11.755615234375, 'zcp_jacov': -16.052830093352252, 'zcp_l2_norm': 687.8189697265625, 'zcp_nwot': 215.56256748021428, 'zcp_params': 4427865.0, 'zcp_plain': 0.08075501024723, 'zcp_snip': 667.359130859375, 'zcp_synflow': 119.9056536778084, 'zcp_zen': 96.20852661132812, 'zcp_val_accuracy': 0.883413434028625}
| |
NASBench101_26805
|
NASBench101
|
26805
|
1034b13a0d8796e8e439dd8fbb88ccef
|
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, 64x64x1x1]
%onnx::Conv_617[FLOAT, 64x64x1x1]
%onnx::Conv_620[FLOAT, 64x128x1x1]
%onnx::Conv_623[FLOAT, 64x64x1x1]
%onnx::Conv_626[FLOAT, 64x64x1x1]
%onnx::Conv_629[FLOAT, 64x128x1x1]
%onnx::Conv_632[FLOAT, 64x64x1x1]
%onnx::Conv_635[FLOAT, 64x64x1x1]
%onnx::Conv_638[FLOAT, 128x128x1x1]
%onnx::Conv_641[FLOAT, 128x128x1x1]
%onnx::Conv_644[FLOAT, 128x128x1x1]
%onnx::Conv_647[FLOAT, 128x256x1x1]
%onnx::Conv_650[FLOAT, 128x128x1x1]
%onnx::Conv_653[FLOAT, 128x128x1x1]
%onnx::Conv_656[FLOAT, 128x256x1x1]
%onnx::Conv_659[FLOAT, 128x128x1x1]
%onnx::Conv_662[FLOAT, 128x128x1x1]
%onnx::Conv_665[FLOAT, 256x256x1x1]
%onnx::Conv_666[FLOAT, 256]
%onnx::Conv_668[FLOAT, 256x256x1x1]
%onnx::Conv_671[FLOAT, 256x256x1x1]
%onnx::Conv_674[FLOAT, 256x512x1x1]
%onnx::Conv_677[FLOAT, 256x256x1x1]
%onnx::Conv_680[FLOAT, 256x256x1x1]
%onnx::Conv_683[FLOAT, 256x512x1x1]
%onnx::Conv_686[FLOAT, 256x256x1x1]
%onnx::Conv_689[FLOAT, 256x256x1x1]
) {
%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/conv1x1/conv_bn_relu/conv_bn_relu.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_614, %onnx::Conv_615)
%/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_617, %onnx::Conv_618)
%/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/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/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.3/maxpool/MaxPool_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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_623, %onnx::Conv_624)
%/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_626, %onnx::Conv_627)
%/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/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/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.3/maxpool/MaxPool_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/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_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/conv1x1/conv_bn_relu/conv_bn_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_632, %onnx::Conv_633)
%/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_635, %onnx::Conv_636)
%/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/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/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.3/maxpool/MaxPool_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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_641, %onnx::Conv_642)
%/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_644, %onnx::Conv_645)
%/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/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/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.3/maxpool/MaxPool_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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_650, %onnx::Conv_651)
%/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_653, %onnx::Conv_654)
%/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/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/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.3/maxpool/MaxPool_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/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_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/conv1x1/conv_bn_relu/conv_bn_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_659, %onnx::Conv_660)
%/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_662, %onnx::Conv_663)
%/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/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/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.3/maxpool/MaxPool_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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_668, %onnx::Conv_669)
%/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_671, %onnx::Conv_672)
%/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/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/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.3/maxpool/MaxPool_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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_677, %onnx::Conv_678)
%/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_680, %onnx::Conv_681)
%/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/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/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.3/maxpool/MaxPool_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/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_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/conv1x1/conv_bn_relu/conv_bn_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_686, %onnx::Conv_687)
%/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_689, %onnx::Conv_690)
%/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/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/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.3/maxpool/MaxPool_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/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)
%606 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %606
}
|
val_accuracy
| 9.505209
| 301,606,912
| 967,178
|
{'zcp_epe_nas': 110.9234105110761, 'zcp_fisher': 118.14064025878906, 'zcp_flops': 4825710592.0, 'zcp_grad_norm': 206.46389770507812, 'zcp_grasp': -786.1376953125, 'zcp_jacov': -16.0495403426321, 'zcp_l2_norm': 498.7563781738281, 'zcp_nwot': 214.61929457230494, 'zcp_params': 967178.0, 'zcp_plain': 0.449035346508026, 'zcp_snip': 944.3605346679688, 'zcp_synflow': 81.2220607550844, 'zcp_zen': 46.04359436035156, 'zcp_val_accuracy': 0.8819110393524171}
| |
NASBench101_385923
|
NASBench101
|
385923
|
e94f02bbf765aa3c68b0648a633e97ad
|
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, 64x128x1x1]
%onnx::Conv_648[FLOAT, 64]
%onnx::Conv_650[FLOAT, 64x64x1x1]
%onnx::Conv_653[FLOAT, 64x64x3x3]
%onnx::Conv_656[FLOAT, 64x128x1x1]
%onnx::Conv_659[FLOAT, 64x128x1x1]
%onnx::Conv_662[FLOAT, 64x64x1x1]
%onnx::Conv_665[FLOAT, 64x64x3x3]
%onnx::Conv_668[FLOAT, 64x128x1x1]
%onnx::Conv_671[FLOAT, 64x128x1x1]
%onnx::Conv_674[FLOAT, 64x64x1x1]
%onnx::Conv_677[FLOAT, 64x64x3x3]
%onnx::Conv_680[FLOAT, 64x128x1x1]
%onnx::Conv_683[FLOAT, 128x128x1x1]
%onnx::Conv_686[FLOAT, 128x128x1x1]
%onnx::Conv_689[FLOAT, 128x128x3x3]
%onnx::Conv_692[FLOAT, 128x128x1x1]
%onnx::Conv_695[FLOAT, 128x256x1x1]
%onnx::Conv_698[FLOAT, 128x128x1x1]
%onnx::Conv_701[FLOAT, 128x128x3x3]
%onnx::Conv_704[FLOAT, 128x256x1x1]
%onnx::Conv_707[FLOAT, 128x256x1x1]
%onnx::Conv_710[FLOAT, 128x128x1x1]
%onnx::Conv_713[FLOAT, 128x128x3x3]
%onnx::Conv_716[FLOAT, 128x256x1x1]
%onnx::Conv_719[FLOAT, 256x256x1x1]
%onnx::Conv_720[FLOAT, 256]
%onnx::Conv_722[FLOAT, 256x256x1x1]
%onnx::Conv_725[FLOAT, 256x256x3x3]
%onnx::Conv_728[FLOAT, 256x256x1x1]
%onnx::Conv_731[FLOAT, 256x512x1x1]
%onnx::Conv_734[FLOAT, 256x256x1x1]
%onnx::Conv_737[FLOAT, 256x256x3x3]
%onnx::Conv_740[FLOAT, 256x512x1x1]
%onnx::Conv_743[FLOAT, 256x512x1x1]
%onnx::Conv_746[FLOAT, 256x256x1x1]
%onnx::Conv_749[FLOAT, 256x256x3x3]
%onnx::Conv_752[FLOAT, 256x512x1x1]
) {
%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_645)
%onnx::Conv_714 = Identity(%onnx::Conv_645)
%onnx::Conv_711 = Identity(%onnx::Conv_645)
%onnx::Conv_708 = Identity(%onnx::Conv_645)
%onnx::Conv_705 = Identity(%onnx::Conv_645)
%onnx::Conv_702 = Identity(%onnx::Conv_645)
%onnx::Conv_699 = Identity(%onnx::Conv_645)
%onnx::Conv_696 = Identity(%onnx::Conv_645)
%onnx::Conv_693 = Identity(%onnx::Conv_645)
%onnx::Conv_690 = Identity(%onnx::Conv_645)
%onnx::Conv_687 = Identity(%onnx::Conv_645)
%onnx::Conv_684 = Identity(%onnx::Conv_645)
%onnx::Conv_681 = Identity(%onnx::Conv_648)
%onnx::Conv_678 = Identity(%onnx::Conv_648)
%onnx::Conv_675 = Identity(%onnx::Conv_648)
%onnx::Conv_672 = Identity(%onnx::Conv_648)
%onnx::Conv_669 = Identity(%onnx::Conv_648)
%onnx::Conv_666 = Identity(%onnx::Conv_648)
%onnx::Conv_663 = Identity(%onnx::Conv_648)
%onnx::Conv_660 = Identity(%onnx::Conv_648)
%onnx::Conv_657 = Identity(%onnx::Conv_648)
%onnx::Conv_654 = Identity(%onnx::Conv_648)
%onnx::Conv_651 = Identity(%onnx::Conv_648)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_650, %onnx::Conv_651)
%/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/conv3x3/conv_bn_relu/conv_bn_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_653, %onnx::Conv_654)
%/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_656, %onnx::Conv_657)
%/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/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/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.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/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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_662, %onnx::Conv_663)
%/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/conv3x3/conv_bn_relu/conv_bn_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_665, %onnx::Conv_666)
%/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_668, %onnx::Conv_669)
%/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/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/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.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/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.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_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/conv1x1/conv_bn_relu/conv_bn_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_674, %onnx::Conv_675)
%/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/conv3x3/conv_bn_relu/conv_bn_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_677, %onnx::Conv_678)
%/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_680, %onnx::Conv_681)
%/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/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/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.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/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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_686, %onnx::Conv_687)
%/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_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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_689, %onnx::Conv_690)
%/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_692, %onnx::Conv_693)
%/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/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/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.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/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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_698, %onnx::Conv_699)
%/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_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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_701, %onnx::Conv_702)
%/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_704, %onnx::Conv_705)
%/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/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/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.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/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.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_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/conv1x1/conv_bn_relu/conv_bn_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_710, %onnx::Conv_711)
%/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_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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_713, %onnx::Conv_714)
%/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_716, %onnx::Conv_717)
%/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/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/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.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/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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_722, %onnx::Conv_723)
%/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/conv3x3/conv_bn_relu/conv_bn_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_725, %onnx::Conv_726)
%/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_728, %onnx::Conv_729)
%/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/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/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.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/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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_734, %onnx::Conv_735)
%/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/conv3x3/conv_bn_relu/conv_bn_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_737, %onnx::Conv_738)
%/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_740, %onnx::Conv_741)
%/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/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/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.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/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.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_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/conv1x1/conv_bn_relu/conv_bn_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_746, %onnx::Conv_747)
%/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/conv3x3/conv_bn_relu/conv_bn_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_749, %onnx::Conv_750)
%/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_752, %onnx::Conv_753)
%/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/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/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.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/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)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%642 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %642
}
|
val_accuracy
| 88.942307
| 1,042,556,928
| 3,468,426
|
{'zcp_epe_nas': 107.56392376735646, 'zcp_fisher': 61.85873794555664, 'zcp_flops': 16680910848.0, 'zcp_grad_norm': 145.42190551757812, 'zcp_grasp': 10.750244140625, 'zcp_jacov': -16.055387046147874, 'zcp_l2_norm': 695.0418090820312, 'zcp_nwot': 218.45396455111666, 'zcp_params': 3468426.0, 'zcp_plain': 0.165231704711914, 'zcp_snip': 808.7145385742188, 'zcp_synflow': 90.55186604131326, 'zcp_zen': 69.58442687988281, 'zcp_val_accuracy': 0.9170672893524171}
| |
NASBench101_370430
|
NASBench101
|
370430
|
dffe03783c31528f5148b85f466ba779
|
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, 128x128x1x1]
%onnx::Conv_677[FLOAT, 128x128x3x3]
%onnx::Conv_680[FLOAT, 128x128x1x1]
%onnx::Conv_683[FLOAT, 128x128x1x1]
%onnx::Conv_686[FLOAT, 128x128x1x1]
%onnx::Conv_689[FLOAT, 128x128x3x3]
%onnx::Conv_692[FLOAT, 128x128x1x1]
%onnx::Conv_695[FLOAT, 128x128x1x1]
%onnx::Conv_698[FLOAT, 128x128x1x1]
%onnx::Conv_701[FLOAT, 128x128x3x3]
%onnx::Conv_704[FLOAT, 128x128x1x1]
%onnx::Conv_707[FLOAT, 128x128x1x1]
%onnx::Conv_710[FLOAT, 256x128x1x1]
%onnx::Conv_711[FLOAT, 256]
%onnx::Conv_713[FLOAT, 256x256x3x3]
%onnx::Conv_716[FLOAT, 256x128x1x1]
%onnx::Conv_719[FLOAT, 256x256x1x1]
%onnx::Conv_722[FLOAT, 256x256x1x1]
%onnx::Conv_725[FLOAT, 256x256x3x3]
%onnx::Conv_728[FLOAT, 256x256x1x1]
%onnx::Conv_731[FLOAT, 256x256x1x1]
%onnx::Conv_734[FLOAT, 256x256x1x1]
%onnx::Conv_737[FLOAT, 256x256x3x3]
%onnx::Conv_740[FLOAT, 256x256x1x1]
%onnx::Conv_743[FLOAT, 256x256x1x1]
%onnx::Conv_746[FLOAT, 512x256x1x1]
%onnx::Conv_747[FLOAT, 512]
%onnx::Conv_749[FLOAT, 512x512x3x3]
%onnx::Conv_752[FLOAT, 512x256x1x1]
%onnx::Conv_755[FLOAT, 512x512x1x1]
%onnx::Conv_758[FLOAT, 512x512x1x1]
%onnx::Conv_761[FLOAT, 512x512x3x3]
%onnx::Conv_764[FLOAT, 512x512x1x1]
%onnx::Conv_767[FLOAT, 512x512x1x1]
%onnx::Conv_770[FLOAT, 512x512x1x1]
%onnx::Conv_773[FLOAT, 512x512x3x3]
%onnx::Conv_776[FLOAT, 512x512x1x1]
%onnx::Conv_779[FLOAT, 512x512x1x1]
) {
%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_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_672)
%onnx::Conv_705 = Identity(%onnx::Conv_672)
%onnx::Conv_702 = Identity(%onnx::Conv_672)
%onnx::Conv_699 = Identity(%onnx::Conv_672)
%onnx::Conv_696 = Identity(%onnx::Conv_672)
%onnx::Conv_693 = Identity(%onnx::Conv_672)
%onnx::Conv_690 = Identity(%onnx::Conv_672)
%onnx::Conv_687 = Identity(%onnx::Conv_672)
%onnx::Conv_684 = Identity(%onnx::Conv_672)
%onnx::Conv_681 = Identity(%onnx::Conv_672)
%onnx::Conv_678 = Identity(%onnx::Conv_672)
%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_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/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_677, %onnx::Conv_678)
%/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_680, %onnx::Conv_681)
%/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_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/Add_3_output_0 = Add(%/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/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_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/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_5_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_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/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_689, %onnx::Conv_690)
%/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/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/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_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/Add_3_output_0 = Add(%/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/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_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/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_5_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_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/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_701, %onnx::Conv_702)
%/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/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/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_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/Add_3_output_0 = Add(%/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/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_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/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_5_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_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/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_713, %onnx::Conv_714)
%/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_716, %onnx::Conv_717)
%/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_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/Add_3_output_0 = Add(%/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/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_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/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_5_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_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/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_725, %onnx::Conv_726)
%/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/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/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_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/Add_3_output_0 = Add(%/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/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_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/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_5_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_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/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_737, %onnx::Conv_738)
%/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/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/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_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/Add_3_output_0 = Add(%/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/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_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/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_5_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_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/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_749, %onnx::Conv_750)
%/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_752, %onnx::Conv_753)
%/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_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/Add_3_output_0 = Add(%/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/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_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/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_5_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_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/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_761, %onnx::Conv_762)
%/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/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/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_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/Add_3_output_0 = Add(%/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/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_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/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_5_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_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/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_773, %onnx::Conv_774)
%/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/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/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_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/Add_3_output_0 = Add(%/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/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_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/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_5_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%669 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %669
}
|
val_accuracy
| 89.322919
| 3,586,926,592
| 12,088,970
|
{'zcp_epe_nas': 99.05616254164926, 'zcp_fisher': 186.98858642578125, 'zcp_flops': 57390825472.0, 'zcp_grad_norm': 234.6580047607422, 'zcp_grasp': -42.193359375, 'zcp_jacov': -16.05344946893609, 'zcp_l2_norm': 818.5975952148438, 'zcp_nwot': 228.7392362005366, 'zcp_params': 12088970.0, 'zcp_plain': 0.15762761235237102, 'zcp_snip': 2042.2030029296875, 'zcp_synflow': 100.01026428948536, 'zcp_zen': 87.70646667480469, 'zcp_val_accuracy': 0.839443087577819}
| |
NASBench101_335822
|
NASBench101
|
335822
|
cb12364032a9d5b184a4df50a5affa06
|
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, 64x64x3x3]
%onnx::Conv_800[FLOAT, 64x64x1x1]
%onnx::Conv_803[FLOAT, 64x64x1x1]
%onnx::Conv_806[FLOAT, 64x128x1x1]
%onnx::Conv_809[FLOAT, 64x64x3x3]
%onnx::Conv_812[FLOAT, 64x64x3x3]
%onnx::Conv_815[FLOAT, 64x64x1x1]
%onnx::Conv_818[FLOAT, 64x64x1x1]
%onnx::Conv_821[FLOAT, 64x128x1x1]
%onnx::Conv_824[FLOAT, 64x64x3x3]
%onnx::Conv_827[FLOAT, 64x64x3x3]
%onnx::Conv_830[FLOAT, 64x64x1x1]
%onnx::Conv_833[FLOAT, 64x64x1x1]
%onnx::Conv_836[FLOAT, 128x128x1x1]
%onnx::Conv_839[FLOAT, 128x128x3x3]
%onnx::Conv_842[FLOAT, 128x128x3x3]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x1x1]
%onnx::Conv_851[FLOAT, 128x256x1x1]
%onnx::Conv_854[FLOAT, 128x128x3x3]
%onnx::Conv_857[FLOAT, 128x128x3x3]
%onnx::Conv_860[FLOAT, 128x128x1x1]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%onnx::Conv_866[FLOAT, 128x256x1x1]
%onnx::Conv_869[FLOAT, 128x128x3x3]
%onnx::Conv_872[FLOAT, 128x128x3x3]
%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, 256x256x3x3]
%onnx::Conv_890[FLOAT, 256x256x1x1]
%onnx::Conv_893[FLOAT, 256x256x1x1]
%onnx::Conv_896[FLOAT, 256x512x1x1]
%onnx::Conv_899[FLOAT, 256x256x3x3]
%onnx::Conv_902[FLOAT, 256x256x3x3]
%onnx::Conv_905[FLOAT, 256x256x1x1]
%onnx::Conv_908[FLOAT, 256x256x1x1]
%onnx::Conv_911[FLOAT, 256x512x1x1]
%onnx::Conv_914[FLOAT, 256x256x3x3]
%onnx::Conv_917[FLOAT, 256x256x3x3]
%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/conv3x3/conv_bn_relu/conv_bn_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.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/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_800, %onnx::Conv_801)
%/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/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.3/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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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/conv3x3/conv_bn_relu/conv_bn_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.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/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_815, %onnx::Conv_816)
%/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/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.3/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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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/conv3x3/conv_bn_relu/conv_bn_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.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/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_830, %onnx::Conv_831)
%/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/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.3/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/conv1x1/conv_bn_relu/conv_bn_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/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_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/conv3x3/conv_bn_relu/conv_bn_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.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/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_845, %onnx::Conv_846)
%/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/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.3/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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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/conv3x3/conv_bn_relu/conv_bn_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.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/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_860, %onnx::Conv_861)
%/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/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.3/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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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/conv3x3/conv_bn_relu/conv_bn_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.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/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_875, %onnx::Conv_876)
%/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/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.3/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/conv1x1/conv_bn_relu/conv_bn_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/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_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/conv3x3/conv_bn_relu/conv_bn_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.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/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_890, %onnx::Conv_891)
%/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/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.3/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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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/conv3x3/conv_bn_relu/conv_bn_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.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/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_905, %onnx::Conv_906)
%/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/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.3/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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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/conv3x3/conv_bn_relu/conv_bn_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.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/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_920, %onnx::Conv_921)
%/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/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.3/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/conv1x1/conv_bn_relu/conv_bn_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/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)
%786 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %786
}
|
val_accuracy
| 91.656649
| 1,666,066,432
| 5,617,418
|
{'zcp_epe_nas': 82.39450788204934, 'zcp_fisher': 112.03303527832031, 'zcp_flops': 26657062912.0, 'zcp_grad_norm': 191.92027282714844, 'zcp_grasp': -50.88037109375, 'zcp_jacov': -16.0573696405959, 'zcp_l2_norm': 798.685546875, 'zcp_nwot': 221.71877672669427, 'zcp_params': 5617418.0, 'zcp_plain': 0.002825783332809, 'zcp_snip': 1089.4244384765625, 'zcp_synflow': 140.5749424052247, 'zcp_zen': 85.7617416381836, 'zcp_val_accuracy': 0.923377394676208}
| |
NASBench101_407451
|
NASBench101
|
407451
|
f6458b6cfbc1769403bd61ec981d40a6
|
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, 128x128x3x3]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%onnx::Conv_866[FLOAT, 128x128x3x3]
%onnx::Conv_869[FLOAT, 128x128x3x3]
%onnx::Conv_872[FLOAT, 128x128x1x1]
%onnx::Conv_875[FLOAT, 128x128x1x1]
%onnx::Conv_878[FLOAT, 128x128x3x3]
%onnx::Conv_881[FLOAT, 128x128x1x1]
%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, 128x128x1x1]
%onnx::Conv_902[FLOAT, 128x128x3x3]
%onnx::Conv_905[FLOAT, 128x128x3x3]
%onnx::Conv_908[FLOAT, 256x128x1x1]
%onnx::Conv_909[FLOAT, 256]
%onnx::Conv_911[FLOAT, 256x128x1x1]
%onnx::Conv_914[FLOAT, 256x256x3x3]
%onnx::Conv_917[FLOAT, 256x256x1x1]
%onnx::Conv_920[FLOAT, 256x256x3x3]
%onnx::Conv_923[FLOAT, 256x256x3x3]
%onnx::Conv_926[FLOAT, 256x256x1x1]
%onnx::Conv_929[FLOAT, 256x256x1x1]
%onnx::Conv_932[FLOAT, 256x256x3x3]
%onnx::Conv_935[FLOAT, 256x256x1x1]
%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, 256x256x1x1]
%onnx::Conv_956[FLOAT, 256x256x3x3]
%onnx::Conv_959[FLOAT, 256x256x3x3]
%onnx::Conv_962[FLOAT, 512x256x1x1]
%onnx::Conv_963[FLOAT, 512]
%onnx::Conv_965[FLOAT, 512x256x1x1]
%onnx::Conv_968[FLOAT, 512x512x3x3]
%onnx::Conv_971[FLOAT, 512x512x1x1]
%onnx::Conv_974[FLOAT, 512x512x3x3]
%onnx::Conv_977[FLOAT, 512x512x3x3]
%onnx::Conv_980[FLOAT, 512x512x1x1]
%onnx::Conv_983[FLOAT, 512x512x1x1]
%onnx::Conv_986[FLOAT, 512x512x3x3]
%onnx::Conv_989[FLOAT, 512x512x1x1]
%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, 512x512x1x1]
%onnx::Conv_1010[FLOAT, 512x512x3x3]
%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/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_857, %onnx::Conv_858)
%/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_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/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_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/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_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/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/conv3x3/conv_bn_relu/conv_bn_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_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/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_875, %onnx::Conv_876)
%/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_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/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_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/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_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/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/conv3x3/conv_bn_relu/conv_bn_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_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/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_893, %onnx::Conv_894)
%/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_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/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_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/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_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/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/conv3x3/conv_bn_relu/conv_bn_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_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/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_911, %onnx::Conv_912)
%/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_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/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_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/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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/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/conv3x3/conv_bn_relu/conv_bn_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_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/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_929, %onnx::Conv_930)
%/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_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/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_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/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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/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/conv3x3/conv_bn_relu/conv_bn_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_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/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_947, %onnx::Conv_948)
%/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_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/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_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/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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/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/conv3x3/conv_bn_relu/conv_bn_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_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/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_965, %onnx::Conv_966)
%/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_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 = <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_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/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/conv3x3/conv_bn_relu/conv_bn_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_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/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_983, %onnx::Conv_984)
%/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_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/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_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/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_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/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/conv3x3/conv_bn_relu/conv_bn_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_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/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_1001, %onnx::Conv_1002)
%/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_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/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_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/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_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/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/conv3x3/conv_bn_relu/conv_bn_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_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
| 92.718351
| 9,033,754,624
| 30,679,178
|
{'zcp_epe_nas': 115.2763004228014, 'zcp_fisher': 221.06565856933594, 'zcp_flops': 144540073984.0, 'zcp_grad_norm': 256.4697265625, 'zcp_grasp': -48.46142578125, 'zcp_jacov': -16.059468373718648, 'zcp_l2_norm': 1242.3587646484375, 'zcp_nwot': 234.68706792826677, 'zcp_params': 30679178.0, 'zcp_plain': 0.036084435880184, 'zcp_snip': 2149.742431640625, 'zcp_synflow': 164.77227468473998, 'zcp_zen': 116.99722290039062, 'zcp_val_accuracy': 0.907952725887298}
| |
NASBench101_390365
|
NASBench101
|
390365
|
ebf50f8118d5be17070444f16849ae3c
|
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, 64x128x1x1]
%onnx::Conv_810[FLOAT, 64]
%onnx::Conv_812[FLOAT, 64x64x1x1]
%onnx::Conv_815[FLOAT, 64x128x1x1]
%onnx::Conv_818[FLOAT, 64x64x1x1]
%onnx::Conv_821[FLOAT, 64x64x1x1]
%onnx::Conv_824[FLOAT, 128x128x1x1]
%onnx::Conv_827[FLOAT, 64x128x1x1]
%onnx::Conv_830[FLOAT, 64x64x1x1]
%onnx::Conv_833[FLOAT, 64x128x1x1]
%onnx::Conv_836[FLOAT, 64x64x1x1]
%onnx::Conv_839[FLOAT, 64x64x1x1]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 64x128x1x1]
%onnx::Conv_848[FLOAT, 64x64x1x1]
%onnx::Conv_851[FLOAT, 64x128x1x1]
%onnx::Conv_854[FLOAT, 64x64x1x1]
%onnx::Conv_857[FLOAT, 64x64x1x1]
%onnx::Conv_860[FLOAT, 128x128x1x1]
%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, 256x128x1x1]
%onnx::Conv_879[FLOAT, 256]
%onnx::Conv_881[FLOAT, 128x256x1x1]
%onnx::Conv_884[FLOAT, 128x128x1x1]
%onnx::Conv_887[FLOAT, 128x256x1x1]
%onnx::Conv_890[FLOAT, 128x128x1x1]
%onnx::Conv_893[FLOAT, 128x128x1x1]
%onnx::Conv_896[FLOAT, 256x256x1x1]
%onnx::Conv_899[FLOAT, 128x256x1x1]
%onnx::Conv_902[FLOAT, 128x128x1x1]
%onnx::Conv_905[FLOAT, 128x256x1x1]
%onnx::Conv_908[FLOAT, 128x128x1x1]
%onnx::Conv_911[FLOAT, 128x128x1x1]
%onnx::Conv_914[FLOAT, 256x256x1x1]
%onnx::Conv_917[FLOAT, 256x256x1x1]
%onnx::Conv_920[FLOAT, 256x256x1x1]
%onnx::Conv_923[FLOAT, 256x256x1x1]
%onnx::Conv_926[FLOAT, 256x256x1x1]
%onnx::Conv_929[FLOAT, 256x256x1x1]
%onnx::Conv_932[FLOAT, 512x256x1x1]
%onnx::Conv_933[FLOAT, 512]
%onnx::Conv_935[FLOAT, 256x512x1x1]
%onnx::Conv_938[FLOAT, 256x256x1x1]
%onnx::Conv_941[FLOAT, 256x512x1x1]
%onnx::Conv_944[FLOAT, 256x256x1x1]
%onnx::Conv_947[FLOAT, 256x256x1x1]
%onnx::Conv_950[FLOAT, 512x512x1x1]
%onnx::Conv_953[FLOAT, 256x512x1x1]
%onnx::Conv_956[FLOAT, 256x256x1x1]
%onnx::Conv_959[FLOAT, 256x512x1x1]
%onnx::Conv_962[FLOAT, 256x256x1x1]
%onnx::Conv_965[FLOAT, 256x256x1x1]
%onnx::Conv_968[FLOAT, 512x512x1x1]
) {
%onnx::Conv_969 = Identity(%onnx::Conv_933)
%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_933)
%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_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_807)
%onnx::Conv_909 = Identity(%onnx::Conv_807)
%onnx::Conv_906 = Identity(%onnx::Conv_807)
%onnx::Conv_903 = Identity(%onnx::Conv_807)
%onnx::Conv_900 = Identity(%onnx::Conv_807)
%onnx::Conv_897 = Identity(%onnx::Conv_879)
%onnx::Conv_894 = Identity(%onnx::Conv_807)
%onnx::Conv_891 = Identity(%onnx::Conv_807)
%onnx::Conv_888 = Identity(%onnx::Conv_807)
%onnx::Conv_885 = Identity(%onnx::Conv_807)
%onnx::Conv_882 = Identity(%onnx::Conv_807)
%onnx::Conv_876 = Identity(%onnx::Conv_807)
%onnx::Conv_873 = Identity(%onnx::Conv_807)
%onnx::Conv_870 = Identity(%onnx::Conv_807)
%onnx::Conv_867 = Identity(%onnx::Conv_807)
%onnx::Conv_864 = Identity(%onnx::Conv_807)
%onnx::Conv_861 = Identity(%onnx::Conv_807)
%onnx::Conv_858 = Identity(%onnx::Conv_810)
%onnx::Conv_855 = Identity(%onnx::Conv_810)
%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_807)
%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_807)
%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)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_812, %onnx::Conv_813)
%/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_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/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_818, %onnx::Conv_819)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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/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_824, %onnx::Conv_825)
%/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_4_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.4/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_830, %onnx::Conv_831)
%/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_4_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/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_836, %onnx::Conv_837)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_839, %onnx::Conv_840)
%/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/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/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_842, %onnx::Conv_843)
%/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_4_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.4/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_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/conv1x1/conv_bn_relu/conv_bn_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_848, %onnx::Conv_849)
%/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_4_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/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_854, %onnx::Conv_855)
%/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/conv1x1/conv_bn_relu/conv_bn_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.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/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/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_860, %onnx::Conv_861)
%/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_4_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.4/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_863, %onnx::Conv_864)
%/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_866, %onnx::Conv_867)
%/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_869, %onnx::Conv_870)
%/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_872, %onnx::Conv_873)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_875, %onnx::Conv_876)
%/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/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/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_878, %onnx::Conv_879)
%/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_4_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.4/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_881, %onnx::Conv_882)
%/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_884, %onnx::Conv_885)
%/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_4_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/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_890, %onnx::Conv_891)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_893, %onnx::Conv_894)
%/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/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/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_896, %onnx::Conv_897)
%/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_4_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.4/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_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/conv1x1/conv_bn_relu/conv_bn_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_902, %onnx::Conv_903)
%/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_4_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/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_908, %onnx::Conv_909)
%/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/conv1x1/conv_bn_relu/conv_bn_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_911, %onnx::Conv_912)
%/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/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/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_914, %onnx::Conv_915)
%/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_4_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.4/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_917, %onnx::Conv_918)
%/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_920, %onnx::Conv_921)
%/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_923, %onnx::Conv_924)
%/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_926, %onnx::Conv_927)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_929, %onnx::Conv_930)
%/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/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/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_932, %onnx::Conv_933)
%/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_4_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.4/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_935, %onnx::Conv_936)
%/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_938, %onnx::Conv_939)
%/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_4_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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/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_950, %onnx::Conv_951)
%/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_4_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.4/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_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/Add_4_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/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_962, %onnx::Conv_963)
%/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/conv1x1/conv_bn_relu/conv_bn_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_965, %onnx::Conv_966)
%/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/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/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_968, %onnx::Conv_969)
%/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_4_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.4/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)
%804 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %804
}
|
val_accuracy
| 83.573717
| 790,767,616
| 2,538,506
|
{'zcp_epe_nas': 101.69327639013453, 'zcp_fisher': 0.6440214514732361, 'zcp_flops': 12652281856.0, 'zcp_grad_norm': 23.44532585144043, 'zcp_grasp': -1.430263519287109, 'zcp_jacov': -16.06849911419279, 'zcp_l2_norm': 1040.9739990234375, 'zcp_nwot': 227.14333836034234, 'zcp_params': 2538506.0, 'zcp_plain': 0.034573372453451004, 'zcp_snip': 136.59063720703125, 'zcp_synflow': 98.31035518139421, 'zcp_zen': 84.68460845947266, 'zcp_val_accuracy': 0.9316906929016111}
| |
NASBench101_208425
|
NASBench101
|
208425
|
7e36005fdb01939e40f18aff2ecf7471
|
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, 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, 128x128x1x1]
%onnx::Conv_920[FLOAT, 128x128x1x1]
%onnx::Conv_923[FLOAT, 128x128x1x1]
%onnx::Conv_926[FLOAT, 256x128x1x1]
%onnx::Conv_927[FLOAT, 256]
%onnx::Conv_929[FLOAT, 256x256x3x3]
%onnx::Conv_932[FLOAT, 256x128x1x1]
%onnx::Conv_935[FLOAT, 256x128x1x1]
%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, 256x256x1x1]
%onnx::Conv_974[FLOAT, 256x256x1x1]
%onnx::Conv_977[FLOAT, 256x256x1x1]
%onnx::Conv_980[FLOAT, 512x256x1x1]
%onnx::Conv_981[FLOAT, 512]
%onnx::Conv_983[FLOAT, 512x512x3x3]
%onnx::Conv_986[FLOAT, 512x256x1x1]
%onnx::Conv_989[FLOAT, 512x256x1x1]
%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_1025[FLOAT, 512x512x1x1]
%onnx::Conv_1028[FLOAT, 512x512x1x1]
%onnx::Conv_1031[FLOAT, 512x512x1x1]
) {
%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/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/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_881, %onnx::Conv_882)
%/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.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/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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/conv1x1/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/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/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_899, %onnx::Conv_900)
%/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.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/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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/conv1x1/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/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/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_917, %onnx::Conv_918)
%/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.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/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_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_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/conv1x1/conv_bn_relu/conv_bn_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_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.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_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/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/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_935, %onnx::Conv_936)
%/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.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/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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/conv1x1/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/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/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_953, %onnx::Conv_954)
%/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.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/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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/conv1x1/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/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/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_971, %onnx::Conv_972)
%/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.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/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_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_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/conv1x1/conv_bn_relu/conv_bn_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_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.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_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/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/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_989, %onnx::Conv_990)
%/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.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/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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/conv1x1/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/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/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_1007, %onnx::Conv_1008)
%/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.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/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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/conv1x1/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/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/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_1025, %onnx::Conv_1026)
%/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.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/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_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_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/conv1x1/conv_bn_relu/conv_bn_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_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)
%/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)
%867 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %867
}
|
val_accuracy
| 90.554887
| 4,168,361,984
| 14,000,266
|
{'zcp_epe_nas': 82.07101847151469, 'zcp_fisher': 188.5209197998047, 'zcp_flops': 66693791744.0, 'zcp_grad_norm': 269.64453125, 'zcp_grasp': 10.560546875, 'zcp_jacov': -16.05753845035298, 'zcp_l2_norm': 1226.897705078125, 'zcp_nwot': 235.53179041560412, 'zcp_params': 14000266.0, 'zcp_plain': 0.022073986008763, 'zcp_snip': 2035.447021484375, 'zcp_synflow': 119.79654890192506, 'zcp_zen': 99.63681030273438, 'zcp_val_accuracy': 0.9190705418586731}
| |
NASBench101_350569
|
NASBench101
|
350569
|
d3eb1cccede36ceb09cf84c87c3dab6a
|
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, 64x128x1x1]
%onnx::Conv_954[FLOAT, 64]
%onnx::Conv_956[FLOAT, 64x64x3x3]
%onnx::Conv_959[FLOAT, 64x128x1x1]
%onnx::Conv_962[FLOAT, 64x64x1x1]
%onnx::Conv_965[FLOAT, 64x128x1x1]
%onnx::Conv_968[FLOAT, 64x64x1x1]
%onnx::Conv_971[FLOAT, 64x64x1x1]
%onnx::Conv_974[FLOAT, 64x128x1x1]
%onnx::Conv_977[FLOAT, 64x64x3x3]
%onnx::Conv_980[FLOAT, 64x128x1x1]
%onnx::Conv_983[FLOAT, 64x64x1x1]
%onnx::Conv_986[FLOAT, 64x128x1x1]
%onnx::Conv_989[FLOAT, 64x64x1x1]
%onnx::Conv_992[FLOAT, 64x64x1x1]
%onnx::Conv_995[FLOAT, 64x128x1x1]
%onnx::Conv_998[FLOAT, 64x64x3x3]
%onnx::Conv_1001[FLOAT, 64x128x1x1]
%onnx::Conv_1004[FLOAT, 64x64x1x1]
%onnx::Conv_1007[FLOAT, 64x128x1x1]
%onnx::Conv_1010[FLOAT, 64x64x1x1]
%onnx::Conv_1013[FLOAT, 64x64x1x1]
%onnx::Conv_1016[FLOAT, 128x128x1x1]
%onnx::Conv_1019[FLOAT, 128x128x3x3]
%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, 128x256x1x1]
%onnx::Conv_1040[FLOAT, 128x128x3x3]
%onnx::Conv_1043[FLOAT, 128x256x1x1]
%onnx::Conv_1046[FLOAT, 128x128x1x1]
%onnx::Conv_1049[FLOAT, 128x256x1x1]
%onnx::Conv_1052[FLOAT, 128x128x1x1]
%onnx::Conv_1055[FLOAT, 128x128x1x1]
%onnx::Conv_1058[FLOAT, 128x256x1x1]
%onnx::Conv_1061[FLOAT, 128x128x3x3]
%onnx::Conv_1064[FLOAT, 128x256x1x1]
%onnx::Conv_1067[FLOAT, 128x128x1x1]
%onnx::Conv_1070[FLOAT, 128x256x1x1]
%onnx::Conv_1073[FLOAT, 128x128x1x1]
%onnx::Conv_1076[FLOAT, 128x128x1x1]
%onnx::Conv_1079[FLOAT, 256x256x1x1]
%onnx::Conv_1080[FLOAT, 256]
%onnx::Conv_1082[FLOAT, 256x256x3x3]
%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, 256x512x1x1]
%onnx::Conv_1103[FLOAT, 256x256x3x3]
%onnx::Conv_1106[FLOAT, 256x512x1x1]
%onnx::Conv_1109[FLOAT, 256x256x1x1]
%onnx::Conv_1112[FLOAT, 256x512x1x1]
%onnx::Conv_1115[FLOAT, 256x256x1x1]
%onnx::Conv_1118[FLOAT, 256x256x1x1]
%onnx::Conv_1121[FLOAT, 256x512x1x1]
%onnx::Conv_1124[FLOAT, 256x256x3x3]
%onnx::Conv_1127[FLOAT, 256x512x1x1]
%onnx::Conv_1130[FLOAT, 256x256x1x1]
%onnx::Conv_1133[FLOAT, 256x512x1x1]
%onnx::Conv_1136[FLOAT, 256x256x1x1]
%onnx::Conv_1139[FLOAT, 256x256x1x1]
) {
%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_951)
%onnx::Conv_1074 = Identity(%onnx::Conv_951)
%onnx::Conv_1071 = Identity(%onnx::Conv_951)
%onnx::Conv_1068 = Identity(%onnx::Conv_951)
%onnx::Conv_1065 = Identity(%onnx::Conv_951)
%onnx::Conv_1062 = Identity(%onnx::Conv_951)
%onnx::Conv_1059 = Identity(%onnx::Conv_951)
%onnx::Conv_1056 = Identity(%onnx::Conv_951)
%onnx::Conv_1053 = Identity(%onnx::Conv_951)
%onnx::Conv_1050 = Identity(%onnx::Conv_951)
%onnx::Conv_1047 = Identity(%onnx::Conv_951)
%onnx::Conv_1044 = Identity(%onnx::Conv_951)
%onnx::Conv_1041 = Identity(%onnx::Conv_951)
%onnx::Conv_1038 = Identity(%onnx::Conv_951)
%onnx::Conv_1035 = Identity(%onnx::Conv_951)
%onnx::Conv_1032 = Identity(%onnx::Conv_951)
%onnx::Conv_1029 = Identity(%onnx::Conv_951)
%onnx::Conv_1026 = Identity(%onnx::Conv_951)
%onnx::Conv_1023 = Identity(%onnx::Conv_951)
%onnx::Conv_1020 = Identity(%onnx::Conv_951)
%onnx::Conv_1017 = Identity(%onnx::Conv_951)
%onnx::Conv_1014 = Identity(%onnx::Conv_954)
%onnx::Conv_1011 = Identity(%onnx::Conv_954)
%onnx::Conv_1008 = Identity(%onnx::Conv_954)
%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)
%/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/conv3x3/conv_bn_relu/conv_bn_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_956, %onnx::Conv_957)
%/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_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/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_968, %onnx::Conv_969)
%/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/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.3/maxpool/MaxPool_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_977, %onnx::Conv_978)
%/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_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/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_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/Concat_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_989, %onnx::Conv_990)
%/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/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.3/maxpool/MaxPool_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_998, %onnx::Conv_999)
%/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_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/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_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/Concat_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/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/conv1x1/conv_bn_relu/conv_bn_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_1010, %onnx::Conv_1011)
%/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/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.3/maxpool/MaxPool_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1019, %onnx::Conv_1020)
%/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_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/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1031, %onnx::Conv_1032)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1034, %onnx::Conv_1035)
%/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1040, %onnx::Conv_1041)
%/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_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/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_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/Concat_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1052, %onnx::Conv_1053)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1055, %onnx::Conv_1056)
%/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1061, %onnx::Conv_1062)
%/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_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/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_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/Concat_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/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/conv1x1/conv_bn_relu/conv_bn_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_1073, %onnx::Conv_1074)
%/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/conv1x1/conv_bn_relu/conv_bn_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_1076, %onnx::Conv_1077)
%/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1082, %onnx::Conv_1083)
%/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_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/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1094, %onnx::Conv_1095)
%/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/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.3/maxpool/MaxPool_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1103, %onnx::Conv_1104)
%/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_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/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_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/Concat_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1115, %onnx::Conv_1116)
%/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/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.3/maxpool/MaxPool_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1124, %onnx::Conv_1125)
%/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_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/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_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/Concat_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/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/conv1x1/conv_bn_relu/conv_bn_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_1136, %onnx::Conv_1137)
%/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/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.3/maxpool/MaxPool_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/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/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)
%948 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %948
}
|
val_accuracy
| 91.185898
| 1,336,027,136
| 4,426,762
|
{'zcp_epe_nas': 135.40099685466305, 'zcp_fisher': 90.66431427001953, 'zcp_flops': 21376434176.0, 'zcp_grad_norm': 204.2870330810547, 'zcp_grasp': 229.46630859375, 'zcp_jacov': -16.055133932710156, 'zcp_l2_norm': 1189.6915283203125, 'zcp_nwot': 227.1180003396881, 'zcp_params': 4426762.0, 'zcp_plain': 0.092096157371997, 'zcp_snip': 1167.5731201171875, 'zcp_synflow': 113.84842060372969, 'zcp_zen': 105.72618865966797, 'zcp_val_accuracy': 0.8645833134651181}
| |
NASBench101_413705
|
NASBench101
|
413705
|
f9f138dd9aeef2565777a872049a0e2e
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_938[FLOAT, 128x3x3x3]
%onnx::Conv_939[FLOAT, 128]
%onnx::Conv_941[FLOAT, 43x128x1x1]
%onnx::Conv_942[FLOAT, 43]
%onnx::Conv_944[FLOAT, 43x128x1x1]
%onnx::Conv_947[FLOAT, 43x43x1x1]
%onnx::Conv_950[FLOAT, 43x43x3x3]
%onnx::Conv_953[FLOAT, 42x42x3x3]
%onnx::Conv_954[FLOAT, 42]
%onnx::Conv_956[FLOAT, 42x42x3x3]
%onnx::Conv_959[FLOAT, 43x128x1x1]
%onnx::Conv_962[FLOAT, 43x128x1x1]
%onnx::Conv_965[FLOAT, 43x43x1x1]
%onnx::Conv_968[FLOAT, 43x43x3x3]
%onnx::Conv_971[FLOAT, 42x42x3x3]
%onnx::Conv_974[FLOAT, 42x42x3x3]
%onnx::Conv_977[FLOAT, 43x128x1x1]
%onnx::Conv_980[FLOAT, 43x128x1x1]
%onnx::Conv_983[FLOAT, 43x43x1x1]
%onnx::Conv_986[FLOAT, 43x43x3x3]
%onnx::Conv_989[FLOAT, 42x42x3x3]
%onnx::Conv_992[FLOAT, 42x42x3x3]
%onnx::Conv_995[FLOAT, 86x128x1x1]
%onnx::Conv_996[FLOAT, 86]
%onnx::Conv_998[FLOAT, 85x128x1x1]
%onnx::Conv_999[FLOAT, 85]
%onnx::Conv_1001[FLOAT, 85x85x1x1]
%onnx::Conv_1004[FLOAT, 85x85x3x3]
%onnx::Conv_1007[FLOAT, 85x85x3x3]
%onnx::Conv_1010[FLOAT, 85x85x3x3]
%onnx::Conv_1013[FLOAT, 86x256x1x1]
%onnx::Conv_1016[FLOAT, 85x256x1x1]
%onnx::Conv_1019[FLOAT, 85x85x1x1]
%onnx::Conv_1022[FLOAT, 85x85x3x3]
%onnx::Conv_1025[FLOAT, 85x85x3x3]
%onnx::Conv_1028[FLOAT, 85x85x3x3]
%onnx::Conv_1031[FLOAT, 86x256x1x1]
%onnx::Conv_1034[FLOAT, 85x256x1x1]
%onnx::Conv_1037[FLOAT, 85x85x1x1]
%onnx::Conv_1040[FLOAT, 85x85x3x3]
%onnx::Conv_1043[FLOAT, 85x85x3x3]
%onnx::Conv_1046[FLOAT, 85x85x3x3]
%onnx::Conv_1049[FLOAT, 171x256x1x1]
%onnx::Conv_1050[FLOAT, 171]
%onnx::Conv_1052[FLOAT, 171x256x1x1]
%onnx::Conv_1055[FLOAT, 171x171x1x1]
%onnx::Conv_1058[FLOAT, 171x171x3x3]
%onnx::Conv_1061[FLOAT, 170x170x3x3]
%onnx::Conv_1062[FLOAT, 170]
%onnx::Conv_1064[FLOAT, 170x170x3x3]
%onnx::Conv_1067[FLOAT, 171x512x1x1]
%onnx::Conv_1070[FLOAT, 171x512x1x1]
%onnx::Conv_1073[FLOAT, 171x171x1x1]
%onnx::Conv_1076[FLOAT, 171x171x3x3]
%onnx::Conv_1079[FLOAT, 170x170x3x3]
%onnx::Conv_1082[FLOAT, 170x170x3x3]
%onnx::Conv_1085[FLOAT, 171x512x1x1]
%onnx::Conv_1088[FLOAT, 171x512x1x1]
%onnx::Conv_1091[FLOAT, 171x171x1x1]
%onnx::Conv_1094[FLOAT, 171x171x3x3]
%onnx::Conv_1097[FLOAT, 170x170x3x3]
%onnx::Conv_1100[FLOAT, 170x170x3x3]
) {
%onnx::Conv_1101 = Identity(%onnx::Conv_1062)
%onnx::Conv_1098 = Identity(%onnx::Conv_1062)
%onnx::Conv_1095 = Identity(%onnx::Conv_1050)
%onnx::Conv_1092 = Identity(%onnx::Conv_1050)
%onnx::Conv_1089 = Identity(%onnx::Conv_1050)
%onnx::Conv_1086 = Identity(%onnx::Conv_1050)
%onnx::Conv_1083 = Identity(%onnx::Conv_1062)
%onnx::Conv_1080 = Identity(%onnx::Conv_1062)
%onnx::Conv_1077 = Identity(%onnx::Conv_1050)
%onnx::Conv_1074 = Identity(%onnx::Conv_1050)
%onnx::Conv_1071 = Identity(%onnx::Conv_1050)
%onnx::Conv_1068 = Identity(%onnx::Conv_1050)
%onnx::Conv_1065 = Identity(%onnx::Conv_1062)
%onnx::Conv_1059 = Identity(%onnx::Conv_1050)
%onnx::Conv_1056 = Identity(%onnx::Conv_1050)
%onnx::Conv_1053 = Identity(%onnx::Conv_1050)
%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_996)
%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_996)
%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_993 = Identity(%onnx::Conv_954)
%onnx::Conv_990 = Identity(%onnx::Conv_954)
%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_954)
%onnx::Conv_972 = Identity(%onnx::Conv_954)
%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_954)
%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_938, %onnx::Conv_939)
%/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_941, %onnx::Conv_942)
%/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_944, %onnx::Conv_945)
%/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_947, %onnx::Conv_948)
%/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_950, %onnx::Conv_951)
%/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.2/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_953, %onnx::Conv_954)
%/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.2/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/conv3x3/conv_bn_relu/conv_bn_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_956, %onnx::Conv_957)
%/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.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_959, %onnx::Conv_960)
%/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_962, %onnx::Conv_963)
%/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_965, %onnx::Conv_966)
%/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_968, %onnx::Conv_969)
%/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.2/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_971, %onnx::Conv_972)
%/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.2/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/conv3x3/conv_bn_relu/conv_bn_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_974, %onnx::Conv_975)
%/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.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_977, %onnx::Conv_978)
%/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_980, %onnx::Conv_981)
%/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_983, %onnx::Conv_984)
%/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_986, %onnx::Conv_987)
%/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.2/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_989, %onnx::Conv_990)
%/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.2/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/conv3x3/conv_bn_relu/conv_bn_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_992, %onnx::Conv_993)
%/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.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_995, %onnx::Conv_996)
%/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_998, %onnx::Conv_999)
%/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_1001, %onnx::Conv_1002)
%/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_1004, %onnx::Conv_1005)
%/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/conv1x1/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_1007, %onnx::Conv_1008)
%/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_1010, %onnx::Conv_1011)
%/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.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_1013, %onnx::Conv_1014)
%/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/Concat_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/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_1019, %onnx::Conv_1020)
%/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_1022, %onnx::Conv_1023)
%/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/conv1x1/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_1025, %onnx::Conv_1026)
%/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_1028, %onnx::Conv_1029)
%/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.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_1031, %onnx::Conv_1032)
%/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/Concat_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/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_1037, %onnx::Conv_1038)
%/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_1040, %onnx::Conv_1041)
%/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/conv1x1/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_1043, %onnx::Conv_1044)
%/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_1046, %onnx::Conv_1047)
%/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.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_1049, %onnx::Conv_1050)
%/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_1052, %onnx::Conv_1053)
%/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_1055, %onnx::Conv_1056)
%/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_1058, %onnx::Conv_1059)
%/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.2/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_1061, %onnx::Conv_1062)
%/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.2/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/conv3x3/conv_bn_relu/conv_bn_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_1064, %onnx::Conv_1065)
%/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.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_1067, %onnx::Conv_1068)
%/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_1070, %onnx::Conv_1071)
%/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_1073, %onnx::Conv_1074)
%/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_1076, %onnx::Conv_1077)
%/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.2/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_1079, %onnx::Conv_1080)
%/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.2/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/conv3x3/conv_bn_relu/conv_bn_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_1082, %onnx::Conv_1083)
%/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.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_1085, %onnx::Conv_1086)
%/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_1088, %onnx::Conv_1089)
%/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_1091, %onnx::Conv_1092)
%/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_1094, %onnx::Conv_1095)
%/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.2/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_1097, %onnx::Conv_1098)
%/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.2/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/conv3x3/conv_bn_relu/conv_bn_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_1100, %onnx::Conv_1101)
%/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.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)
%936 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %936
}
|
val_accuracy
| 92.608172
| 1,130,302,208
| 3,795,268
|
{'zcp_epe_nas': 92.53680236471062, 'zcp_fisher': 7.454337120056152, 'zcp_flops': 18084835328.0, 'zcp_grad_norm': 60.21857452392578, 'zcp_grasp': 0.083770751953125, 'zcp_jacov': -16.05079790401949, 'zcp_l2_norm': 883.84033203125, 'zcp_nwot': 218.3223341116885, 'zcp_params': 3795268.0, 'zcp_plain': -0.020254248753190002, 'zcp_snip': 315.2435302734375, 'zcp_synflow': 109.61084513051067, 'zcp_zen': 97.13228607177734, 'zcp_val_accuracy': 0.905048072338104}
| |
NASBench101_247710
|
NASBench101
|
247710
|
95f5ef91fd2e74455f68075a8e21e43d
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_1067[FLOAT, 128x3x3x3]
%onnx::Conv_1068[FLOAT, 128]
%onnx::Conv_1070[FLOAT, 64x128x1x1]
%onnx::Conv_1071[FLOAT, 64]
%onnx::Conv_1073[FLOAT, 64x64x1x1]
%onnx::Conv_1076[FLOAT, 64x128x1x1]
%onnx::Conv_1079[FLOAT, 64x64x3x3]
%onnx::Conv_1082[FLOAT, 64x128x1x1]
%onnx::Conv_1085[FLOAT, 64x64x3x3]
%onnx::Conv_1088[FLOAT, 64x128x1x1]
%onnx::Conv_1091[FLOAT, 64x64x3x3]
%onnx::Conv_1094[FLOAT, 64x128x1x1]
%onnx::Conv_1097[FLOAT, 64x64x1x1]
%onnx::Conv_1100[FLOAT, 64x128x1x1]
%onnx::Conv_1103[FLOAT, 64x64x3x3]
%onnx::Conv_1106[FLOAT, 64x128x1x1]
%onnx::Conv_1109[FLOAT, 64x64x3x3]
%onnx::Conv_1112[FLOAT, 64x128x1x1]
%onnx::Conv_1115[FLOAT, 64x64x3x3]
%onnx::Conv_1118[FLOAT, 64x128x1x1]
%onnx::Conv_1121[FLOAT, 64x64x1x1]
%onnx::Conv_1124[FLOAT, 64x128x1x1]
%onnx::Conv_1127[FLOAT, 64x64x3x3]
%onnx::Conv_1130[FLOAT, 64x128x1x1]
%onnx::Conv_1133[FLOAT, 64x64x3x3]
%onnx::Conv_1136[FLOAT, 64x128x1x1]
%onnx::Conv_1139[FLOAT, 64x64x3x3]
%onnx::Conv_1142[FLOAT, 128x128x1x1]
%onnx::Conv_1145[FLOAT, 128x128x1x1]
%onnx::Conv_1148[FLOAT, 128x128x1x1]
%onnx::Conv_1151[FLOAT, 128x128x3x3]
%onnx::Conv_1154[FLOAT, 128x128x1x1]
%onnx::Conv_1157[FLOAT, 128x128x3x3]
%onnx::Conv_1160[FLOAT, 128x128x1x1]
%onnx::Conv_1163[FLOAT, 128x128x3x3]
%onnx::Conv_1166[FLOAT, 128x256x1x1]
%onnx::Conv_1169[FLOAT, 128x128x1x1]
%onnx::Conv_1172[FLOAT, 128x256x1x1]
%onnx::Conv_1175[FLOAT, 128x128x3x3]
%onnx::Conv_1178[FLOAT, 128x256x1x1]
%onnx::Conv_1181[FLOAT, 128x128x3x3]
%onnx::Conv_1184[FLOAT, 128x256x1x1]
%onnx::Conv_1187[FLOAT, 128x128x3x3]
%onnx::Conv_1190[FLOAT, 128x256x1x1]
%onnx::Conv_1193[FLOAT, 128x128x1x1]
%onnx::Conv_1196[FLOAT, 128x256x1x1]
%onnx::Conv_1199[FLOAT, 128x128x3x3]
%onnx::Conv_1202[FLOAT, 128x256x1x1]
%onnx::Conv_1205[FLOAT, 128x128x3x3]
%onnx::Conv_1208[FLOAT, 128x256x1x1]
%onnx::Conv_1211[FLOAT, 128x128x3x3]
%onnx::Conv_1214[FLOAT, 256x256x1x1]
%onnx::Conv_1215[FLOAT, 256]
%onnx::Conv_1217[FLOAT, 256x256x1x1]
%onnx::Conv_1220[FLOAT, 256x256x1x1]
%onnx::Conv_1223[FLOAT, 256x256x3x3]
%onnx::Conv_1226[FLOAT, 256x256x1x1]
%onnx::Conv_1229[FLOAT, 256x256x3x3]
%onnx::Conv_1232[FLOAT, 256x256x1x1]
%onnx::Conv_1235[FLOAT, 256x256x3x3]
%onnx::Conv_1238[FLOAT, 256x512x1x1]
%onnx::Conv_1241[FLOAT, 256x256x1x1]
%onnx::Conv_1244[FLOAT, 256x512x1x1]
%onnx::Conv_1247[FLOAT, 256x256x3x3]
%onnx::Conv_1250[FLOAT, 256x512x1x1]
%onnx::Conv_1253[FLOAT, 256x256x3x3]
%onnx::Conv_1256[FLOAT, 256x512x1x1]
%onnx::Conv_1259[FLOAT, 256x256x3x3]
%onnx::Conv_1262[FLOAT, 256x512x1x1]
%onnx::Conv_1265[FLOAT, 256x256x1x1]
%onnx::Conv_1268[FLOAT, 256x512x1x1]
%onnx::Conv_1271[FLOAT, 256x256x3x3]
%onnx::Conv_1274[FLOAT, 256x512x1x1]
%onnx::Conv_1277[FLOAT, 256x256x3x3]
%onnx::Conv_1280[FLOAT, 256x512x1x1]
%onnx::Conv_1283[FLOAT, 256x256x3x3]
) {
%onnx::Conv_1284 = Identity(%onnx::Conv_1215)
%onnx::Conv_1281 = Identity(%onnx::Conv_1215)
%onnx::Conv_1278 = Identity(%onnx::Conv_1215)
%onnx::Conv_1275 = Identity(%onnx::Conv_1215)
%onnx::Conv_1272 = Identity(%onnx::Conv_1215)
%onnx::Conv_1269 = Identity(%onnx::Conv_1215)
%onnx::Conv_1266 = Identity(%onnx::Conv_1215)
%onnx::Conv_1263 = Identity(%onnx::Conv_1215)
%onnx::Conv_1260 = Identity(%onnx::Conv_1215)
%onnx::Conv_1257 = Identity(%onnx::Conv_1215)
%onnx::Conv_1254 = Identity(%onnx::Conv_1215)
%onnx::Conv_1251 = Identity(%onnx::Conv_1215)
%onnx::Conv_1248 = Identity(%onnx::Conv_1215)
%onnx::Conv_1245 = Identity(%onnx::Conv_1215)
%onnx::Conv_1242 = Identity(%onnx::Conv_1215)
%onnx::Conv_1239 = Identity(%onnx::Conv_1215)
%onnx::Conv_1236 = Identity(%onnx::Conv_1215)
%onnx::Conv_1233 = Identity(%onnx::Conv_1215)
%onnx::Conv_1230 = Identity(%onnx::Conv_1215)
%onnx::Conv_1227 = Identity(%onnx::Conv_1215)
%onnx::Conv_1224 = Identity(%onnx::Conv_1215)
%onnx::Conv_1221 = Identity(%onnx::Conv_1215)
%onnx::Conv_1218 = Identity(%onnx::Conv_1215)
%onnx::Conv_1212 = Identity(%onnx::Conv_1068)
%onnx::Conv_1209 = Identity(%onnx::Conv_1068)
%onnx::Conv_1206 = Identity(%onnx::Conv_1068)
%onnx::Conv_1203 = Identity(%onnx::Conv_1068)
%onnx::Conv_1200 = Identity(%onnx::Conv_1068)
%onnx::Conv_1197 = Identity(%onnx::Conv_1068)
%onnx::Conv_1194 = Identity(%onnx::Conv_1068)
%onnx::Conv_1191 = Identity(%onnx::Conv_1068)
%onnx::Conv_1188 = Identity(%onnx::Conv_1068)
%onnx::Conv_1185 = Identity(%onnx::Conv_1068)
%onnx::Conv_1182 = Identity(%onnx::Conv_1068)
%onnx::Conv_1179 = Identity(%onnx::Conv_1068)
%onnx::Conv_1176 = Identity(%onnx::Conv_1068)
%onnx::Conv_1173 = Identity(%onnx::Conv_1068)
%onnx::Conv_1170 = Identity(%onnx::Conv_1068)
%onnx::Conv_1167 = Identity(%onnx::Conv_1068)
%onnx::Conv_1164 = Identity(%onnx::Conv_1068)
%onnx::Conv_1161 = Identity(%onnx::Conv_1068)
%onnx::Conv_1158 = Identity(%onnx::Conv_1068)
%onnx::Conv_1155 = Identity(%onnx::Conv_1068)
%onnx::Conv_1152 = Identity(%onnx::Conv_1068)
%onnx::Conv_1149 = Identity(%onnx::Conv_1068)
%onnx::Conv_1146 = Identity(%onnx::Conv_1068)
%onnx::Conv_1143 = Identity(%onnx::Conv_1068)
%onnx::Conv_1140 = Identity(%onnx::Conv_1071)
%onnx::Conv_1137 = Identity(%onnx::Conv_1071)
%onnx::Conv_1134 = Identity(%onnx::Conv_1071)
%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)
%/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_1067, %onnx::Conv_1068)
%/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_1070, %onnx::Conv_1071)
%/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_1073, %onnx::Conv_1074)
%/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_1076, %onnx::Conv_1077)
%/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_1079, %onnx::Conv_1080)
%/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_1082, %onnx::Conv_1083)
%/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/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.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_1085, %onnx::Conv_1086)
%/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_1088, %onnx::Conv_1089)
%/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_4_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/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_1091, %onnx::Conv_1092)
%/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_1094, %onnx::Conv_1095)
%/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_1097, %onnx::Conv_1098)
%/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_1100, %onnx::Conv_1101)
%/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_1103, %onnx::Conv_1104)
%/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_1106, %onnx::Conv_1107)
%/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/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.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_1109, %onnx::Conv_1110)
%/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_1112, %onnx::Conv_1113)
%/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_4_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/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_1115, %onnx::Conv_1116)
%/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_1118, %onnx::Conv_1119)
%/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_1121, %onnx::Conv_1122)
%/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_1124, %onnx::Conv_1125)
%/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_1127, %onnx::Conv_1128)
%/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_1130, %onnx::Conv_1131)
%/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/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.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_1133, %onnx::Conv_1134)
%/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_1136, %onnx::Conv_1137)
%/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_4_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/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_1139, %onnx::Conv_1140)
%/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_1142, %onnx::Conv_1143)
%/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_1145, %onnx::Conv_1146)
%/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_1148, %onnx::Conv_1149)
%/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_1151, %onnx::Conv_1152)
%/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_1154, %onnx::Conv_1155)
%/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/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.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_1157, %onnx::Conv_1158)
%/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_1160, %onnx::Conv_1161)
%/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_4_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/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_1163, %onnx::Conv_1164)
%/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_1166, %onnx::Conv_1167)
%/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_1169, %onnx::Conv_1170)
%/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_1172, %onnx::Conv_1173)
%/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_1175, %onnx::Conv_1176)
%/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_1178, %onnx::Conv_1179)
%/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/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.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_1181, %onnx::Conv_1182)
%/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_1184, %onnx::Conv_1185)
%/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_4_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/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_1187, %onnx::Conv_1188)
%/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_1190, %onnx::Conv_1191)
%/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_1193, %onnx::Conv_1194)
%/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_1196, %onnx::Conv_1197)
%/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_1199, %onnx::Conv_1200)
%/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_1202, %onnx::Conv_1203)
%/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/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.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_1205, %onnx::Conv_1206)
%/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_1208, %onnx::Conv_1209)
%/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_4_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/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_1211, %onnx::Conv_1212)
%/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_1214, %onnx::Conv_1215)
%/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_1217, %onnx::Conv_1218)
%/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_1220, %onnx::Conv_1221)
%/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_1223, %onnx::Conv_1224)
%/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_1226, %onnx::Conv_1227)
%/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/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.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_1229, %onnx::Conv_1230)
%/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_1232, %onnx::Conv_1233)
%/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_4_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/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_1235, %onnx::Conv_1236)
%/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_1238, %onnx::Conv_1239)
%/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_1241, %onnx::Conv_1242)
%/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_1244, %onnx::Conv_1245)
%/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_1247, %onnx::Conv_1248)
%/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_1250, %onnx::Conv_1251)
%/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/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.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_1253, %onnx::Conv_1254)
%/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_1256, %onnx::Conv_1257)
%/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_4_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/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_1259, %onnx::Conv_1260)
%/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_1262, %onnx::Conv_1263)
%/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_1265, %onnx::Conv_1266)
%/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_1268, %onnx::Conv_1269)
%/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_1271, %onnx::Conv_1272)
%/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_1274, %onnx::Conv_1275)
%/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/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.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_1277, %onnx::Conv_1278)
%/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_1280, %onnx::Conv_1281)
%/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_4_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/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_1283, %onnx::Conv_1284)
%/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)
%1065 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %1065
}
|
val_accuracy
| 93.930286
| 2,680,956,928
| 8,992,394
|
{'zcp_epe_nas': 78.46092731287172, 'zcp_fisher': 2.276650667190551, 'zcp_flops': 42895310848.0, 'zcp_grad_norm': 35.36616516113281, 'zcp_grasp': 0.11963653564453101, 'zcp_jacov': -16.073718815168007, 'zcp_l2_norm': 1386.2919921875, 'zcp_nwot': 228.77277397120807, 'zcp_params': 8992394.0, 'zcp_plain': -0.009088848717510001, 'zcp_snip': 235.7122344970703, 'zcp_synflow': 126.83391816895202, 'zcp_zen': 133.02955627441406, 'zcp_val_accuracy': 0.9399038553237911}
| |
NASBench101_275241
|
NASBench101
|
275241
|
a6a70b5dfd26436aaf7aa99767dd3e3e
|
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, 128x128x1x1]
%onnx::Conv_839[FLOAT, 128x128x1x1]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x3x3]
%onnx::Conv_851[FLOAT, 128x128x3x3]
%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, 128x128x3x3]
%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, 128x128x3x3]
%onnx::Conv_890[FLOAT, 256x128x1x1]
%onnx::Conv_891[FLOAT, 256]
%onnx::Conv_893[FLOAT, 256x256x1x1]
%onnx::Conv_896[FLOAT, 256x128x1x1]
%onnx::Conv_899[FLOAT, 256x256x1x1]
%onnx::Conv_902[FLOAT, 256x256x3x3]
%onnx::Conv_905[FLOAT, 256x256x3x3]
%onnx::Conv_908[FLOAT, 256x256x1x1]
%onnx::Conv_911[FLOAT, 256x256x1x1]
%onnx::Conv_914[FLOAT, 256x256x1x1]
%onnx::Conv_917[FLOAT, 256x256x1x1]
%onnx::Conv_920[FLOAT, 256x256x3x3]
%onnx::Conv_923[FLOAT, 256x256x3x3]
%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, 256x256x3x3]
%onnx::Conv_944[FLOAT, 512x256x1x1]
%onnx::Conv_945[FLOAT, 512]
%onnx::Conv_947[FLOAT, 512x512x1x1]
%onnx::Conv_950[FLOAT, 512x256x1x1]
%onnx::Conv_953[FLOAT, 512x512x1x1]
%onnx::Conv_956[FLOAT, 512x512x3x3]
%onnx::Conv_959[FLOAT, 512x512x3x3]
%onnx::Conv_962[FLOAT, 512x512x1x1]
%onnx::Conv_965[FLOAT, 512x512x1x1]
%onnx::Conv_968[FLOAT, 512x512x1x1]
%onnx::Conv_971[FLOAT, 512x512x1x1]
%onnx::Conv_974[FLOAT, 512x512x3x3]
%onnx::Conv_977[FLOAT, 512x512x3x3]
%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, 512x512x3x3]
) {
%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_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)
%onnx::Conv_888 = Identity(%onnx::Conv_834)
%onnx::Conv_885 = Identity(%onnx::Conv_834)
%onnx::Conv_882 = Identity(%onnx::Conv_834)
%onnx::Conv_879 = Identity(%onnx::Conv_834)
%onnx::Conv_876 = Identity(%onnx::Conv_834)
%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_834)
%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_846 = 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_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/input_op.2/conv_bn_relu/conv_bn_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/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_845, %onnx::Conv_846)
%/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_3_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/conv3x3/conv_bn_relu/conv_bn_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/Add_4_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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_851, %onnx::Conv_852)
%/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_863, %onnx::Conv_864)
%/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_3_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/conv3x3/conv_bn_relu/conv_bn_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/Add_4_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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_869, %onnx::Conv_870)
%/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_881, %onnx::Conv_882)
%/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_3_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/conv3x3/conv_bn_relu/conv_bn_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/Add_4_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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_887, %onnx::Conv_888)
%/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_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/input_op.2/conv_bn_relu/conv_bn_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/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_899, %onnx::Conv_900)
%/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_3_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/conv3x3/conv_bn_relu/conv_bn_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/Add_4_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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_905, %onnx::Conv_906)
%/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_917, %onnx::Conv_918)
%/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_3_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/conv3x3/conv_bn_relu/conv_bn_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/Add_4_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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_923, %onnx::Conv_924)
%/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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/Add_3_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/conv3x3/conv_bn_relu/conv_bn_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/Add_4_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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_941, %onnx::Conv_942)
%/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_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/input_op.2/conv_bn_relu/conv_bn_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/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_953, %onnx::Conv_954)
%/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_3_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/conv3x3/conv_bn_relu/conv_bn_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/Add_4_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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_959, %onnx::Conv_960)
%/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_971, %onnx::Conv_972)
%/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_3_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/conv3x3/conv_bn_relu/conv_bn_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/Add_4_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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_977, %onnx::Conv_978)
%/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_989, %onnx::Conv_990)
%/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_3_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/conv3x3/conv_bn_relu/conv_bn_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/Add_4_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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_995, %onnx::Conv_996)
%/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)
%831 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %831
}
|
val_accuracy
| 92.497998
| 6,617,835,520
| 22,421,642
|
{'zcp_epe_nas': 112.04896197443851, 'zcp_fisher': 22.948749542236328, 'zcp_flops': 105885368320.0, 'zcp_grad_norm': 77.70215606689453, 'zcp_grasp': 3.64593505859375, 'zcp_jacov': -16.046681156644265, 'zcp_l2_norm': 1242.3812255859375, 'zcp_nwot': 234.17488915980766, 'zcp_params': 22421642.0, 'zcp_plain': -0.005886509083211, 'zcp_snip': 653.9764404296875, 'zcp_synflow': 156.68112226820253, 'zcp_zen': 120.77342224121094, 'zcp_val_accuracy': 0.892327725887298}
| |
NASBench101_331367
|
NASBench101
|
331367
|
c870f951f27d72c792548e6d32b8280f
|
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, 32x128x1x1]
%onnx::Conv_783[FLOAT, 32]
%onnx::Conv_785[FLOAT, 32x128x1x1]
%onnx::Conv_788[FLOAT, 32x32x3x3]
%onnx::Conv_791[FLOAT, 32x32x3x3]
%onnx::Conv_794[FLOAT, 32x32x1x1]
%onnx::Conv_797[FLOAT, 32x128x1x1]
%onnx::Conv_800[FLOAT, 32x128x1x1]
%onnx::Conv_803[FLOAT, 32x32x3x3]
%onnx::Conv_806[FLOAT, 32x32x3x3]
%onnx::Conv_809[FLOAT, 32x32x1x1]
%onnx::Conv_812[FLOAT, 32x128x1x1]
%onnx::Conv_815[FLOAT, 32x128x1x1]
%onnx::Conv_818[FLOAT, 32x32x3x3]
%onnx::Conv_821[FLOAT, 32x32x3x3]
%onnx::Conv_824[FLOAT, 32x32x1x1]
%onnx::Conv_827[FLOAT, 64x128x1x1]
%onnx::Conv_828[FLOAT, 64]
%onnx::Conv_830[FLOAT, 64x128x1x1]
%onnx::Conv_833[FLOAT, 64x64x3x3]
%onnx::Conv_836[FLOAT, 64x64x3x3]
%onnx::Conv_839[FLOAT, 64x64x1x1]
%onnx::Conv_842[FLOAT, 64x256x1x1]
%onnx::Conv_845[FLOAT, 64x256x1x1]
%onnx::Conv_848[FLOAT, 64x64x3x3]
%onnx::Conv_851[FLOAT, 64x64x3x3]
%onnx::Conv_854[FLOAT, 64x64x1x1]
%onnx::Conv_857[FLOAT, 64x256x1x1]
%onnx::Conv_860[FLOAT, 64x256x1x1]
%onnx::Conv_863[FLOAT, 64x64x3x3]
%onnx::Conv_866[FLOAT, 64x64x3x3]
%onnx::Conv_869[FLOAT, 64x64x1x1]
%onnx::Conv_872[FLOAT, 128x256x1x1]
%onnx::Conv_875[FLOAT, 128x256x1x1]
%onnx::Conv_878[FLOAT, 128x128x3x3]
%onnx::Conv_881[FLOAT, 128x128x3x3]
%onnx::Conv_884[FLOAT, 128x128x1x1]
%onnx::Conv_887[FLOAT, 128x512x1x1]
%onnx::Conv_890[FLOAT, 128x512x1x1]
%onnx::Conv_893[FLOAT, 128x128x3x3]
%onnx::Conv_896[FLOAT, 128x128x3x3]
%onnx::Conv_899[FLOAT, 128x128x1x1]
%onnx::Conv_902[FLOAT, 128x512x1x1]
%onnx::Conv_905[FLOAT, 128x512x1x1]
%onnx::Conv_908[FLOAT, 128x128x3x3]
%onnx::Conv_911[FLOAT, 128x128x3x3]
%onnx::Conv_914[FLOAT, 128x128x1x1]
) {
%onnx::Conv_915 = Identity(%onnx::Conv_780)
%onnx::Conv_912 = Identity(%onnx::Conv_780)
%onnx::Conv_909 = Identity(%onnx::Conv_780)
%onnx::Conv_906 = Identity(%onnx::Conv_780)
%onnx::Conv_903 = Identity(%onnx::Conv_780)
%onnx::Conv_900 = Identity(%onnx::Conv_780)
%onnx::Conv_897 = Identity(%onnx::Conv_780)
%onnx::Conv_894 = Identity(%onnx::Conv_780)
%onnx::Conv_891 = Identity(%onnx::Conv_780)
%onnx::Conv_888 = Identity(%onnx::Conv_780)
%onnx::Conv_885 = Identity(%onnx::Conv_780)
%onnx::Conv_882 = Identity(%onnx::Conv_780)
%onnx::Conv_879 = Identity(%onnx::Conv_780)
%onnx::Conv_876 = Identity(%onnx::Conv_780)
%onnx::Conv_873 = Identity(%onnx::Conv_780)
%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)
%/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/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_785, %onnx::Conv_786)
%/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_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/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_791, %onnx::Conv_792)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_794, %onnx::Conv_795)
%/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_4_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_4_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/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.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/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_800, %onnx::Conv_801)
%/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_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/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_806, %onnx::Conv_807)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_809, %onnx::Conv_810)
%/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_4_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_4_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/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.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/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_815, %onnx::Conv_816)
%/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_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/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_821, %onnx::Conv_822)
%/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/conv1x1/conv_bn_relu/conv_bn_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_824, %onnx::Conv_825)
%/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_4_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_4_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/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.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/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_830, %onnx::Conv_831)
%/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_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/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_836, %onnx::Conv_837)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_839, %onnx::Conv_840)
%/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_4_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_4_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/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.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/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/Concat_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/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_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/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_851, %onnx::Conv_852)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_854, %onnx::Conv_855)
%/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_4_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_4_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/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.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/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/Concat_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/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_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/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_866, %onnx::Conv_867)
%/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/conv1x1/conv_bn_relu/conv_bn_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_869, %onnx::Conv_870)
%/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_4_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_4_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/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.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/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_875, %onnx::Conv_876)
%/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_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/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_881, %onnx::Conv_882)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_884, %onnx::Conv_885)
%/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_4_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_4_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/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.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/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_890, %onnx::Conv_891)
%/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_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/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_896, %onnx::Conv_897)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_899, %onnx::Conv_900)
%/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_4_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_4_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/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.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/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_905, %onnx::Conv_906)
%/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_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/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_911, %onnx::Conv_912)
%/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/conv1x1/conv_bn_relu/conv_bn_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_914, %onnx::Conv_915)
%/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_4_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_4_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/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.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
| 90.885419
| 507,848,704
| 1,675,466
|
{'zcp_epe_nas': 89.92548358318713, 'zcp_fisher': 203.8788604736328, 'zcp_flops': 8125579264.0, 'zcp_grad_norm': 264.723388671875, 'zcp_grasp': 117.953125, 'zcp_jacov': -16.066825688939847, 'zcp_l2_norm': 712.4859619140625, 'zcp_nwot': 211.79849029881225, 'zcp_params': 1675466.0, 'zcp_plain': 0.072145655751228, 'zcp_snip': 1123.1927490234375, 'zcp_synflow': 111.14624529263745, 'zcp_zen': 73.83191680908203, 'zcp_val_accuracy': 0.942908644676208}
| |
NASBench101_198030
|
NASBench101
|
198030
|
77da401d8f4365a77dd786a62b510e1c
|
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, 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, 128x128x1x1]
%onnx::Conv_920[FLOAT, 128x128x1x1]
%onnx::Conv_923[FLOAT, 128x128x1x1]
%onnx::Conv_926[FLOAT, 256x128x1x1]
%onnx::Conv_927[FLOAT, 256]
%onnx::Conv_929[FLOAT, 256x256x3x3]
%onnx::Conv_932[FLOAT, 256x256x1x1]
%onnx::Conv_935[FLOAT, 256x256x1x1]
%onnx::Conv_938[FLOAT, 256x256x1x1]
%onnx::Conv_941[FLOAT, 256x128x1x1]
%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, 256x256x1x1]
%onnx::Conv_974[FLOAT, 256x256x1x1]
%onnx::Conv_977[FLOAT, 256x256x1x1]
%onnx::Conv_980[FLOAT, 512x256x1x1]
%onnx::Conv_981[FLOAT, 512]
%onnx::Conv_983[FLOAT, 512x512x3x3]
%onnx::Conv_986[FLOAT, 512x512x1x1]
%onnx::Conv_989[FLOAT, 512x512x1x1]
%onnx::Conv_992[FLOAT, 512x512x1x1]
%onnx::Conv_995[FLOAT, 512x256x1x1]
%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_1025[FLOAT, 512x512x1x1]
%onnx::Conv_1028[FLOAT, 512x512x1x1]
%onnx::Conv_1031[FLOAT, 512x512x1x1]
) {
%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/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_878, %onnx::Conv_879)
%/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.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/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_3_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/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_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/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_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/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_887, %onnx::Conv_888)
%/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_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/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_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_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/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_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_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/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_902, %onnx::Conv_903)
%/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_905, %onnx::Conv_906)
%/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_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/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_914, %onnx::Conv_915)
%/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.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/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_3_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/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_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/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_920, %onnx::Conv_921)
%/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_923, %onnx::Conv_924)
%/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_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/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_932, %onnx::Conv_933)
%/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.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/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_3_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/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_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/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_938, %onnx::Conv_939)
%/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_941, %onnx::Conv_942)
%/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_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/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_950, %onnx::Conv_951)
%/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.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/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_3_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/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_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/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_956, %onnx::Conv_957)
%/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_959, %onnx::Conv_960)
%/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_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/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_968, %onnx::Conv_969)
%/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.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/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_3_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/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_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/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_974, %onnx::Conv_975)
%/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_977, %onnx::Conv_978)
%/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_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/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_986, %onnx::Conv_987)
%/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.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/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_3_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/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_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/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_992, %onnx::Conv_993)
%/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_995, %onnx::Conv_996)
%/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_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/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_1004, %onnx::Conv_1005)
%/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.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/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_3_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/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_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/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_1010, %onnx::Conv_1011)
%/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_1013, %onnx::Conv_1014)
%/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_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/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_1022, %onnx::Conv_1023)
%/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.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/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_3_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/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_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/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_1028, %onnx::Conv_1029)
%/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_1031, %onnx::Conv_1032)
%/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)
%867 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %867
}
|
val_accuracy
| 93.399441
| 4,201,916,416
| 14,164,106
|
{'zcp_epe_nas': 76.13324485552434, 'zcp_fisher': 26.06396484375, 'zcp_flops': 67230662656.0, 'zcp_grad_norm': 95.83882904052734, 'zcp_grasp': -4.2939453125, 'zcp_jacov': -16.03902198456045, 'zcp_l2_norm': 1242.1619873046875, 'zcp_nwot': 235.23941802546636, 'zcp_params': 14164106.0, 'zcp_plain': 0.059879895299673004, 'zcp_snip': 761.82373046875, 'zcp_synflow': 146.64721825037321, 'zcp_zen': 105.84344482421875, 'zcp_val_accuracy': 0.945112168788909}
| |
NASBench101_179506
|
NASBench101
|
179506
|
6ca60c68fa5b0b489cf08e3fc9174994
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_680[FLOAT, 128x3x3x3]
%onnx::Conv_681[FLOAT, 128]
%onnx::Conv_683[FLOAT, 64x128x1x1]
%onnx::Conv_684[FLOAT, 64]
%onnx::Conv_686[FLOAT, 64x64x3x3]
%onnx::Conv_689[FLOAT, 64x64x1x1]
%onnx::Conv_692[FLOAT, 64x64x1x1]
%onnx::Conv_695[FLOAT, 64x128x1x1]
%onnx::Conv_698[FLOAT, 64x64x3x3]
%onnx::Conv_701[FLOAT, 64x64x1x1]
%onnx::Conv_704[FLOAT, 64x64x1x1]
%onnx::Conv_707[FLOAT, 64x128x1x1]
%onnx::Conv_710[FLOAT, 64x64x3x3]
%onnx::Conv_713[FLOAT, 64x64x1x1]
%onnx::Conv_716[FLOAT, 64x64x1x1]
%onnx::Conv_719[FLOAT, 128x128x1x1]
%onnx::Conv_722[FLOAT, 128x128x3x3]
%onnx::Conv_725[FLOAT, 128x128x1x1]
%onnx::Conv_728[FLOAT, 128x128x1x1]
%onnx::Conv_731[FLOAT, 128x256x1x1]
%onnx::Conv_734[FLOAT, 128x128x3x3]
%onnx::Conv_737[FLOAT, 128x128x1x1]
%onnx::Conv_740[FLOAT, 128x128x1x1]
%onnx::Conv_743[FLOAT, 128x256x1x1]
%onnx::Conv_746[FLOAT, 128x128x3x3]
%onnx::Conv_749[FLOAT, 128x128x1x1]
%onnx::Conv_752[FLOAT, 128x128x1x1]
%onnx::Conv_755[FLOAT, 256x256x1x1]
%onnx::Conv_756[FLOAT, 256]
%onnx::Conv_758[FLOAT, 256x256x3x3]
%onnx::Conv_761[FLOAT, 256x256x1x1]
%onnx::Conv_764[FLOAT, 256x256x1x1]
%onnx::Conv_767[FLOAT, 256x512x1x1]
%onnx::Conv_770[FLOAT, 256x256x3x3]
%onnx::Conv_773[FLOAT, 256x256x1x1]
%onnx::Conv_776[FLOAT, 256x256x1x1]
%onnx::Conv_779[FLOAT, 256x512x1x1]
%onnx::Conv_782[FLOAT, 256x256x3x3]
%onnx::Conv_785[FLOAT, 256x256x1x1]
%onnx::Conv_788[FLOAT, 256x256x1x1]
) {
%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)
%onnx::Conv_753 = Identity(%onnx::Conv_681)
%onnx::Conv_750 = Identity(%onnx::Conv_681)
%onnx::Conv_747 = Identity(%onnx::Conv_681)
%onnx::Conv_744 = Identity(%onnx::Conv_681)
%onnx::Conv_741 = Identity(%onnx::Conv_681)
%onnx::Conv_738 = Identity(%onnx::Conv_681)
%onnx::Conv_735 = Identity(%onnx::Conv_681)
%onnx::Conv_732 = Identity(%onnx::Conv_681)
%onnx::Conv_729 = Identity(%onnx::Conv_681)
%onnx::Conv_726 = Identity(%onnx::Conv_681)
%onnx::Conv_723 = Identity(%onnx::Conv_681)
%onnx::Conv_720 = Identity(%onnx::Conv_681)
%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)
%/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_680, %onnx::Conv_681)
%/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_683, %onnx::Conv_684)
%/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_686, %onnx::Conv_687)
%/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_689, %onnx::Conv_690)
%/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.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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_692, %onnx::Conv_693)
%/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_695, %onnx::Conv_696)
%/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_698, %onnx::Conv_699)
%/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_701, %onnx::Conv_702)
%/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.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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_704, %onnx::Conv_705)
%/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_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 = <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/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_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/conv1x1/conv_bn_relu/conv_bn_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_716, %onnx::Conv_717)
%/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_719, %onnx::Conv_720)
%/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_722, %onnx::Conv_723)
%/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/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.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_725, %onnx::Conv_726)
%/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.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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_728, %onnx::Conv_729)
%/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_731, %onnx::Conv_732)
%/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_734, %onnx::Conv_735)
%/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/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.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_737, %onnx::Conv_738)
%/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.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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_740, %onnx::Conv_741)
%/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_743, %onnx::Conv_744)
%/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_746, %onnx::Conv_747)
%/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/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_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_749, %onnx::Conv_750)
%/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.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/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_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/conv1x1/conv_bn_relu/conv_bn_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_752, %onnx::Conv_753)
%/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_755, %onnx::Conv_756)
%/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_758, %onnx::Conv_759)
%/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_761, %onnx::Conv_762)
%/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.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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_764, %onnx::Conv_765)
%/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_767, %onnx::Conv_768)
%/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_770, %onnx::Conv_771)
%/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_773, %onnx::Conv_774)
%/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.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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_776, %onnx::Conv_777)
%/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_779, %onnx::Conv_780)
%/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_782, %onnx::Conv_783)
%/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_785, %onnx::Conv_786)
%/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.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/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_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/conv1x1/conv_bn_relu/conv_bn_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_788, %onnx::Conv_789)
%/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)
%678 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %678
}
|
val_accuracy
| 91.766828
| 983,836,672
| 3,292,298
|
{'zcp_epe_nas': 117.7844184628156, 'zcp_fisher': 37.2276611328125, 'zcp_flops': 15741386752.0, 'zcp_grad_norm': 92.07573699951172, 'zcp_grasp': -3.174560546875, 'zcp_jacov': -16.052610763845152, 'zcp_l2_norm': 649.13232421875, 'zcp_nwot': 218.3379333561873, 'zcp_params': 3292298.0, 'zcp_plain': 0.09748329222202301, 'zcp_snip': 545.3758544921875, 'zcp_synflow': 108.82122403699904, 'zcp_zen': 69.05035400390625, 'zcp_val_accuracy': 0.9228765964508051}
| |
NASBench101_193165
|
NASBench101
|
193165
|
74d5a71f2eacdb088cc36e5601c952ac
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_650[FLOAT, 128x3x3x3]
%onnx::Conv_651[FLOAT, 128]
%onnx::Conv_653[FLOAT, 43x128x1x1]
%onnx::Conv_654[FLOAT, 43]
%onnx::Conv_656[FLOAT, 43x43x1x1]
%onnx::Conv_659[FLOAT, 42x42x3x3]
%onnx::Conv_660[FLOAT, 42]
%onnx::Conv_662[FLOAT, 43x128x1x1]
%onnx::Conv_665[FLOAT, 43x43x1x1]
%onnx::Conv_668[FLOAT, 42x42x3x3]
%onnx::Conv_671[FLOAT, 43x128x1x1]
%onnx::Conv_674[FLOAT, 43x43x1x1]
%onnx::Conv_677[FLOAT, 42x42x3x3]
%onnx::Conv_680[FLOAT, 86x128x1x1]
%onnx::Conv_681[FLOAT, 86]
%onnx::Conv_683[FLOAT, 86x86x1x1]
%onnx::Conv_686[FLOAT, 85x85x3x3]
%onnx::Conv_687[FLOAT, 85]
%onnx::Conv_689[FLOAT, 86x256x1x1]
%onnx::Conv_692[FLOAT, 86x86x1x1]
%onnx::Conv_695[FLOAT, 85x85x3x3]
%onnx::Conv_698[FLOAT, 86x256x1x1]
%onnx::Conv_701[FLOAT, 86x86x1x1]
%onnx::Conv_704[FLOAT, 85x85x3x3]
%onnx::Conv_707[FLOAT, 171x256x1x1]
%onnx::Conv_708[FLOAT, 171]
%onnx::Conv_710[FLOAT, 171x171x1x1]
%onnx::Conv_713[FLOAT, 170x170x3x3]
%onnx::Conv_714[FLOAT, 170]
%onnx::Conv_716[FLOAT, 171x512x1x1]
%onnx::Conv_719[FLOAT, 171x171x1x1]
%onnx::Conv_722[FLOAT, 170x170x3x3]
%onnx::Conv_725[FLOAT, 171x512x1x1]
%onnx::Conv_728[FLOAT, 171x171x1x1]
%onnx::Conv_731[FLOAT, 170x170x3x3]
) {
%onnx::Conv_732 = Identity(%onnx::Conv_714)
%onnx::Conv_729 = Identity(%onnx::Conv_708)
%onnx::Conv_726 = Identity(%onnx::Conv_708)
%onnx::Conv_723 = Identity(%onnx::Conv_714)
%onnx::Conv_720 = Identity(%onnx::Conv_708)
%onnx::Conv_717 = Identity(%onnx::Conv_708)
%onnx::Conv_711 = Identity(%onnx::Conv_708)
%onnx::Conv_705 = Identity(%onnx::Conv_687)
%onnx::Conv_702 = Identity(%onnx::Conv_681)
%onnx::Conv_699 = Identity(%onnx::Conv_681)
%onnx::Conv_696 = Identity(%onnx::Conv_687)
%onnx::Conv_693 = Identity(%onnx::Conv_681)
%onnx::Conv_690 = Identity(%onnx::Conv_681)
%onnx::Conv_684 = Identity(%onnx::Conv_681)
%onnx::Conv_678 = Identity(%onnx::Conv_660)
%onnx::Conv_675 = Identity(%onnx::Conv_654)
%onnx::Conv_672 = Identity(%onnx::Conv_654)
%onnx::Conv_669 = Identity(%onnx::Conv_660)
%onnx::Conv_666 = Identity(%onnx::Conv_654)
%onnx::Conv_663 = 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_650, %onnx::Conv_651)
%/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_653, %onnx::Conv_654)
%/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_656, %onnx::Conv_657)
%/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 = <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/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_659, %onnx::Conv_660)
%/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 = <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_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_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/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_662, %onnx::Conv_663)
%/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_665, %onnx::Conv_666)
%/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 = <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/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_668, %onnx::Conv_669)
%/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 = <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_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_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/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_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/conv1x1/conv_bn_relu/conv_bn_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_674, %onnx::Conv_675)
%/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 = <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/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_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/Constant_8_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_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_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/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_680, %onnx::Conv_681)
%/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_683, %onnx::Conv_684)
%/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 = <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/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/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/conv1x1/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/conv3x3/conv_bn_relu/conv_bn_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_686, %onnx::Conv_687)
%/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_4_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/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/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_689, %onnx::Conv_690)
%/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_692, %onnx::Conv_693)
%/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 = <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/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/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/conv1x1/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/conv3x3/conv_bn_relu/conv_bn_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.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_4_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/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/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_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 = <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/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/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/conv1x1/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/conv3x3/conv_bn_relu/conv_bn_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_704, %onnx::Conv_705)
%/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_4_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/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/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_707, %onnx::Conv_708)
%/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_710, %onnx::Conv_711)
%/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 = <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/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_713, %onnx::Conv_714)
%/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 = <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_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_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/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_716, %onnx::Conv_717)
%/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_719, %onnx::Conv_720)
%/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 = <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/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_722, %onnx::Conv_723)
%/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 = <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_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_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/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_725, %onnx::Conv_726)
%/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_728, %onnx::Conv_729)
%/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 = <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/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_731, %onnx::Conv_732)
%/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 = <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_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_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/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)
%648 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %648
}
|
val_accuracy
| 88.361377
| 434,909,568
| 1,443,117
|
{'zcp_epe_nas': 144.90279640459144, 'zcp_fisher': 29.12883758544922, 'zcp_flops': 6958553088.0, 'zcp_grad_norm': 110.31996154785156, 'zcp_grasp': 17.322265625, 'zcp_jacov': -16.05858366762441, 'zcp_l2_norm': 443.96319580078125, 'zcp_nwot': 208.89224798531706, 'zcp_params': 1443117.0, 'zcp_plain': -0.06956768035888601, 'zcp_snip': 457.708984375, 'zcp_synflow': 79.22523162021285, 'zcp_zen': 47.32115936279297, 'zcp_val_accuracy': 0.915765225887298}
| |
NASBench101_38935
|
NASBench101
|
38935
|
179d5156030809106c0490a721b107f6
|
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, 32x128x1x1]
%onnx::Conv_756[FLOAT, 32]
%onnx::Conv_758[FLOAT, 32x32x1x1]
%onnx::Conv_761[FLOAT, 32x32x1x1]
%onnx::Conv_764[FLOAT, 32x32x3x3]
%onnx::Conv_767[FLOAT, 32x32x3x3]
%onnx::Conv_770[FLOAT, 32x128x1x1]
%onnx::Conv_773[FLOAT, 32x32x1x1]
%onnx::Conv_776[FLOAT, 32x32x1x1]
%onnx::Conv_779[FLOAT, 32x32x3x3]
%onnx::Conv_782[FLOAT, 32x32x3x3]
%onnx::Conv_785[FLOAT, 32x128x1x1]
%onnx::Conv_788[FLOAT, 32x32x1x1]
%onnx::Conv_791[FLOAT, 32x32x1x1]
%onnx::Conv_794[FLOAT, 32x32x3x3]
%onnx::Conv_797[FLOAT, 32x32x3x3]
%onnx::Conv_800[FLOAT, 64x128x1x1]
%onnx::Conv_801[FLOAT, 64]
%onnx::Conv_803[FLOAT, 64x64x1x1]
%onnx::Conv_806[FLOAT, 64x64x1x1]
%onnx::Conv_809[FLOAT, 64x64x3x3]
%onnx::Conv_812[FLOAT, 64x64x3x3]
%onnx::Conv_815[FLOAT, 64x256x1x1]
%onnx::Conv_818[FLOAT, 64x64x1x1]
%onnx::Conv_821[FLOAT, 64x64x1x1]
%onnx::Conv_824[FLOAT, 64x64x3x3]
%onnx::Conv_827[FLOAT, 64x64x3x3]
%onnx::Conv_830[FLOAT, 64x256x1x1]
%onnx::Conv_833[FLOAT, 64x64x1x1]
%onnx::Conv_836[FLOAT, 64x64x1x1]
%onnx::Conv_839[FLOAT, 64x64x3x3]
%onnx::Conv_842[FLOAT, 64x64x3x3]
%onnx::Conv_845[FLOAT, 128x256x1x1]
%onnx::Conv_848[FLOAT, 128x128x1x1]
%onnx::Conv_851[FLOAT, 128x128x1x1]
%onnx::Conv_854[FLOAT, 128x128x3x3]
%onnx::Conv_857[FLOAT, 128x128x3x3]
%onnx::Conv_860[FLOAT, 128x512x1x1]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%onnx::Conv_866[FLOAT, 128x128x1x1]
%onnx::Conv_869[FLOAT, 128x128x3x3]
%onnx::Conv_872[FLOAT, 128x128x3x3]
%onnx::Conv_875[FLOAT, 128x512x1x1]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 128x128x1x1]
%onnx::Conv_884[FLOAT, 128x128x3x3]
%onnx::Conv_887[FLOAT, 128x128x3x3]
) {
%onnx::Conv_888 = Identity(%onnx::Conv_753)
%onnx::Conv_885 = Identity(%onnx::Conv_753)
%onnx::Conv_882 = Identity(%onnx::Conv_753)
%onnx::Conv_879 = Identity(%onnx::Conv_753)
%onnx::Conv_876 = Identity(%onnx::Conv_753)
%onnx::Conv_873 = Identity(%onnx::Conv_753)
%onnx::Conv_870 = Identity(%onnx::Conv_753)
%onnx::Conv_867 = Identity(%onnx::Conv_753)
%onnx::Conv_864 = Identity(%onnx::Conv_753)
%onnx::Conv_861 = Identity(%onnx::Conv_753)
%onnx::Conv_858 = Identity(%onnx::Conv_753)
%onnx::Conv_855 = Identity(%onnx::Conv_753)
%onnx::Conv_852 = Identity(%onnx::Conv_753)
%onnx::Conv_849 = Identity(%onnx::Conv_753)
%onnx::Conv_846 = Identity(%onnx::Conv_753)
%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_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/conv1x1/conv_bn_relu/conv_bn_relu.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/conv1x1/conv_bn_relu/conv_bn_relu.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.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/conv3x3/conv_bn_relu/conv_bn_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.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/conv3x3/conv_bn_relu/conv_bn_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_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.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.2/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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/conv1x1/conv_bn_relu/conv_bn_relu.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.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/conv3x3/conv_bn_relu/conv_bn_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.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/conv3x3/conv_bn_relu/conv_bn_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_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.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.2/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/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/conv1x1/conv_bn_relu/conv_bn_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/conv1x1/conv_bn_relu/conv_bn_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.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/conv3x3/conv_bn_relu/conv_bn_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.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/conv3x3/conv_bn_relu/conv_bn_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_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.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.2/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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/conv1x1/conv_bn_relu/conv_bn_relu.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.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/conv3x3/conv_bn_relu/conv_bn_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.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/conv3x3/conv_bn_relu/conv_bn_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_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.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.2/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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/conv1x1/conv_bn_relu/conv_bn_relu.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.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/conv3x3/conv_bn_relu/conv_bn_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.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/conv3x3/conv_bn_relu/conv_bn_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_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.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.2/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/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/conv1x1/conv_bn_relu/conv_bn_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/conv1x1/conv_bn_relu/conv_bn_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.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/conv3x3/conv_bn_relu/conv_bn_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.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/conv3x3/conv_bn_relu/conv_bn_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_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.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.2/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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/conv1x1/conv_bn_relu/conv_bn_relu.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.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/conv3x3/conv_bn_relu/conv_bn_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.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/conv3x3/conv_bn_relu/conv_bn_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_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.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.2/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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/conv1x1/conv_bn_relu/conv_bn_relu.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.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/conv3x3/conv_bn_relu/conv_bn_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.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/conv3x3/conv_bn_relu/conv_bn_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_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.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.2/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/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/conv1x1/conv_bn_relu/conv_bn_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/conv1x1/conv_bn_relu/conv_bn_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.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/conv3x3/conv_bn_relu/conv_bn_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.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/conv3x3/conv_bn_relu/conv_bn_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_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.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.2/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/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
| 90.594953
| 459,614,208
| 1,522,890
|
{'zcp_epe_nas': 86.56307851295824, 'zcp_fisher': 69.93891143798828, 'zcp_flops': 7353827328.0, 'zcp_grad_norm': 157.84732055664062, 'zcp_grasp': -61.83349609375, 'zcp_jacov': -16.057398322022834, 'zcp_l2_norm': 623.0946655273438, 'zcp_nwot': 211.69390571314818, 'zcp_params': 1522890.0, 'zcp_plain': -0.024757532402873, 'zcp_snip': 615.7283935546875, 'zcp_synflow': 105.10984569834586, 'zcp_zen': 70.67900848388672, 'zcp_val_accuracy': 0.9231770634651181}
| |
NASBench101_326678
|
NASBench101
|
326678
|
c59cc8d473488a624abc31872c13a467
|
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, 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, 128x128x1x1]
%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, 128x128x1x1]
%onnx::Conv_935[FLOAT, 128x128x1x1]
%onnx::Conv_938[FLOAT, 128x128x1x1]
%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, 256x256x1x1]
%onnx::Conv_956[FLOAT, 256x128x1x1]
%onnx::Conv_959[FLOAT, 256x256x1x1]
%onnx::Conv_962[FLOAT, 256x256x1x1]
%onnx::Conv_965[FLOAT, 256x256x1x1]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%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, 256x256x1x1]
%onnx::Conv_989[FLOAT, 256x256x1x1]
%onnx::Conv_992[FLOAT, 256x256x1x1]
%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, 512x512x1x1]
%onnx::Conv_1010[FLOAT, 512x256x1x1]
%onnx::Conv_1013[FLOAT, 512x512x1x1]
%onnx::Conv_1016[FLOAT, 512x512x1x1]
%onnx::Conv_1019[FLOAT, 512x512x1x1]
%onnx::Conv_1022[FLOAT, 512x512x1x1]
%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, 512x512x1x1]
%onnx::Conv_1043[FLOAT, 512x512x1x1]
%onnx::Conv_1046[FLOAT, 512x512x1x1]
%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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_902, %onnx::Conv_903)
%/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/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 = <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/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_920, %onnx::Conv_921)
%/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/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 = <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/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/conv1x1/conv_bn_relu/conv_bn_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.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_938, %onnx::Conv_939)
%/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/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 = <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/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_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_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_956, %onnx::Conv_957)
%/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/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_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/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_974, %onnx::Conv_975)
%/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/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_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/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/conv1x1/conv_bn_relu/conv_bn_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.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_992, %onnx::Conv_993)
%/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/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_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/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_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_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_1010, %onnx::Conv_1011)
%/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/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 = <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/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_1028, %onnx::Conv_1029)
%/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/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 = <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/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/conv1x1/conv_bn_relu/conv_bn_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.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_1046, %onnx::Conv_1047)
%/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/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 = <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/conv1x1/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/conv1x1/conv_bn_relu/conv_bn_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_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)
%/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)
%885 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %885
}
|
val_accuracy
| 84.795672
| 1,785,997,312
| 5,906,570
|
{'zcp_epe_nas': 114.0691978266897, 'zcp_fisher': 99.49354553222656, 'zcp_flops': 28575956992.0, 'zcp_grad_norm': 214.33346557617188, 'zcp_grasp': 68.71240234375, 'zcp_jacov': -16.039385422448113, 'zcp_l2_norm': 1242.4803466796875, 'zcp_nwot': 235.48268683982175, 'zcp_params': 5906570.0, 'zcp_plain': 0.010577196255326, 'zcp_snip': 1453.2470703125, 'zcp_synflow': 136.80739790124048, 'zcp_zen': 92.73822021484375, 'zcp_val_accuracy': 0.9170672893524171}
| |
NASBench101_240082
|
NASBench101
|
240082
|
914fe0e2391af4f96aeea57abecf0b5f
|
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, 64x64x3x3]
%onnx::Conv_662[FLOAT, 64x128x1x1]
%onnx::Conv_665[FLOAT, 64x64x1x1]
%onnx::Conv_668[FLOAT, 64x128x1x1]
%onnx::Conv_671[FLOAT, 64x64x3x3]
%onnx::Conv_674[FLOAT, 64x128x1x1]
%onnx::Conv_677[FLOAT, 64x64x1x1]
%onnx::Conv_680[FLOAT, 64x128x1x1]
%onnx::Conv_683[FLOAT, 64x64x3x3]
%onnx::Conv_686[FLOAT, 64x128x1x1]
%onnx::Conv_689[FLOAT, 64x64x1x1]
%onnx::Conv_692[FLOAT, 128x128x1x1]
%onnx::Conv_695[FLOAT, 128x128x3x3]
%onnx::Conv_698[FLOAT, 128x128x1x1]
%onnx::Conv_701[FLOAT, 128x128x1x1]
%onnx::Conv_704[FLOAT, 128x256x1x1]
%onnx::Conv_707[FLOAT, 128x128x3x3]
%onnx::Conv_710[FLOAT, 128x256x1x1]
%onnx::Conv_713[FLOAT, 128x128x1x1]
%onnx::Conv_716[FLOAT, 128x256x1x1]
%onnx::Conv_719[FLOAT, 128x128x3x3]
%onnx::Conv_722[FLOAT, 128x256x1x1]
%onnx::Conv_725[FLOAT, 128x128x1x1]
%onnx::Conv_728[FLOAT, 256x256x1x1]
%onnx::Conv_729[FLOAT, 256]
%onnx::Conv_731[FLOAT, 256x256x3x3]
%onnx::Conv_734[FLOAT, 256x256x1x1]
%onnx::Conv_737[FLOAT, 256x256x1x1]
%onnx::Conv_740[FLOAT, 256x512x1x1]
%onnx::Conv_743[FLOAT, 256x256x3x3]
%onnx::Conv_746[FLOAT, 256x512x1x1]
%onnx::Conv_749[FLOAT, 256x256x1x1]
%onnx::Conv_752[FLOAT, 256x512x1x1]
%onnx::Conv_755[FLOAT, 256x256x3x3]
%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/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/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/Add_1_output_0 = Add(%/layers.1/vertex_op.1/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_1_output_0, %onnx::Conv_659, %onnx::Conv_660)
%/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_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/Constant_1_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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/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/Add_1_output_0 = Add(%/layers.2/vertex_op.1/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_1_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/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_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/Constant_1_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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/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/Add_1_output_0 = Add(%/layers.3/vertex_op.1/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_1_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/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_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/Constant_1_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_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/conv1x1/conv_bn_relu/conv_bn_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/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_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/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/Add_1_output_0 = Add(%/layers.5/vertex_op.1/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_1_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/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_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/Constant_1_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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/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/Add_1_output_0 = Add(%/layers.6/vertex_op.1/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_1_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/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_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/Constant_1_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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/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/Add_1_output_0 = Add(%/layers.7/vertex_op.1/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_1_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/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_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/Constant_1_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_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/conv1x1/conv_bn_relu/conv_bn_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/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_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/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/Add_1_output_0 = Add(%/layers.9/vertex_op.1/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_1_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/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_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/Constant_1_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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/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/Add_1_output_0 = Add(%/layers.10/vertex_op.1/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_1_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/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_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/Constant_1_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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/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/Add_1_output_0 = Add(%/layers.11/vertex_op.1/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_1_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/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_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/Constant_1_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_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/conv1x1/conv_bn_relu/conv_bn_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/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)
%651 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %651
}
|
val_accuracy
| 90.314502
| 1,042,556,928
| 3,468,426
|
{'zcp_epe_nas': 106.2069925572392, 'zcp_fisher': 3.62886118888855, 'zcp_flops': 16680910848.0, 'zcp_grad_norm': 35.831268310546875, 'zcp_grasp': -1.244033813476562, 'zcp_jacov': -16.03982325546317, 'zcp_l2_norm': 694.381591796875, 'zcp_nwot': 217.84899516829353, 'zcp_params': 3468426.0, 'zcp_plain': 0.086360089480876, 'zcp_snip': 230.18251037597656, 'zcp_synflow': 90.40262672568063, 'zcp_zen': 73.54469299316406, 'zcp_val_accuracy': 0.8890224099159241}
| |
NASBench101_220064
|
NASBench101
|
220064
|
855e77f49496db27a1e1f9d3d5bd57f6
|
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, 128x128x3x3]
%onnx::Conv_980[FLOAT, 128x128x1x1]
%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, 128x128x3x3]
%onnx::Conv_1001[FLOAT, 128x128x1x1]
%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, 128x128x3x3]
%onnx::Conv_1022[FLOAT, 128x128x1x1]
%onnx::Conv_1025[FLOAT, 256x128x1x1]
%onnx::Conv_1026[FLOAT, 256]
%onnx::Conv_1028[FLOAT, 256x256x3x3]
%onnx::Conv_1031[FLOAT, 256x256x1x1]
%onnx::Conv_1034[FLOAT, 256x128x1x1]
%onnx::Conv_1037[FLOAT, 256x128x1x1]
%onnx::Conv_1040[FLOAT, 256x256x3x3]
%onnx::Conv_1043[FLOAT, 256x128x1x1]
%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, 256x256x3x3]
%onnx::Conv_1064[FLOAT, 256x256x1x1]
%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, 256x256x3x3]
%onnx::Conv_1085[FLOAT, 256x256x1x1]
%onnx::Conv_1088[FLOAT, 512x256x1x1]
%onnx::Conv_1089[FLOAT, 512]
%onnx::Conv_1091[FLOAT, 512x512x3x3]
%onnx::Conv_1094[FLOAT, 512x512x1x1]
%onnx::Conv_1097[FLOAT, 512x256x1x1]
%onnx::Conv_1100[FLOAT, 512x256x1x1]
%onnx::Conv_1103[FLOAT, 512x512x3x3]
%onnx::Conv_1106[FLOAT, 512x256x1x1]
%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, 512x512x3x3]
%onnx::Conv_1127[FLOAT, 512x512x1x1]
%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, 512x512x3x3]
%onnx::Conv_1148[FLOAT, 512x512x1x1]
) {
%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/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_968, %onnx::Conv_969)
%/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_971, %onnx::Conv_972)
%/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/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_974, %onnx::Conv_975)
%/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/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_4_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/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_980, %onnx::Conv_981)
%/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/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_5_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/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_989, %onnx::Conv_990)
%/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/Add_5_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/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/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_995, %onnx::Conv_996)
%/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/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_4_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/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_5_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/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/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_5_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/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_1010, %onnx::Conv_1011)
%/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/Add_5_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/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/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_1016, %onnx::Conv_1017)
%/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/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_4_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/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_5_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/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/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_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_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/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_1031, %onnx::Conv_1032)
%/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_1034, %onnx::Conv_1035)
%/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/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_1037, %onnx::Conv_1038)
%/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/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_4_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/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_1043, %onnx::Conv_1044)
%/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/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_5_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/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_1052, %onnx::Conv_1053)
%/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/Add_5_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/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/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_1058, %onnx::Conv_1059)
%/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/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_4_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/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_5_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/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/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_5_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/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_1073, %onnx::Conv_1074)
%/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/Add_5_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/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/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_1079, %onnx::Conv_1080)
%/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/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_4_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/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_5_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/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/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_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_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/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_1094, %onnx::Conv_1095)
%/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_1097, %onnx::Conv_1098)
%/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/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_1100, %onnx::Conv_1101)
%/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/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_4_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/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_1106, %onnx::Conv_1107)
%/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/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_5_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/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_1115, %onnx::Conv_1116)
%/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/Add_5_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/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/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_1121, %onnx::Conv_1122)
%/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/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_4_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/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_5_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/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/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_5_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/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_1136, %onnx::Conv_1137)
%/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/Add_5_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/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/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_1142, %onnx::Conv_1143)
%/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/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_4_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/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_5_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/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/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_5_output_0)
%957 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %957
}
|
val_accuracy
| 93.679887
| 6,858,221,568
| 23,131,530
|
{'zcp_epe_nas': 84.25923008532396, 'zcp_fisher': 9.033373832702637, 'zcp_flops': 109731545088.0, 'zcp_grad_norm': 61.95002746582031, 'zcp_grasp': 0.032455444335937, 'zcp_jacov': -16.056667315903987, 'zcp_l2_norm': 1422.351318359375, 'zcp_nwot': 236.74603736317647, 'zcp_params': 23131530.0, 'zcp_plain': -0.018711188808083, 'zcp_snip': 563.062744140625, 'zcp_synflow': 129.63237159826022, 'zcp_zen': 132.68870544433594, 'zcp_val_accuracy': 0.882512032985687}
| |
NASBench101_391461
|
NASBench101
|
391461
|
eca0a10a8aea15d13c237bf90bb32763
|
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, 64x128x1x1]
%onnx::Conv_954[FLOAT, 64]
%onnx::Conv_956[FLOAT, 64x64x3x3]
%onnx::Conv_959[FLOAT, 64x128x1x1]
%onnx::Conv_962[FLOAT, 64x64x1x1]
%onnx::Conv_965[FLOAT, 64x128x1x1]
%onnx::Conv_968[FLOAT, 64x64x3x3]
%onnx::Conv_971[FLOAT, 64x64x1x1]
%onnx::Conv_974[FLOAT, 64x128x1x1]
%onnx::Conv_977[FLOAT, 64x64x3x3]
%onnx::Conv_980[FLOAT, 64x128x1x1]
%onnx::Conv_983[FLOAT, 64x64x1x1]
%onnx::Conv_986[FLOAT, 64x128x1x1]
%onnx::Conv_989[FLOAT, 64x64x3x3]
%onnx::Conv_992[FLOAT, 64x64x1x1]
%onnx::Conv_995[FLOAT, 64x128x1x1]
%onnx::Conv_998[FLOAT, 64x64x3x3]
%onnx::Conv_1001[FLOAT, 64x128x1x1]
%onnx::Conv_1004[FLOAT, 64x64x1x1]
%onnx::Conv_1007[FLOAT, 64x128x1x1]
%onnx::Conv_1010[FLOAT, 64x64x3x3]
%onnx::Conv_1013[FLOAT, 64x64x1x1]
%onnx::Conv_1016[FLOAT, 128x128x1x1]
%onnx::Conv_1019[FLOAT, 128x128x3x3]
%onnx::Conv_1022[FLOAT, 128x128x1x1]
%onnx::Conv_1025[FLOAT, 128x128x1x1]
%onnx::Conv_1028[FLOAT, 128x128x1x1]
%onnx::Conv_1031[FLOAT, 128x128x3x3]
%onnx::Conv_1034[FLOAT, 128x128x1x1]
%onnx::Conv_1037[FLOAT, 128x256x1x1]
%onnx::Conv_1040[FLOAT, 128x128x3x3]
%onnx::Conv_1043[FLOAT, 128x256x1x1]
%onnx::Conv_1046[FLOAT, 128x128x1x1]
%onnx::Conv_1049[FLOAT, 128x256x1x1]
%onnx::Conv_1052[FLOAT, 128x128x3x3]
%onnx::Conv_1055[FLOAT, 128x128x1x1]
%onnx::Conv_1058[FLOAT, 128x256x1x1]
%onnx::Conv_1061[FLOAT, 128x128x3x3]
%onnx::Conv_1064[FLOAT, 128x256x1x1]
%onnx::Conv_1067[FLOAT, 128x128x1x1]
%onnx::Conv_1070[FLOAT, 128x256x1x1]
%onnx::Conv_1073[FLOAT, 128x128x3x3]
%onnx::Conv_1076[FLOAT, 128x128x1x1]
%onnx::Conv_1079[FLOAT, 256x256x1x1]
%onnx::Conv_1080[FLOAT, 256]
%onnx::Conv_1082[FLOAT, 256x256x3x3]
%onnx::Conv_1085[FLOAT, 256x256x1x1]
%onnx::Conv_1088[FLOAT, 256x256x1x1]
%onnx::Conv_1091[FLOAT, 256x256x1x1]
%onnx::Conv_1094[FLOAT, 256x256x3x3]
%onnx::Conv_1097[FLOAT, 256x256x1x1]
%onnx::Conv_1100[FLOAT, 256x512x1x1]
%onnx::Conv_1103[FLOAT, 256x256x3x3]
%onnx::Conv_1106[FLOAT, 256x512x1x1]
%onnx::Conv_1109[FLOAT, 256x256x1x1]
%onnx::Conv_1112[FLOAT, 256x512x1x1]
%onnx::Conv_1115[FLOAT, 256x256x3x3]
%onnx::Conv_1118[FLOAT, 256x256x1x1]
%onnx::Conv_1121[FLOAT, 256x512x1x1]
%onnx::Conv_1124[FLOAT, 256x256x3x3]
%onnx::Conv_1127[FLOAT, 256x512x1x1]
%onnx::Conv_1130[FLOAT, 256x256x1x1]
%onnx::Conv_1133[FLOAT, 256x512x1x1]
%onnx::Conv_1136[FLOAT, 256x256x3x3]
%onnx::Conv_1139[FLOAT, 256x256x1x1]
) {
%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_951)
%onnx::Conv_1074 = Identity(%onnx::Conv_951)
%onnx::Conv_1071 = Identity(%onnx::Conv_951)
%onnx::Conv_1068 = Identity(%onnx::Conv_951)
%onnx::Conv_1065 = Identity(%onnx::Conv_951)
%onnx::Conv_1062 = Identity(%onnx::Conv_951)
%onnx::Conv_1059 = Identity(%onnx::Conv_951)
%onnx::Conv_1056 = Identity(%onnx::Conv_951)
%onnx::Conv_1053 = Identity(%onnx::Conv_951)
%onnx::Conv_1050 = Identity(%onnx::Conv_951)
%onnx::Conv_1047 = Identity(%onnx::Conv_951)
%onnx::Conv_1044 = Identity(%onnx::Conv_951)
%onnx::Conv_1041 = Identity(%onnx::Conv_951)
%onnx::Conv_1038 = Identity(%onnx::Conv_951)
%onnx::Conv_1035 = Identity(%onnx::Conv_951)
%onnx::Conv_1032 = Identity(%onnx::Conv_951)
%onnx::Conv_1029 = Identity(%onnx::Conv_951)
%onnx::Conv_1026 = Identity(%onnx::Conv_951)
%onnx::Conv_1023 = Identity(%onnx::Conv_951)
%onnx::Conv_1020 = Identity(%onnx::Conv_951)
%onnx::Conv_1017 = Identity(%onnx::Conv_951)
%onnx::Conv_1014 = Identity(%onnx::Conv_954)
%onnx::Conv_1011 = Identity(%onnx::Conv_954)
%onnx::Conv_1008 = Identity(%onnx::Conv_954)
%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)
%/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/conv3x3/conv_bn_relu/conv_bn_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_956, %onnx::Conv_957)
%/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_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/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_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_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/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.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.2/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_971, %onnx::Conv_972)
%/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.3/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_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/conv3x3/conv_bn_relu/conv_bn_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_977, %onnx::Conv_978)
%/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_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/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_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/Concat_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_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/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.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.2/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_992, %onnx::Conv_993)
%/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.3/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_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/conv3x3/conv_bn_relu/conv_bn_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_998, %onnx::Conv_999)
%/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_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/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_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/Concat_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_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/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.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.2/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_1013, %onnx::Conv_1014)
%/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.3/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_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/conv3x3/conv_bn_relu/conv_bn_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_1019, %onnx::Conv_1020)
%/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_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/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_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_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/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.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.2/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_1034, %onnx::Conv_1035)
%/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.3/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_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/conv3x3/conv_bn_relu/conv_bn_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_1040, %onnx::Conv_1041)
%/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_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/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_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/Concat_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_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/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.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.2/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_1055, %onnx::Conv_1056)
%/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.3/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_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/conv3x3/conv_bn_relu/conv_bn_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_1061, %onnx::Conv_1062)
%/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_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/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_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/Concat_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_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/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.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.2/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_1076, %onnx::Conv_1077)
%/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.3/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_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/conv3x3/conv_bn_relu/conv_bn_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_1082, %onnx::Conv_1083)
%/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_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/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_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_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/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.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.2/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_1097, %onnx::Conv_1098)
%/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.3/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_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/conv3x3/conv_bn_relu/conv_bn_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_1103, %onnx::Conv_1104)
%/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_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/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_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/Concat_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_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/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.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.2/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_1118, %onnx::Conv_1119)
%/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.3/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_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/conv3x3/conv_bn_relu/conv_bn_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_1124, %onnx::Conv_1125)
%/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_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/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_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/Concat_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_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/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.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.2/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_1139, %onnx::Conv_1140)
%/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.3/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)
%948 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %948
}
|
val_accuracy
| 93.85016
| 1,940,006,912
| 6,491,146
|
{'zcp_epe_nas': 70.5527462151197, 'zcp_fisher': 2.8087658882141113, 'zcp_flops': 31040110592.0, 'zcp_grad_norm': 40.23139572143555, 'zcp_grasp': -0.17916870117187503, 'zcp_jacov': -16.06463382206519, 'zcp_l2_norm': 1189.9088134765625, 'zcp_nwot': 226.5144678594452, 'zcp_params': 6491146.0, 'zcp_plain': -0.010205627419054, 'zcp_snip': 248.71971130371094, 'zcp_synflow': 98.77638162930857, 'zcp_zen': 110.61852264404297, 'zcp_val_accuracy': 0.8470553159713741}
| |
NASBench101_57072
|
NASBench101
|
57072
|
22b73114fb375d4d5583ca9f8c68c5a8
|
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, 64x64x3x3]
%onnx::Conv_812[FLOAT, 64x128x1x1]
%onnx::Conv_815[FLOAT, 64x128x1x1]
%onnx::Conv_818[FLOAT, 64x64x1x1]
%onnx::Conv_821[FLOAT, 64x64x1x1]
%onnx::Conv_824[FLOAT, 64x64x3x3]
%onnx::Conv_827[FLOAT, 64x128x1x1]
%onnx::Conv_830[FLOAT, 64x128x1x1]
%onnx::Conv_833[FLOAT, 64x64x1x1]
%onnx::Conv_836[FLOAT, 64x64x1x1]
%onnx::Conv_839[FLOAT, 64x64x3x3]
%onnx::Conv_842[FLOAT, 64x128x1x1]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x1x1]
%onnx::Conv_851[FLOAT, 128x128x1x1]
%onnx::Conv_854[FLOAT, 128x128x3x3]
%onnx::Conv_857[FLOAT, 128x128x1x1]
%onnx::Conv_860[FLOAT, 128x256x1x1]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%onnx::Conv_866[FLOAT, 128x128x1x1]
%onnx::Conv_869[FLOAT, 128x128x3x3]
%onnx::Conv_872[FLOAT, 128x256x1x1]
%onnx::Conv_875[FLOAT, 128x256x1x1]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 128x128x1x1]
%onnx::Conv_884[FLOAT, 128x128x3x3]
%onnx::Conv_887[FLOAT, 128x256x1x1]
%onnx::Conv_890[FLOAT, 256x256x1x1]
%onnx::Conv_891[FLOAT, 256]
%onnx::Conv_893[FLOAT, 256x256x1x1]
%onnx::Conv_896[FLOAT, 256x256x1x1]
%onnx::Conv_899[FLOAT, 256x256x3x3]
%onnx::Conv_902[FLOAT, 256x256x1x1]
%onnx::Conv_905[FLOAT, 256x512x1x1]
%onnx::Conv_908[FLOAT, 256x256x1x1]
%onnx::Conv_911[FLOAT, 256x256x1x1]
%onnx::Conv_914[FLOAT, 256x256x3x3]
%onnx::Conv_917[FLOAT, 256x512x1x1]
%onnx::Conv_920[FLOAT, 256x512x1x1]
%onnx::Conv_923[FLOAT, 256x256x1x1]
%onnx::Conv_926[FLOAT, 256x256x1x1]
%onnx::Conv_929[FLOAT, 256x256x3x3]
%onnx::Conv_932[FLOAT, 256x512x1x1]
) {
%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.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_809, %onnx::Conv_810)
%/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/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_812, %onnx::Conv_813)
%/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_4_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_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/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.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_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.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_824, %onnx::Conv_825)
%/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/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_827, %onnx::Conv_828)
%/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_4_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_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/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.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_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.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_839, %onnx::Conv_840)
%/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/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_842, %onnx::Conv_843)
%/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_4_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_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/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.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_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.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_854, %onnx::Conv_855)
%/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/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_857, %onnx::Conv_858)
%/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_4_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_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/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.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_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.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_869, %onnx::Conv_870)
%/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/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_872, %onnx::Conv_873)
%/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_4_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_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/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.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_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.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_884, %onnx::Conv_885)
%/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/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_887, %onnx::Conv_888)
%/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_4_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_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/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.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_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.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_899, %onnx::Conv_900)
%/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/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_902, %onnx::Conv_903)
%/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_4_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_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/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.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_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.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_914, %onnx::Conv_915)
%/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/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_917, %onnx::Conv_918)
%/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_4_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_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/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.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_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.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_929, %onnx::Conv_930)
%/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/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_932, %onnx::Conv_933)
%/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_4_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_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/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.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)
%795 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %795
}
|
val_accuracy
| 89.853764
| 1,120,806,912
| 3,729,162
|
{'zcp_epe_nas': 102.78278672742826, 'zcp_fisher': 777.41162109375, 'zcp_flops': 17932910592.0, 'zcp_grad_norm': 465.6590270996094, 'zcp_grasp': -742.31640625, 'zcp_jacov': -16.044720535083165, 'zcp_l2_norm': 844.2869873046875, 'zcp_nwot': 222.02602805444093, 'zcp_params': 3729162.0, 'zcp_plain': 0.125708028674125, 'zcp_snip': 2539.6318359375, 'zcp_synflow': 113.54531441170923, 'zcp_zen': 79.6166763305664, 'zcp_val_accuracy': 0.9188702106475831}
| |
NASBench101_309397
|
NASBench101
|
309397
|
bb3590f810221ddd384479d644aa9ef3
|
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, 128x128x1x1]
%onnx::Conv_677[FLOAT, 128x128x1x1]
%onnx::Conv_680[FLOAT, 128x128x1x1]
%onnx::Conv_683[FLOAT, 128x128x3x3]
%onnx::Conv_686[FLOAT, 128x128x1x1]
%onnx::Conv_689[FLOAT, 128x128x1x1]
%onnx::Conv_692[FLOAT, 128x128x1x1]
%onnx::Conv_695[FLOAT, 128x128x3x3]
%onnx::Conv_698[FLOAT, 128x128x1x1]
%onnx::Conv_701[FLOAT, 128x128x1x1]
%onnx::Conv_704[FLOAT, 128x128x1x1]
%onnx::Conv_707[FLOAT, 128x128x3x3]
%onnx::Conv_710[FLOAT, 256x128x1x1]
%onnx::Conv_711[FLOAT, 256]
%onnx::Conv_713[FLOAT, 256x256x1x1]
%onnx::Conv_716[FLOAT, 256x128x1x1]
%onnx::Conv_719[FLOAT, 256x256x3x3]
%onnx::Conv_722[FLOAT, 256x256x1x1]
%onnx::Conv_725[FLOAT, 256x256x1x1]
%onnx::Conv_728[FLOAT, 256x256x1x1]
%onnx::Conv_731[FLOAT, 256x256x3x3]
%onnx::Conv_734[FLOAT, 256x256x1x1]
%onnx::Conv_737[FLOAT, 256x256x1x1]
%onnx::Conv_740[FLOAT, 256x256x1x1]
%onnx::Conv_743[FLOAT, 256x256x3x3]
%onnx::Conv_746[FLOAT, 512x256x1x1]
%onnx::Conv_747[FLOAT, 512]
%onnx::Conv_749[FLOAT, 512x512x1x1]
%onnx::Conv_752[FLOAT, 512x256x1x1]
%onnx::Conv_755[FLOAT, 512x512x3x3]
%onnx::Conv_758[FLOAT, 512x512x1x1]
%onnx::Conv_761[FLOAT, 512x512x1x1]
%onnx::Conv_764[FLOAT, 512x512x1x1]
%onnx::Conv_767[FLOAT, 512x512x3x3]
%onnx::Conv_770[FLOAT, 512x512x1x1]
%onnx::Conv_773[FLOAT, 512x512x1x1]
%onnx::Conv_776[FLOAT, 512x512x1x1]
%onnx::Conv_779[FLOAT, 512x512x3x3]
) {
%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_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_672)
%onnx::Conv_705 = Identity(%onnx::Conv_672)
%onnx::Conv_702 = Identity(%onnx::Conv_672)
%onnx::Conv_699 = Identity(%onnx::Conv_672)
%onnx::Conv_696 = Identity(%onnx::Conv_672)
%onnx::Conv_693 = Identity(%onnx::Conv_672)
%onnx::Conv_690 = Identity(%onnx::Conv_672)
%onnx::Conv_687 = Identity(%onnx::Conv_672)
%onnx::Conv_684 = Identity(%onnx::Conv_672)
%onnx::Conv_681 = Identity(%onnx::Conv_672)
%onnx::Conv_678 = Identity(%onnx::Conv_672)
%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_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/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_680, %onnx::Conv_681)
%/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/maxpool/MaxPool_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/Add_5_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/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/conv3x3/conv_bn_relu/conv_bn_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_683, %onnx::Conv_684)
%/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_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/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/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/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/maxpool/MaxPool_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/Add_5_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/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/conv3x3/conv_bn_relu/conv_bn_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_695, %onnx::Conv_696)
%/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_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/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/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/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/maxpool/MaxPool_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/Add_5_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/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/conv3x3/conv_bn_relu/conv_bn_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_707, %onnx::Conv_708)
%/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_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/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_716, %onnx::Conv_717)
%/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/vertex_op.2/maxpool/MaxPool_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/Add_5_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_5_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_719, %onnx::Conv_720)
%/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_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/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/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/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/vertex_op.2/maxpool/MaxPool_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/Add_5_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_5_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_731, %onnx::Conv_732)
%/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_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/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/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/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/vertex_op.2/maxpool/MaxPool_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/Add_5_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_5_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_743, %onnx::Conv_744)
%/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_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/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_752, %onnx::Conv_753)
%/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/maxpool/MaxPool_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/Add_5_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/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/conv3x3/conv_bn_relu/conv_bn_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_755, %onnx::Conv_756)
%/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_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/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/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/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/maxpool/MaxPool_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/Add_5_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/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/conv3x3/conv_bn_relu/conv_bn_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_767, %onnx::Conv_768)
%/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_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/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/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/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/maxpool/MaxPool_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/Add_5_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/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/conv3x3/conv_bn_relu/conv_bn_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_779, %onnx::Conv_780)
%/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)
%669 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %669
}
|
val_accuracy
| 89.783657
| 3,586,926,592
| 12,088,970
|
{'zcp_epe_nas': 71.58097123508131, 'zcp_fisher': 51.5639762878418, 'zcp_flops': 57390825472.0, 'zcp_grad_norm': 96.04783630371094, 'zcp_grasp': 7.39404296875, 'zcp_jacov': -16.049081133819506, 'zcp_l2_norm': 817.9445190429688, 'zcp_nwot': 227.75117896487112, 'zcp_params': 12088970.0, 'zcp_plain': -0.010097218677401001, 'zcp_snip': 819.9092407226562, 'zcp_synflow': 103.43160070042777, 'zcp_zen': 80.80168151855469, 'zcp_val_accuracy': 0.911959111690521}
| |
NASBench101_367308
|
NASBench101
|
367308
|
de15b23465fcd1eeb3b87c2068143e4b
|
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, 64x128x1x1]
%onnx::Conv_954[FLOAT, 64]
%onnx::Conv_956[FLOAT, 64x64x3x3]
%onnx::Conv_959[FLOAT, 64x128x1x1]
%onnx::Conv_962[FLOAT, 64x64x3x3]
%onnx::Conv_965[FLOAT, 64x128x1x1]
%onnx::Conv_968[FLOAT, 64x64x3x3]
%onnx::Conv_971[FLOAT, 64x64x3x3]
%onnx::Conv_974[FLOAT, 64x128x1x1]
%onnx::Conv_977[FLOAT, 64x64x3x3]
%onnx::Conv_980[FLOAT, 64x128x1x1]
%onnx::Conv_983[FLOAT, 64x64x3x3]
%onnx::Conv_986[FLOAT, 64x128x1x1]
%onnx::Conv_989[FLOAT, 64x64x3x3]
%onnx::Conv_992[FLOAT, 64x64x3x3]
%onnx::Conv_995[FLOAT, 64x128x1x1]
%onnx::Conv_998[FLOAT, 64x64x3x3]
%onnx::Conv_1001[FLOAT, 64x128x1x1]
%onnx::Conv_1004[FLOAT, 64x64x3x3]
%onnx::Conv_1007[FLOAT, 64x128x1x1]
%onnx::Conv_1010[FLOAT, 64x64x3x3]
%onnx::Conv_1013[FLOAT, 64x64x3x3]
%onnx::Conv_1016[FLOAT, 128x128x1x1]
%onnx::Conv_1019[FLOAT, 128x128x3x3]
%onnx::Conv_1022[FLOAT, 128x128x1x1]
%onnx::Conv_1025[FLOAT, 128x128x3x3]
%onnx::Conv_1028[FLOAT, 128x128x1x1]
%onnx::Conv_1031[FLOAT, 128x128x3x3]
%onnx::Conv_1034[FLOAT, 128x128x3x3]
%onnx::Conv_1037[FLOAT, 128x256x1x1]
%onnx::Conv_1040[FLOAT, 128x128x3x3]
%onnx::Conv_1043[FLOAT, 128x256x1x1]
%onnx::Conv_1046[FLOAT, 128x128x3x3]
%onnx::Conv_1049[FLOAT, 128x256x1x1]
%onnx::Conv_1052[FLOAT, 128x128x3x3]
%onnx::Conv_1055[FLOAT, 128x128x3x3]
%onnx::Conv_1058[FLOAT, 128x256x1x1]
%onnx::Conv_1061[FLOAT, 128x128x3x3]
%onnx::Conv_1064[FLOAT, 128x256x1x1]
%onnx::Conv_1067[FLOAT, 128x128x3x3]
%onnx::Conv_1070[FLOAT, 128x256x1x1]
%onnx::Conv_1073[FLOAT, 128x128x3x3]
%onnx::Conv_1076[FLOAT, 128x128x3x3]
%onnx::Conv_1079[FLOAT, 256x256x1x1]
%onnx::Conv_1080[FLOAT, 256]
%onnx::Conv_1082[FLOAT, 256x256x3x3]
%onnx::Conv_1085[FLOAT, 256x256x1x1]
%onnx::Conv_1088[FLOAT, 256x256x3x3]
%onnx::Conv_1091[FLOAT, 256x256x1x1]
%onnx::Conv_1094[FLOAT, 256x256x3x3]
%onnx::Conv_1097[FLOAT, 256x256x3x3]
%onnx::Conv_1100[FLOAT, 256x512x1x1]
%onnx::Conv_1103[FLOAT, 256x256x3x3]
%onnx::Conv_1106[FLOAT, 256x512x1x1]
%onnx::Conv_1109[FLOAT, 256x256x3x3]
%onnx::Conv_1112[FLOAT, 256x512x1x1]
%onnx::Conv_1115[FLOAT, 256x256x3x3]
%onnx::Conv_1118[FLOAT, 256x256x3x3]
%onnx::Conv_1121[FLOAT, 256x512x1x1]
%onnx::Conv_1124[FLOAT, 256x256x3x3]
%onnx::Conv_1127[FLOAT, 256x512x1x1]
%onnx::Conv_1130[FLOAT, 256x256x3x3]
%onnx::Conv_1133[FLOAT, 256x512x1x1]
%onnx::Conv_1136[FLOAT, 256x256x3x3]
%onnx::Conv_1139[FLOAT, 256x256x3x3]
) {
%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_951)
%onnx::Conv_1074 = Identity(%onnx::Conv_951)
%onnx::Conv_1071 = Identity(%onnx::Conv_951)
%onnx::Conv_1068 = Identity(%onnx::Conv_951)
%onnx::Conv_1065 = Identity(%onnx::Conv_951)
%onnx::Conv_1062 = Identity(%onnx::Conv_951)
%onnx::Conv_1059 = Identity(%onnx::Conv_951)
%onnx::Conv_1056 = Identity(%onnx::Conv_951)
%onnx::Conv_1053 = Identity(%onnx::Conv_951)
%onnx::Conv_1050 = Identity(%onnx::Conv_951)
%onnx::Conv_1047 = Identity(%onnx::Conv_951)
%onnx::Conv_1044 = Identity(%onnx::Conv_951)
%onnx::Conv_1041 = Identity(%onnx::Conv_951)
%onnx::Conv_1038 = Identity(%onnx::Conv_951)
%onnx::Conv_1035 = Identity(%onnx::Conv_951)
%onnx::Conv_1032 = Identity(%onnx::Conv_951)
%onnx::Conv_1029 = Identity(%onnx::Conv_951)
%onnx::Conv_1026 = Identity(%onnx::Conv_951)
%onnx::Conv_1023 = Identity(%onnx::Conv_951)
%onnx::Conv_1020 = Identity(%onnx::Conv_951)
%onnx::Conv_1017 = Identity(%onnx::Conv_951)
%onnx::Conv_1014 = Identity(%onnx::Conv_954)
%onnx::Conv_1011 = Identity(%onnx::Conv_954)
%onnx::Conv_1008 = Identity(%onnx::Conv_954)
%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)
%/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/conv3x3/conv_bn_relu/conv_bn_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_956, %onnx::Conv_957)
%/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_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/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_962, %onnx::Conv_963)
%/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_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.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/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/conv3x3/conv_bn_relu/conv_bn_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_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_6_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_6_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/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.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.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_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/conv3x3/conv_bn_relu/conv_bn_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_977, %onnx::Conv_978)
%/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_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/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_983, %onnx::Conv_984)
%/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_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.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/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/conv3x3/conv_bn_relu/conv_bn_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_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_6_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_6_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/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.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.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_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/conv3x3/conv_bn_relu/conv_bn_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_998, %onnx::Conv_999)
%/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_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/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_1004, %onnx::Conv_1005)
%/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_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.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/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/conv3x3/conv_bn_relu/conv_bn_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_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_6_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_6_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/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.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.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_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/conv3x3/conv_bn_relu/conv_bn_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_1019, %onnx::Conv_1020)
%/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_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/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_1025, %onnx::Conv_1026)
%/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_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.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/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/conv3x3/conv_bn_relu/conv_bn_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_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_6_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_6_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/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.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.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_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/conv3x3/conv_bn_relu/conv_bn_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_1040, %onnx::Conv_1041)
%/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_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/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_1046, %onnx::Conv_1047)
%/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_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.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/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/conv3x3/conv_bn_relu/conv_bn_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_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_6_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_6_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/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.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.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_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/conv3x3/conv_bn_relu/conv_bn_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_1061, %onnx::Conv_1062)
%/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_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/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_1067, %onnx::Conv_1068)
%/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_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.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/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/conv3x3/conv_bn_relu/conv_bn_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_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_6_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_6_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/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.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.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_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/conv3x3/conv_bn_relu/conv_bn_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_1082, %onnx::Conv_1083)
%/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_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/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_1088, %onnx::Conv_1089)
%/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_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.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/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/conv3x3/conv_bn_relu/conv_bn_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_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_6_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_6_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/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.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.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_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/conv3x3/conv_bn_relu/conv_bn_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_1103, %onnx::Conv_1104)
%/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_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/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_1109, %onnx::Conv_1110)
%/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_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.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/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/conv3x3/conv_bn_relu/conv_bn_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_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_6_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_6_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/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.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.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_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/conv3x3/conv_bn_relu/conv_bn_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_1124, %onnx::Conv_1125)
%/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_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/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_1130, %onnx::Conv_1131)
%/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_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.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/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/conv3x3/conv_bn_relu/conv_bn_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_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_6_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_6_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/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.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)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%948 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %948
}
|
val_accuracy
| 93.038863
| 3,147,966,464
| 10,619,914
|
{'zcp_epe_nas': 176.1014427627705, 'zcp_fisher': 19.733598709106445, 'zcp_flops': 50367463424.0, 'zcp_grad_norm': 93.11236572265625, 'zcp_grasp': 7.90081787109375, 'zcp_jacov': -16.05379707024597, 'zcp_l2_norm': 1189.30517578125, 'zcp_nwot': 226.11712197827842, 'zcp_params': 10619914.0, 'zcp_plain': 0.027739245444536, 'zcp_snip': 584.7057495117188, 'zcp_synflow': 159.4552387743242, 'zcp_zen': 129.61788940429688, 'zcp_val_accuracy': 0.926282048225402}
| |
NASBench101_15907
|
NASBench101
|
15907
|
09986d729ef5f552541cbaf165e8877d
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_938[FLOAT, 128x3x3x3]
%onnx::Conv_939[FLOAT, 128]
%onnx::Conv_941[FLOAT, 43x128x1x1]
%onnx::Conv_942[FLOAT, 43]
%onnx::Conv_944[FLOAT, 43x43x3x3]
%onnx::Conv_947[FLOAT, 43x128x1x1]
%onnx::Conv_950[FLOAT, 43x43x1x1]
%onnx::Conv_953[FLOAT, 43x43x3x3]
%onnx::Conv_956[FLOAT, 43x43x3x3]
%onnx::Conv_959[FLOAT, 43x128x1x1]
%onnx::Conv_962[FLOAT, 43x43x3x3]
%onnx::Conv_965[FLOAT, 43x128x1x1]
%onnx::Conv_968[FLOAT, 43x43x1x1]
%onnx::Conv_971[FLOAT, 43x43x3x3]
%onnx::Conv_974[FLOAT, 43x43x3x3]
%onnx::Conv_977[FLOAT, 43x128x1x1]
%onnx::Conv_980[FLOAT, 43x43x3x3]
%onnx::Conv_983[FLOAT, 43x128x1x1]
%onnx::Conv_986[FLOAT, 43x43x1x1]
%onnx::Conv_989[FLOAT, 43x43x3x3]
%onnx::Conv_992[FLOAT, 43x43x3x3]
%onnx::Conv_995[FLOAT, 86x128x1x1]
%onnx::Conv_996[FLOAT, 86]
%onnx::Conv_998[FLOAT, 86x86x3x3]
%onnx::Conv_1001[FLOAT, 85x128x1x1]
%onnx::Conv_1002[FLOAT, 85]
%onnx::Conv_1004[FLOAT, 85x85x1x1]
%onnx::Conv_1007[FLOAT, 85x85x3x3]
%onnx::Conv_1010[FLOAT, 85x85x3x3]
%onnx::Conv_1013[FLOAT, 86x256x1x1]
%onnx::Conv_1016[FLOAT, 86x86x3x3]
%onnx::Conv_1019[FLOAT, 85x256x1x1]
%onnx::Conv_1022[FLOAT, 85x85x1x1]
%onnx::Conv_1025[FLOAT, 85x85x3x3]
%onnx::Conv_1028[FLOAT, 85x85x3x3]
%onnx::Conv_1031[FLOAT, 86x256x1x1]
%onnx::Conv_1034[FLOAT, 86x86x3x3]
%onnx::Conv_1037[FLOAT, 85x256x1x1]
%onnx::Conv_1040[FLOAT, 85x85x1x1]
%onnx::Conv_1043[FLOAT, 85x85x3x3]
%onnx::Conv_1046[FLOAT, 85x85x3x3]
%onnx::Conv_1049[FLOAT, 171x256x1x1]
%onnx::Conv_1050[FLOAT, 171]
%onnx::Conv_1052[FLOAT, 171x171x3x3]
%onnx::Conv_1055[FLOAT, 171x256x1x1]
%onnx::Conv_1058[FLOAT, 171x171x1x1]
%onnx::Conv_1061[FLOAT, 171x171x3x3]
%onnx::Conv_1064[FLOAT, 171x171x3x3]
%onnx::Conv_1067[FLOAT, 171x512x1x1]
%onnx::Conv_1070[FLOAT, 171x171x3x3]
%onnx::Conv_1073[FLOAT, 171x512x1x1]
%onnx::Conv_1076[FLOAT, 171x171x1x1]
%onnx::Conv_1079[FLOAT, 171x171x3x3]
%onnx::Conv_1082[FLOAT, 171x171x3x3]
%onnx::Conv_1085[FLOAT, 171x512x1x1]
%onnx::Conv_1088[FLOAT, 171x171x3x3]
%onnx::Conv_1091[FLOAT, 171x512x1x1]
%onnx::Conv_1094[FLOAT, 171x171x1x1]
%onnx::Conv_1097[FLOAT, 171x171x3x3]
%onnx::Conv_1100[FLOAT, 171x171x3x3]
) {
%onnx::Conv_1101 = Identity(%onnx::Conv_1050)
%onnx::Conv_1098 = Identity(%onnx::Conv_1050)
%onnx::Conv_1095 = Identity(%onnx::Conv_1050)
%onnx::Conv_1092 = Identity(%onnx::Conv_1050)
%onnx::Conv_1089 = Identity(%onnx::Conv_1050)
%onnx::Conv_1086 = Identity(%onnx::Conv_1050)
%onnx::Conv_1083 = Identity(%onnx::Conv_1050)
%onnx::Conv_1080 = Identity(%onnx::Conv_1050)
%onnx::Conv_1077 = Identity(%onnx::Conv_1050)
%onnx::Conv_1074 = Identity(%onnx::Conv_1050)
%onnx::Conv_1071 = Identity(%onnx::Conv_1050)
%onnx::Conv_1068 = Identity(%onnx::Conv_1050)
%onnx::Conv_1065 = Identity(%onnx::Conv_1050)
%onnx::Conv_1062 = Identity(%onnx::Conv_1050)
%onnx::Conv_1059 = Identity(%onnx::Conv_1050)
%onnx::Conv_1056 = Identity(%onnx::Conv_1050)
%onnx::Conv_1053 = Identity(%onnx::Conv_1050)
%onnx::Conv_1047 = Identity(%onnx::Conv_1002)
%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_996)
%onnx::Conv_1032 = Identity(%onnx::Conv_996)
%onnx::Conv_1029 = Identity(%onnx::Conv_1002)
%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_996)
%onnx::Conv_1014 = Identity(%onnx::Conv_996)
%onnx::Conv_1011 = Identity(%onnx::Conv_1002)
%onnx::Conv_1008 = Identity(%onnx::Conv_1002)
%onnx::Conv_1005 = Identity(%onnx::Conv_1002)
%onnx::Conv_999 = Identity(%onnx::Conv_996)
%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_938, %onnx::Conv_939)
%/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_941, %onnx::Conv_942)
%/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_944, %onnx::Conv_945)
%/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_947, %onnx::Conv_948)
%/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_950, %onnx::Conv_951)
%/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_953, %onnx::Conv_954)
%/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_956, %onnx::Conv_957)
%/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.2/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 = <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.4/conv3x3/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_output_0, %/layers.1/Constant_12_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/Slice_1_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/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_959, %onnx::Conv_960)
%/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_962, %onnx::Conv_963)
%/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_965, %onnx::Conv_966)
%/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_968, %onnx::Conv_969)
%/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_971, %onnx::Conv_972)
%/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_974, %onnx::Conv_975)
%/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.2/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 = <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.4/conv3x3/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_output_0, %/layers.2/Constant_12_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/Slice_1_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/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_977, %onnx::Conv_978)
%/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_980, %onnx::Conv_981)
%/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_983, %onnx::Conv_984)
%/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_986, %onnx::Conv_987)
%/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_989, %onnx::Conv_990)
%/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_992, %onnx::Conv_993)
%/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.2/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 = <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.4/conv3x3/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_output_0, %/layers.3/Constant_12_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/Slice_1_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/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_995, %onnx::Conv_996)
%/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_998, %onnx::Conv_999)
%/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_1001, %onnx::Conv_1002)
%/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_1004, %onnx::Conv_1005)
%/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_1007, %onnx::Conv_1008)
%/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_1010, %onnx::Conv_1011)
%/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/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/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_1013, %onnx::Conv_1014)
%/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_1016, %onnx::Conv_1017)
%/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_1019, %onnx::Conv_1020)
%/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_1022, %onnx::Conv_1023)
%/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_1025, %onnx::Conv_1026)
%/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_1028, %onnx::Conv_1029)
%/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/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/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_1031, %onnx::Conv_1032)
%/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_1034, %onnx::Conv_1035)
%/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_1037, %onnx::Conv_1038)
%/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_1040, %onnx::Conv_1041)
%/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_1043, %onnx::Conv_1044)
%/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_1046, %onnx::Conv_1047)
%/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/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/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_1049, %onnx::Conv_1050)
%/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_1052, %onnx::Conv_1053)
%/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_1055, %onnx::Conv_1056)
%/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_1058, %onnx::Conv_1059)
%/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_1061, %onnx::Conv_1062)
%/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_1064, %onnx::Conv_1065)
%/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.2/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 = <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.4/conv3x3/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_output_0, %/layers.9/Constant_12_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/Slice_1_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/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_1067, %onnx::Conv_1068)
%/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_1070, %onnx::Conv_1071)
%/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_1073, %onnx::Conv_1074)
%/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_1076, %onnx::Conv_1077)
%/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_1079, %onnx::Conv_1080)
%/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_1082, %onnx::Conv_1083)
%/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.2/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 = <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.4/conv3x3/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_output_0, %/layers.10/Constant_12_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/Slice_1_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/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_1085, %onnx::Conv_1086)
%/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_1088, %onnx::Conv_1089)
%/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_1091, %onnx::Conv_1092)
%/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_1094, %onnx::Conv_1095)
%/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_1097, %onnx::Conv_1098)
%/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_1100, %onnx::Conv_1101)
%/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.2/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 = <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.4/conv3x3/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_output_0, %/layers.11/Constant_12_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/Slice_1_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/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)
%936 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %936
}
|
val_accuracy
| 91.45633
| 1,144,481,792
| 3,822,919
|
{'zcp_epe_nas': 74.43291409400524, 'zcp_fisher': 342.87548828125, 'zcp_flops': 18311708672.0, 'zcp_grad_norm': 408.9103698730469, 'zcp_grasp': -2961.12109375, 'zcp_jacov': -16.059347711667115, 'zcp_l2_norm': 884.7678833007812, 'zcp_nwot': 218.67858585974102, 'zcp_params': 3822919.0, 'zcp_plain': 0.040905714035034006, 'zcp_snip': 1804.86376953125, 'zcp_synflow': 115.91223497471098, 'zcp_zen': 96.7794418334961, 'zcp_val_accuracy': 0.8958333134651181}
| |
NASBench101_45920
|
NASBench101
|
45920
|
1bdb03f269ab986df41d2fd14ad67705
|
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, 64x128x1x1]
%onnx::Conv_1089[FLOAT, 64]
%onnx::Conv_1091[FLOAT, 64x64x1x1]
%onnx::Conv_1094[FLOAT, 64x128x1x1]
%onnx::Conv_1097[FLOAT, 64x64x1x1]
%onnx::Conv_1100[FLOAT, 64x128x1x1]
%onnx::Conv_1103[FLOAT, 64x64x3x3]
%onnx::Conv_1106[FLOAT, 64x128x1x1]
%onnx::Conv_1109[FLOAT, 64x64x3x3]
%onnx::Conv_1112[FLOAT, 64x128x1x1]
%onnx::Conv_1115[FLOAT, 64x64x1x1]
%onnx::Conv_1118[FLOAT, 64x128x1x1]
%onnx::Conv_1121[FLOAT, 64x64x1x1]
%onnx::Conv_1124[FLOAT, 64x128x1x1]
%onnx::Conv_1127[FLOAT, 64x64x3x3]
%onnx::Conv_1130[FLOAT, 64x128x1x1]
%onnx::Conv_1133[FLOAT, 64x64x3x3]
%onnx::Conv_1136[FLOAT, 64x128x1x1]
%onnx::Conv_1139[FLOAT, 64x64x1x1]
%onnx::Conv_1142[FLOAT, 64x128x1x1]
%onnx::Conv_1145[FLOAT, 64x64x1x1]
%onnx::Conv_1148[FLOAT, 64x128x1x1]
%onnx::Conv_1151[FLOAT, 64x64x3x3]
%onnx::Conv_1154[FLOAT, 64x128x1x1]
%onnx::Conv_1157[FLOAT, 64x64x3x3]
%onnx::Conv_1160[FLOAT, 128x128x1x1]
%onnx::Conv_1163[FLOAT, 128x128x1x1]
%onnx::Conv_1166[FLOAT, 128x128x1x1]
%onnx::Conv_1169[FLOAT, 128x128x1x1]
%onnx::Conv_1172[FLOAT, 128x128x1x1]
%onnx::Conv_1175[FLOAT, 128x128x3x3]
%onnx::Conv_1178[FLOAT, 128x128x1x1]
%onnx::Conv_1181[FLOAT, 128x128x3x3]
%onnx::Conv_1184[FLOAT, 128x256x1x1]
%onnx::Conv_1187[FLOAT, 128x128x1x1]
%onnx::Conv_1190[FLOAT, 128x256x1x1]
%onnx::Conv_1193[FLOAT, 128x128x1x1]
%onnx::Conv_1196[FLOAT, 128x256x1x1]
%onnx::Conv_1199[FLOAT, 128x128x3x3]
%onnx::Conv_1202[FLOAT, 128x256x1x1]
%onnx::Conv_1205[FLOAT, 128x128x3x3]
%onnx::Conv_1208[FLOAT, 128x256x1x1]
%onnx::Conv_1211[FLOAT, 128x128x1x1]
%onnx::Conv_1214[FLOAT, 128x256x1x1]
%onnx::Conv_1217[FLOAT, 128x128x1x1]
%onnx::Conv_1220[FLOAT, 128x256x1x1]
%onnx::Conv_1223[FLOAT, 128x128x3x3]
%onnx::Conv_1226[FLOAT, 128x256x1x1]
%onnx::Conv_1229[FLOAT, 128x128x3x3]
%onnx::Conv_1232[FLOAT, 256x256x1x1]
%onnx::Conv_1233[FLOAT, 256]
%onnx::Conv_1235[FLOAT, 256x256x1x1]
%onnx::Conv_1238[FLOAT, 256x256x1x1]
%onnx::Conv_1241[FLOAT, 256x256x1x1]
%onnx::Conv_1244[FLOAT, 256x256x1x1]
%onnx::Conv_1247[FLOAT, 256x256x3x3]
%onnx::Conv_1250[FLOAT, 256x256x1x1]
%onnx::Conv_1253[FLOAT, 256x256x3x3]
%onnx::Conv_1256[FLOAT, 256x512x1x1]
%onnx::Conv_1259[FLOAT, 256x256x1x1]
%onnx::Conv_1262[FLOAT, 256x512x1x1]
%onnx::Conv_1265[FLOAT, 256x256x1x1]
%onnx::Conv_1268[FLOAT, 256x512x1x1]
%onnx::Conv_1271[FLOAT, 256x256x3x3]
%onnx::Conv_1274[FLOAT, 256x512x1x1]
%onnx::Conv_1277[FLOAT, 256x256x3x3]
%onnx::Conv_1280[FLOAT, 256x512x1x1]
%onnx::Conv_1283[FLOAT, 256x256x1x1]
%onnx::Conv_1286[FLOAT, 256x512x1x1]
%onnx::Conv_1289[FLOAT, 256x256x1x1]
%onnx::Conv_1292[FLOAT, 256x512x1x1]
%onnx::Conv_1295[FLOAT, 256x256x3x3]
%onnx::Conv_1298[FLOAT, 256x512x1x1]
%onnx::Conv_1301[FLOAT, 256x256x3x3]
) {
%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_1086)
%onnx::Conv_1227 = Identity(%onnx::Conv_1086)
%onnx::Conv_1224 = Identity(%onnx::Conv_1086)
%onnx::Conv_1221 = Identity(%onnx::Conv_1086)
%onnx::Conv_1218 = Identity(%onnx::Conv_1086)
%onnx::Conv_1215 = Identity(%onnx::Conv_1086)
%onnx::Conv_1212 = Identity(%onnx::Conv_1086)
%onnx::Conv_1209 = Identity(%onnx::Conv_1086)
%onnx::Conv_1206 = Identity(%onnx::Conv_1086)
%onnx::Conv_1203 = Identity(%onnx::Conv_1086)
%onnx::Conv_1200 = Identity(%onnx::Conv_1086)
%onnx::Conv_1197 = Identity(%onnx::Conv_1086)
%onnx::Conv_1194 = Identity(%onnx::Conv_1086)
%onnx::Conv_1191 = Identity(%onnx::Conv_1086)
%onnx::Conv_1188 = Identity(%onnx::Conv_1086)
%onnx::Conv_1185 = Identity(%onnx::Conv_1086)
%onnx::Conv_1182 = Identity(%onnx::Conv_1086)
%onnx::Conv_1179 = Identity(%onnx::Conv_1086)
%onnx::Conv_1176 = Identity(%onnx::Conv_1086)
%onnx::Conv_1173 = Identity(%onnx::Conv_1086)
%onnx::Conv_1170 = Identity(%onnx::Conv_1086)
%onnx::Conv_1167 = Identity(%onnx::Conv_1086)
%onnx::Conv_1164 = Identity(%onnx::Conv_1086)
%onnx::Conv_1161 = Identity(%onnx::Conv_1086)
%onnx::Conv_1158 = Identity(%onnx::Conv_1089)
%onnx::Conv_1155 = Identity(%onnx::Conv_1089)
%onnx::Conv_1152 = Identity(%onnx::Conv_1089)
%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)
%/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/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_1097, %onnx::Conv_1098)
%/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_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_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_1103, %onnx::Conv_1104)
%/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_1106, %onnx::Conv_1107)
%/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/input_op.4/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_1109, %onnx::Conv_1110)
%/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.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/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_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_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/Concat_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/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_1121, %onnx::Conv_1122)
%/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_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_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_1127, %onnx::Conv_1128)
%/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_1130, %onnx::Conv_1131)
%/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/input_op.4/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_1133, %onnx::Conv_1134)
%/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.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/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_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_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/Concat_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/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_1145, %onnx::Conv_1146)
%/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_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_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_1151, %onnx::Conv_1152)
%/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_1154, %onnx::Conv_1155)
%/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/input_op.4/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_1157, %onnx::Conv_1158)
%/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.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/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_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_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/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_1169, %onnx::Conv_1170)
%/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_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_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_1175, %onnx::Conv_1176)
%/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_1178, %onnx::Conv_1179)
%/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/input_op.4/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_4_output_0, %onnx::Conv_1181, %onnx::Conv_1182)
%/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.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/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_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_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/Concat_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/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_1193, %onnx::Conv_1194)
%/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_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_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_1199, %onnx::Conv_1200)
%/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_1202, %onnx::Conv_1203)
%/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/input_op.4/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_4_output_0, %onnx::Conv_1205, %onnx::Conv_1206)
%/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.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/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_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_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/Concat_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/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_1217, %onnx::Conv_1218)
%/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_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_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_1223, %onnx::Conv_1224)
%/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_1226, %onnx::Conv_1227)
%/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/input_op.4/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_4_output_0, %onnx::Conv_1229, %onnx::Conv_1230)
%/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.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/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_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_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/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_1241, %onnx::Conv_1242)
%/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_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_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_1247, %onnx::Conv_1248)
%/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_1250, %onnx::Conv_1251)
%/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/input_op.4/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_1253, %onnx::Conv_1254)
%/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.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/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_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_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/Concat_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/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_1265, %onnx::Conv_1266)
%/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_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_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_1271, %onnx::Conv_1272)
%/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_1274, %onnx::Conv_1275)
%/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/input_op.4/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_1277, %onnx::Conv_1278)
%/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.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/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_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_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/Concat_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/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_1289, %onnx::Conv_1290)
%/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_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_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_1295, %onnx::Conv_1296)
%/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_1298, %onnx::Conv_1299)
%/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/input_op.4/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_1301, %onnx::Conv_1302)
%/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.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/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_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)
%1083 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %1083
}
|
val_accuracy
| 92.317706
| 2,076,977,152
| 6,928,010
|
{'zcp_epe_nas': 123.25602641734483, 'zcp_fisher': 23.12440299987793, 'zcp_flops': 33231634432.0, 'zcp_grad_norm': 106.62459564208984, 'zcp_grasp': -7.373046875, 'zcp_jacov': -16.049074095537605, 'zcp_l2_norm': 1387.0675048828125, 'zcp_nwot': 228.96290809308678, 'zcp_params': 6928010.0, 'zcp_plain': 0.08553940057754501, 'zcp_snip': 681.9314575195312, 'zcp_synflow': 78.27364049190656, 'zcp_zen': 126.36865234375, 'zcp_val_accuracy': 0.9266827106475831}
| |
NASBench101_230901
|
NASBench101
|
230901
|
8bcde73fc69775983fecdcc571aa56c1
|
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, 43x43x1x1]
%onnx::Conv_842[FLOAT, 43x43x1x1]
%onnx::Conv_845[FLOAT, 43x43x1x1]
%onnx::Conv_848[FLOAT, 43x128x1x1]
%onnx::Conv_851[FLOAT, 43x43x1x1]
%onnx::Conv_854[FLOAT, 43x43x1x1]
%onnx::Conv_857[FLOAT, 43x43x1x1]
%onnx::Conv_860[FLOAT, 43x43x1x1]
%onnx::Conv_863[FLOAT, 43x128x1x1]
%onnx::Conv_866[FLOAT, 43x43x1x1]
%onnx::Conv_869[FLOAT, 43x43x1x1]
%onnx::Conv_872[FLOAT, 43x43x1x1]
%onnx::Conv_875[FLOAT, 43x43x1x1]
%onnx::Conv_878[FLOAT, 86x128x1x1]
%onnx::Conv_879[FLOAT, 86]
%onnx::Conv_881[FLOAT, 86x86x1x1]
%onnx::Conv_884[FLOAT, 86x86x1x1]
%onnx::Conv_887[FLOAT, 86x86x1x1]
%onnx::Conv_890[FLOAT, 85x85x1x1]
%onnx::Conv_891[FLOAT, 85]
%onnx::Conv_893[FLOAT, 86x256x1x1]
%onnx::Conv_896[FLOAT, 86x86x1x1]
%onnx::Conv_899[FLOAT, 86x86x1x1]
%onnx::Conv_902[FLOAT, 86x86x1x1]
%onnx::Conv_905[FLOAT, 85x85x1x1]
%onnx::Conv_908[FLOAT, 86x256x1x1]
%onnx::Conv_911[FLOAT, 86x86x1x1]
%onnx::Conv_914[FLOAT, 86x86x1x1]
%onnx::Conv_917[FLOAT, 86x86x1x1]
%onnx::Conv_920[FLOAT, 85x85x1x1]
%onnx::Conv_923[FLOAT, 171x256x1x1]
%onnx::Conv_924[FLOAT, 171]
%onnx::Conv_926[FLOAT, 171x171x1x1]
%onnx::Conv_929[FLOAT, 171x171x1x1]
%onnx::Conv_932[FLOAT, 171x171x1x1]
%onnx::Conv_935[FLOAT, 171x171x1x1]
%onnx::Conv_938[FLOAT, 171x512x1x1]
%onnx::Conv_941[FLOAT, 171x171x1x1]
%onnx::Conv_944[FLOAT, 171x171x1x1]
%onnx::Conv_947[FLOAT, 171x171x1x1]
%onnx::Conv_950[FLOAT, 171x171x1x1]
%onnx::Conv_953[FLOAT, 171x512x1x1]
%onnx::Conv_956[FLOAT, 171x171x1x1]
%onnx::Conv_959[FLOAT, 171x171x1x1]
%onnx::Conv_962[FLOAT, 171x171x1x1]
%onnx::Conv_965[FLOAT, 171x171x1x1]
) {
%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_924)
%onnx::Conv_954 = Identity(%onnx::Conv_924)
%onnx::Conv_951 = Identity(%onnx::Conv_924)
%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_936 = 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_891)
%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_891)
%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_888 = Identity(%onnx::Conv_879)
%onnx::Conv_885 = Identity(%onnx::Conv_879)
%onnx::Conv_882 = Identity(%onnx::Conv_879)
%onnx::Conv_876 = Identity(%onnx::Conv_834)
%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_834)
%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_846 = 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/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_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_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_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.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_3_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/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.2/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_4_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_4_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/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_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/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_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_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_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.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_3_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/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.2/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_4_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_4_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/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_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/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_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_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_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.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_3_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/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.2/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_4_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_4_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/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_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/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_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_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_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_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.2/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/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_890, %onnx::Conv_891)
%/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.2/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/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.3/conv1x1/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_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/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_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_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_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_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.2/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/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_905, %onnx::Conv_906)
%/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.2/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/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.3/conv1x1/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_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/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_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_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_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_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.2/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/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_920, %onnx::Conv_921)
%/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.2/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/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.3/conv1x1/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_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/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_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_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_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.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_3_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/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.2/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_4_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_4_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/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_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/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_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_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_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.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_3_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/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.2/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_4_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_4_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/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_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/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_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_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_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.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_3_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/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.2/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_4_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_4_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/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)
%828 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %828
}
|
val_accuracy
| 82.722354
| 242,916,864
| 769,587
|
{'zcp_epe_nas': 129.3654029072888, 'zcp_fisher': 115.57283020019531, 'zcp_flops': 3886669824.0, 'zcp_grad_norm': 236.33346557617188, 'zcp_grasp': -1280.09375, 'zcp_jacov': -16.042058177217918, 'zcp_l2_norm': 689.6390991210938, 'zcp_nwot': 216.2099561850082, 'zcp_params': 769587.0, 'zcp_plain': 0.052637863904237005, 'zcp_snip': 886.4783325195312, 'zcp_synflow': 96.98916679940773, 'zcp_zen': 55.85942077636719, 'zcp_val_accuracy': 0.9123597741127011}
| |
NASBench101_109704
|
NASBench101
|
109704
|
423ca4be5719c4c5674c53656be968c8
|
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, 64x64x1x1]
%onnx::Conv_779[FLOAT, 64x128x1x1]
%onnx::Conv_782[FLOAT, 64x64x3x3]
%onnx::Conv_785[FLOAT, 128x128x1x1]
%onnx::Conv_788[FLOAT, 64x128x1x1]
%onnx::Conv_791[FLOAT, 64x64x1x1]
%onnx::Conv_794[FLOAT, 64x128x1x1]
%onnx::Conv_797[FLOAT, 64x64x3x3]
%onnx::Conv_800[FLOAT, 128x128x1x1]
%onnx::Conv_803[FLOAT, 64x128x1x1]
%onnx::Conv_806[FLOAT, 64x64x1x1]
%onnx::Conv_809[FLOAT, 64x128x1x1]
%onnx::Conv_812[FLOAT, 64x64x3x3]
%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, 256x128x1x1]
%onnx::Conv_831[FLOAT, 256]
%onnx::Conv_833[FLOAT, 128x256x1x1]
%onnx::Conv_836[FLOAT, 128x128x1x1]
%onnx::Conv_839[FLOAT, 128x256x1x1]
%onnx::Conv_842[FLOAT, 128x128x3x3]
%onnx::Conv_845[FLOAT, 256x256x1x1]
%onnx::Conv_848[FLOAT, 128x256x1x1]
%onnx::Conv_851[FLOAT, 128x128x1x1]
%onnx::Conv_854[FLOAT, 128x256x1x1]
%onnx::Conv_857[FLOAT, 128x128x3x3]
%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, 512x256x1x1]
%onnx::Conv_876[FLOAT, 512]
%onnx::Conv_878[FLOAT, 256x512x1x1]
%onnx::Conv_881[FLOAT, 256x256x1x1]
%onnx::Conv_884[FLOAT, 256x512x1x1]
%onnx::Conv_887[FLOAT, 256x256x3x3]
%onnx::Conv_890[FLOAT, 512x512x1x1]
%onnx::Conv_893[FLOAT, 256x512x1x1]
%onnx::Conv_896[FLOAT, 256x256x1x1]
%onnx::Conv_899[FLOAT, 256x512x1x1]
%onnx::Conv_902[FLOAT, 256x256x3x3]
%onnx::Conv_905[FLOAT, 512x512x1x1]
) {
%onnx::Conv_906 = Identity(%onnx::Conv_876)
%onnx::Conv_903 = Identity(%onnx::Conv_831)
%onnx::Conv_900 = Identity(%onnx::Conv_831)
%onnx::Conv_897 = Identity(%onnx::Conv_831)
%onnx::Conv_894 = Identity(%onnx::Conv_831)
%onnx::Conv_891 = Identity(%onnx::Conv_876)
%onnx::Conv_888 = Identity(%onnx::Conv_831)
%onnx::Conv_885 = Identity(%onnx::Conv_831)
%onnx::Conv_882 = Identity(%onnx::Conv_831)
%onnx::Conv_879 = Identity(%onnx::Conv_831)
%onnx::Conv_873 = Identity(%onnx::Conv_831)
%onnx::Conv_870 = Identity(%onnx::Conv_831)
%onnx::Conv_867 = Identity(%onnx::Conv_831)
%onnx::Conv_864 = Identity(%onnx::Conv_831)
%onnx::Conv_861 = Identity(%onnx::Conv_831)
%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_831)
%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_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_771)
%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_771)
%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_771)
%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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_779, %onnx::Conv_780)
%/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_782, %onnx::Conv_783)
%/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.4/conv3x3/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_3_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.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_785, %onnx::Conv_786)
%/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_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/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_794, %onnx::Conv_795)
%/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_797, %onnx::Conv_798)
%/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.4/conv3x3/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_3_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.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_800, %onnx::Conv_801)
%/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_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/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_809, %onnx::Conv_810)
%/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_812, %onnx::Conv_813)
%/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.4/conv3x3/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_3_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.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_815, %onnx::Conv_816)
%/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_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/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_824, %onnx::Conv_825)
%/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_827, %onnx::Conv_828)
%/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.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_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.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_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_830, %onnx::Conv_831)
%/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_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/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_839, %onnx::Conv_840)
%/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_842, %onnx::Conv_843)
%/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.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_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.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_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_845, %onnx::Conv_846)
%/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_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/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_854, %onnx::Conv_855)
%/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_857, %onnx::Conv_858)
%/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.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_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.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_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_860, %onnx::Conv_861)
%/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_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/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_869, %onnx::Conv_870)
%/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_872, %onnx::Conv_873)
%/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.4/conv3x3/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_3_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.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_875, %onnx::Conv_876)
%/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_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/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_884, %onnx::Conv_885)
%/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_887, %onnx::Conv_888)
%/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.4/conv3x3/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_3_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.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_890, %onnx::Conv_891)
%/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_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/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_899, %onnx::Conv_900)
%/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_902, %onnx::Conv_903)
%/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.4/conv3x3/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_3_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)
%/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_905, %onnx::Conv_906)
%/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)
%768 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %768
}
|
val_accuracy
| 92.357773
| 1,316,497,408
| 4,342,154
|
{'zcp_epe_nas': 124.33127925713936, 'zcp_fisher': 9.048548698425293, 'zcp_flops': 21063958528.0, 'zcp_grad_norm': 59.668785095214844, 'zcp_grasp': -6.14208984375, 'zcp_jacov': -16.05332009364886, 'zcp_l2_norm': 889.5413208007812, 'zcp_nwot': 224.26586521981858, 'zcp_params': 4342154.0, 'zcp_plain': 0.07757651805877601, 'zcp_snip': 391.1539611816406, 'zcp_synflow': 85.12545049076704, 'zcp_zen': 90.7119369506836, 'zcp_val_accuracy': 0.868689894676208}
| |
NASBench101_163864
|
NASBench101
|
163864
|
63354bd878ba3ac859e55ea6b9888863
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_839[FLOAT, 128x3x3x3]
%onnx::Conv_840[FLOAT, 128]
%onnx::Conv_842[FLOAT, 43x128x1x1]
%onnx::Conv_843[FLOAT, 43]
%onnx::Conv_845[FLOAT, 43x43x1x1]
%onnx::Conv_848[FLOAT, 43x43x1x1]
%onnx::Conv_851[FLOAT, 43x43x3x3]
%onnx::Conv_854[FLOAT, 42x42x3x3]
%onnx::Conv_855[FLOAT, 42]
%onnx::Conv_857[FLOAT, 43x128x1x1]
%onnx::Conv_860[FLOAT, 43x43x1x1]
%onnx::Conv_863[FLOAT, 43x43x1x1]
%onnx::Conv_866[FLOAT, 43x43x3x3]
%onnx::Conv_869[FLOAT, 42x42x3x3]
%onnx::Conv_872[FLOAT, 43x128x1x1]
%onnx::Conv_875[FLOAT, 43x43x1x1]
%onnx::Conv_878[FLOAT, 43x43x1x1]
%onnx::Conv_881[FLOAT, 43x43x3x3]
%onnx::Conv_884[FLOAT, 42x42x3x3]
%onnx::Conv_887[FLOAT, 86x128x1x1]
%onnx::Conv_888[FLOAT, 86]
%onnx::Conv_890[FLOAT, 86x86x1x1]
%onnx::Conv_893[FLOAT, 86x86x1x1]
%onnx::Conv_896[FLOAT, 85x85x3x3]
%onnx::Conv_897[FLOAT, 85]
%onnx::Conv_899[FLOAT, 85x85x3x3]
%onnx::Conv_902[FLOAT, 86x256x1x1]
%onnx::Conv_905[FLOAT, 86x86x1x1]
%onnx::Conv_908[FLOAT, 86x86x1x1]
%onnx::Conv_911[FLOAT, 85x85x3x3]
%onnx::Conv_914[FLOAT, 85x85x3x3]
%onnx::Conv_917[FLOAT, 86x256x1x1]
%onnx::Conv_920[FLOAT, 86x86x1x1]
%onnx::Conv_923[FLOAT, 86x86x1x1]
%onnx::Conv_926[FLOAT, 85x85x3x3]
%onnx::Conv_929[FLOAT, 85x85x3x3]
%onnx::Conv_932[FLOAT, 171x256x1x1]
%onnx::Conv_933[FLOAT, 171]
%onnx::Conv_935[FLOAT, 171x171x1x1]
%onnx::Conv_938[FLOAT, 171x171x1x1]
%onnx::Conv_941[FLOAT, 171x171x3x3]
%onnx::Conv_944[FLOAT, 170x170x3x3]
%onnx::Conv_945[FLOAT, 170]
%onnx::Conv_947[FLOAT, 171x512x1x1]
%onnx::Conv_950[FLOAT, 171x171x1x1]
%onnx::Conv_953[FLOAT, 171x171x1x1]
%onnx::Conv_956[FLOAT, 171x171x3x3]
%onnx::Conv_959[FLOAT, 170x170x3x3]
%onnx::Conv_962[FLOAT, 171x512x1x1]
%onnx::Conv_965[FLOAT, 171x171x1x1]
%onnx::Conv_968[FLOAT, 171x171x1x1]
%onnx::Conv_971[FLOAT, 171x171x3x3]
%onnx::Conv_974[FLOAT, 170x170x3x3]
) {
%onnx::Conv_975 = Identity(%onnx::Conv_945)
%onnx::Conv_972 = Identity(%onnx::Conv_933)
%onnx::Conv_969 = Identity(%onnx::Conv_933)
%onnx::Conv_966 = Identity(%onnx::Conv_933)
%onnx::Conv_963 = Identity(%onnx::Conv_933)
%onnx::Conv_960 = Identity(%onnx::Conv_945)
%onnx::Conv_957 = Identity(%onnx::Conv_933)
%onnx::Conv_954 = Identity(%onnx::Conv_933)
%onnx::Conv_951 = Identity(%onnx::Conv_933)
%onnx::Conv_948 = 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)
%onnx::Conv_930 = Identity(%onnx::Conv_897)
%onnx::Conv_927 = Identity(%onnx::Conv_897)
%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_897)
%onnx::Conv_912 = Identity(%onnx::Conv_897)
%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_897)
%onnx::Conv_894 = Identity(%onnx::Conv_888)
%onnx::Conv_891 = Identity(%onnx::Conv_888)
%onnx::Conv_885 = Identity(%onnx::Conv_855)
%onnx::Conv_882 = Identity(%onnx::Conv_843)
%onnx::Conv_879 = Identity(%onnx::Conv_843)
%onnx::Conv_876 = Identity(%onnx::Conv_843)
%onnx::Conv_873 = Identity(%onnx::Conv_843)
%onnx::Conv_870 = Identity(%onnx::Conv_855)
%onnx::Conv_867 = Identity(%onnx::Conv_843)
%onnx::Conv_864 = Identity(%onnx::Conv_843)
%onnx::Conv_861 = Identity(%onnx::Conv_843)
%onnx::Conv_858 = Identity(%onnx::Conv_843)
%onnx::Conv_852 = Identity(%onnx::Conv_843)
%onnx::Conv_849 = Identity(%onnx::Conv_843)
%onnx::Conv_846 = Identity(%onnx::Conv_843)
%/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_839, %onnx::Conv_840)
%/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_842, %onnx::Conv_843)
%/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_845, %onnx::Conv_846)
%/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_848, %onnx::Conv_849)
%/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/conv3x3/conv_bn_relu/conv_bn_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_851, %onnx::Conv_852)
%/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_854, %onnx::Conv_855)
%/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.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_857, %onnx::Conv_858)
%/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_860, %onnx::Conv_861)
%/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_863, %onnx::Conv_864)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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/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_869, %onnx::Conv_870)
%/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.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_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/conv1x1/conv_bn_relu/conv_bn_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_878, %onnx::Conv_879)
%/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/conv3x3/conv_bn_relu/conv_bn_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_881, %onnx::Conv_882)
%/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_884, %onnx::Conv_885)
%/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.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_887, %onnx::Conv_888)
%/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_890, %onnx::Conv_891)
%/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_893, %onnx::Conv_894)
%/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 = <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.2/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/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.3/maxpool/MaxPool_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_output_0, %/layers.5/Constant_11_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/Slice_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/Add_4_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/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_899, %onnx::Conv_900)
%/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.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_902, %onnx::Conv_903)
%/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_905, %onnx::Conv_906)
%/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_908, %onnx::Conv_909)
%/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 = <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.2/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/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.3/maxpool/MaxPool_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_output_0, %/layers.6/Constant_11_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/Slice_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/Add_4_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/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_914, %onnx::Conv_915)
%/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.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_917, %onnx::Conv_918)
%/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_920, %onnx::Conv_921)
%/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_923, %onnx::Conv_924)
%/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 = <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.2/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/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.3/maxpool/MaxPool_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_output_0, %/layers.7/Constant_11_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/Slice_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/Add_4_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/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_929, %onnx::Conv_930)
%/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.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_932, %onnx::Conv_933)
%/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_935, %onnx::Conv_936)
%/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_938, %onnx::Conv_939)
%/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/conv3x3/conv_bn_relu/conv_bn_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_941, %onnx::Conv_942)
%/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_944, %onnx::Conv_945)
%/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.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_947, %onnx::Conv_948)
%/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_950, %onnx::Conv_951)
%/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_953, %onnx::Conv_954)
%/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/conv3x3/conv_bn_relu/conv_bn_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_956, %onnx::Conv_957)
%/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_959, %onnx::Conv_960)
%/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.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_962, %onnx::Conv_963)
%/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_965, %onnx::Conv_966)
%/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_968, %onnx::Conv_969)
%/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/conv3x3/conv_bn_relu/conv_bn_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_971, %onnx::Conv_972)
%/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_974, %onnx::Conv_975)
%/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.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)
%837 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %837
}
|
val_accuracy
| 87.700319
| 775,725,696
| 2,596,674
|
{'zcp_epe_nas': 65.30828142952308, 'zcp_fisher': 366.7463684082031, 'zcp_flops': 12411611136.0, 'zcp_grad_norm': 366.748046875, 'zcp_grasp': -685.109375, 'zcp_jacov': -16.05403442828669, 'zcp_l2_norm': 688.9366455078125, 'zcp_nwot': 215.85930783760372, 'zcp_params': 2596674.0, 'zcp_plain': 0.006482721306383001, 'zcp_snip': 1598.398681640625, 'zcp_synflow': 137.28182438748334, 'zcp_zen': 79.4700927734375, 'zcp_val_accuracy': 0.888221144676208}
| |
NASBench101_231529
|
NASBench101
|
231529
|
8c3064ad49a8cd5821f1e0381c2cc91a
|
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, 64x128x1x1]
%onnx::Conv_738[FLOAT, 64]
%onnx::Conv_740[FLOAT, 64x64x3x3]
%onnx::Conv_743[FLOAT, 64x128x1x1]
%onnx::Conv_746[FLOAT, 64x64x1x1]
%onnx::Conv_749[FLOAT, 128x128x1x1]
%onnx::Conv_752[FLOAT, 64x128x1x1]
%onnx::Conv_755[FLOAT, 64x64x3x3]
%onnx::Conv_758[FLOAT, 64x128x1x1]
%onnx::Conv_761[FLOAT, 64x64x1x1]
%onnx::Conv_764[FLOAT, 128x128x1x1]
%onnx::Conv_767[FLOAT, 64x128x1x1]
%onnx::Conv_770[FLOAT, 64x64x3x3]
%onnx::Conv_773[FLOAT, 64x128x1x1]
%onnx::Conv_776[FLOAT, 64x64x1x1]
%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, 256x128x1x1]
%onnx::Conv_795[FLOAT, 256]
%onnx::Conv_797[FLOAT, 128x256x1x1]
%onnx::Conv_800[FLOAT, 128x128x3x3]
%onnx::Conv_803[FLOAT, 128x256x1x1]
%onnx::Conv_806[FLOAT, 128x128x1x1]
%onnx::Conv_809[FLOAT, 256x256x1x1]
%onnx::Conv_812[FLOAT, 128x256x1x1]
%onnx::Conv_815[FLOAT, 128x128x3x3]
%onnx::Conv_818[FLOAT, 128x256x1x1]
%onnx::Conv_821[FLOAT, 128x128x1x1]
%onnx::Conv_824[FLOAT, 256x256x1x1]
%onnx::Conv_827[FLOAT, 256x256x1x1]
%onnx::Conv_830[FLOAT, 256x256x3x3]
%onnx::Conv_833[FLOAT, 256x256x1x1]
%onnx::Conv_836[FLOAT, 256x256x1x1]
%onnx::Conv_839[FLOAT, 512x256x1x1]
%onnx::Conv_840[FLOAT, 512]
%onnx::Conv_842[FLOAT, 256x512x1x1]
%onnx::Conv_845[FLOAT, 256x256x3x3]
%onnx::Conv_848[FLOAT, 256x512x1x1]
%onnx::Conv_851[FLOAT, 256x256x1x1]
%onnx::Conv_854[FLOAT, 512x512x1x1]
%onnx::Conv_857[FLOAT, 256x512x1x1]
%onnx::Conv_860[FLOAT, 256x256x3x3]
%onnx::Conv_863[FLOAT, 256x512x1x1]
%onnx::Conv_866[FLOAT, 256x256x1x1]
%onnx::Conv_869[FLOAT, 512x512x1x1]
) {
%onnx::Conv_870 = Identity(%onnx::Conv_840)
%onnx::Conv_867 = Identity(%onnx::Conv_795)
%onnx::Conv_864 = Identity(%onnx::Conv_795)
%onnx::Conv_861 = Identity(%onnx::Conv_795)
%onnx::Conv_858 = Identity(%onnx::Conv_795)
%onnx::Conv_855 = Identity(%onnx::Conv_840)
%onnx::Conv_852 = Identity(%onnx::Conv_795)
%onnx::Conv_849 = Identity(%onnx::Conv_795)
%onnx::Conv_846 = Identity(%onnx::Conv_795)
%onnx::Conv_843 = Identity(%onnx::Conv_795)
%onnx::Conv_837 = Identity(%onnx::Conv_795)
%onnx::Conv_834 = Identity(%onnx::Conv_795)
%onnx::Conv_831 = Identity(%onnx::Conv_795)
%onnx::Conv_828 = Identity(%onnx::Conv_795)
%onnx::Conv_825 = Identity(%onnx::Conv_795)
%onnx::Conv_822 = Identity(%onnx::Conv_735)
%onnx::Conv_819 = Identity(%onnx::Conv_735)
%onnx::Conv_816 = Identity(%onnx::Conv_735)
%onnx::Conv_813 = Identity(%onnx::Conv_735)
%onnx::Conv_810 = Identity(%onnx::Conv_795)
%onnx::Conv_807 = Identity(%onnx::Conv_735)
%onnx::Conv_804 = Identity(%onnx::Conv_735)
%onnx::Conv_801 = Identity(%onnx::Conv_735)
%onnx::Conv_798 = Identity(%onnx::Conv_735)
%onnx::Conv_792 = Identity(%onnx::Conv_735)
%onnx::Conv_789 = Identity(%onnx::Conv_735)
%onnx::Conv_786 = Identity(%onnx::Conv_735)
%onnx::Conv_783 = Identity(%onnx::Conv_735)
%onnx::Conv_780 = Identity(%onnx::Conv_735)
%onnx::Conv_777 = Identity(%onnx::Conv_738)
%onnx::Conv_774 = Identity(%onnx::Conv_738)
%onnx::Conv_771 = Identity(%onnx::Conv_738)
%onnx::Conv_768 = Identity(%onnx::Conv_738)
%onnx::Conv_765 = Identity(%onnx::Conv_735)
%onnx::Conv_762 = Identity(%onnx::Conv_738)
%onnx::Conv_759 = Identity(%onnx::Conv_738)
%onnx::Conv_756 = Identity(%onnx::Conv_738)
%onnx::Conv_753 = Identity(%onnx::Conv_738)
%onnx::Conv_750 = Identity(%onnx::Conv_735)
%onnx::Conv_747 = Identity(%onnx::Conv_738)
%onnx::Conv_744 = Identity(%onnx::Conv_738)
%onnx::Conv_741 = Identity(%onnx::Conv_738)
%/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/conv3x3/conv_bn_relu/conv_bn_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_740, %onnx::Conv_741)
%/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_743, %onnx::Conv_744)
%/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_746, %onnx::Conv_747)
%/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_3_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/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/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_749, %onnx::Conv_750)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_755, %onnx::Conv_756)
%/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_4_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/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_761, %onnx::Conv_762)
%/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_3_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/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/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_764, %onnx::Conv_765)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_770, %onnx::Conv_771)
%/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_4_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/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_776, %onnx::Conv_777)
%/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_3_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/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/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_779, %onnx::Conv_780)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_785, %onnx::Conv_786)
%/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_788, %onnx::Conv_789)
%/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_791, %onnx::Conv_792)
%/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_3_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/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/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_794, %onnx::Conv_795)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_800, %onnx::Conv_801)
%/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_4_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/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_806, %onnx::Conv_807)
%/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_3_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/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/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_809, %onnx::Conv_810)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_815, %onnx::Conv_816)
%/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_4_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/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_821, %onnx::Conv_822)
%/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_3_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/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/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_824, %onnx::Conv_825)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_830, %onnx::Conv_831)
%/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_833, %onnx::Conv_834)
%/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_836, %onnx::Conv_837)
%/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_3_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/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/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_839, %onnx::Conv_840)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_845, %onnx::Conv_846)
%/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_4_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/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_851, %onnx::Conv_852)
%/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_3_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/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/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_854, %onnx::Conv_855)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_860, %onnx::Conv_861)
%/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_4_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/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_866, %onnx::Conv_867)
%/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_3_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/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/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_869, %onnx::Conv_870)
%/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)
%732 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %732
}
|
val_accuracy
| 92.247593
| 1,316,497,408
| 4,342,154
|
{'zcp_epe_nas': 107.05796292683868, 'zcp_fisher': 21.83139991760254, 'zcp_flops': 21063958528.0, 'zcp_grad_norm': 93.01920318603516, 'zcp_grasp': -15.3924560546875, 'zcp_jacov': -16.068862680993025, 'zcp_l2_norm': 890.205810546875, 'zcp_nwot': 224.31875506356917, 'zcp_params': 4342154.0, 'zcp_plain': 0.13427831232547702, 'zcp_snip': 589.101806640625, 'zcp_synflow': 85.72925184951055, 'zcp_zen': 92.74195098876953, 'zcp_val_accuracy': 0.9037460088729851}
| |
NASBench101_254925
|
NASBench101
|
254925
|
9a57e97b0e0903e857c4d259914b3d16
|
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, 128x128x3x3]
%onnx::Conv_962[FLOAT, 128x128x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x128x1x1]
%onnx::Conv_971[FLOAT, 128x128x3x3]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 128x128x3x3]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x128x1x1]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 128x128x3x3]
%onnx::Conv_995[FLOAT, 128x128x1x1]
%onnx::Conv_998[FLOAT, 128x128x1x1]
%onnx::Conv_1001[FLOAT, 128x128x3x3]
%onnx::Conv_1004[FLOAT, 128x128x1x1]
%onnx::Conv_1007[FLOAT, 128x128x1x1]
%onnx::Conv_1010[FLOAT, 128x128x1x1]
%onnx::Conv_1013[FLOAT, 128x128x3x3]
%onnx::Conv_1016[FLOAT, 256x128x1x1]
%onnx::Conv_1017[FLOAT, 256]
%onnx::Conv_1019[FLOAT, 256x128x1x1]
%onnx::Conv_1022[FLOAT, 256x256x3x3]
%onnx::Conv_1025[FLOAT, 256x256x1x1]
%onnx::Conv_1028[FLOAT, 256x256x1x1]
%onnx::Conv_1031[FLOAT, 256x128x1x1]
%onnx::Conv_1034[FLOAT, 256x256x3x3]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 256x256x1x1]
%onnx::Conv_1043[FLOAT, 256x256x3x3]
%onnx::Conv_1046[FLOAT, 256x256x1x1]
%onnx::Conv_1049[FLOAT, 256x256x1x1]
%onnx::Conv_1052[FLOAT, 256x256x1x1]
%onnx::Conv_1055[FLOAT, 256x256x3x3]
%onnx::Conv_1058[FLOAT, 256x256x1x1]
%onnx::Conv_1061[FLOAT, 256x256x1x1]
%onnx::Conv_1064[FLOAT, 256x256x3x3]
%onnx::Conv_1067[FLOAT, 256x256x1x1]
%onnx::Conv_1070[FLOAT, 256x256x1x1]
%onnx::Conv_1073[FLOAT, 256x256x1x1]
%onnx::Conv_1076[FLOAT, 256x256x3x3]
%onnx::Conv_1079[FLOAT, 512x256x1x1]
%onnx::Conv_1080[FLOAT, 512]
%onnx::Conv_1082[FLOAT, 512x256x1x1]
%onnx::Conv_1085[FLOAT, 512x512x3x3]
%onnx::Conv_1088[FLOAT, 512x512x1x1]
%onnx::Conv_1091[FLOAT, 512x512x1x1]
%onnx::Conv_1094[FLOAT, 512x256x1x1]
%onnx::Conv_1097[FLOAT, 512x512x3x3]
%onnx::Conv_1100[FLOAT, 512x512x1x1]
%onnx::Conv_1103[FLOAT, 512x512x1x1]
%onnx::Conv_1106[FLOAT, 512x512x3x3]
%onnx::Conv_1109[FLOAT, 512x512x1x1]
%onnx::Conv_1112[FLOAT, 512x512x1x1]
%onnx::Conv_1115[FLOAT, 512x512x1x1]
%onnx::Conv_1118[FLOAT, 512x512x3x3]
%onnx::Conv_1121[FLOAT, 512x512x1x1]
%onnx::Conv_1124[FLOAT, 512x512x1x1]
%onnx::Conv_1127[FLOAT, 512x512x3x3]
%onnx::Conv_1130[FLOAT, 512x512x1x1]
%onnx::Conv_1133[FLOAT, 512x512x1x1]
%onnx::Conv_1136[FLOAT, 512x512x1x1]
%onnx::Conv_1139[FLOAT, 512x512x3x3]
) {
%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/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_956, %onnx::Conv_957)
%/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_959, %onnx::Conv_960)
%/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_962, %onnx::Conv_963)
%/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_3_output_0 = Add(%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_965, %onnx::Conv_966)
%/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_968, %onnx::Conv_969)
%/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_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/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/Constant_2_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_971, %onnx::Conv_972)
%/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_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/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_977, %onnx::Conv_978)
%/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_980, %onnx::Conv_981)
%/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_983, %onnx::Conv_984)
%/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_3_output_0 = Add(%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_986, %onnx::Conv_987)
%/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/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/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_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/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/Constant_2_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_992, %onnx::Conv_993)
%/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_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/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_998, %onnx::Conv_999)
%/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_1001, %onnx::Conv_1002)
%/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_1004, %onnx::Conv_1005)
%/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_3_output_0 = Add(%/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/conv1x1/conv_bn_relu/conv_bn_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_1007, %onnx::Conv_1008)
%/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/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/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_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/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/Constant_2_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_1013, %onnx::Conv_1014)
%/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_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/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_1019, %onnx::Conv_1020)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1022, %onnx::Conv_1023)
%/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_2_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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_3_output_0 = Add(%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1028, %onnx::Conv_1029)
%/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_1031, %onnx::Conv_1032)
%/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_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/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/Constant_2_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_1034, %onnx::Conv_1035)
%/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_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/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_1040, %onnx::Conv_1041)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1043, %onnx::Conv_1044)
%/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_2_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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_3_output_0 = Add(%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1049, %onnx::Conv_1050)
%/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/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/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_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/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/Constant_2_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_1055, %onnx::Conv_1056)
%/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_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/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_1061, %onnx::Conv_1062)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1064, %onnx::Conv_1065)
%/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_2_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/conv1x1/conv_bn_relu/conv_bn_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.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_3_output_0 = Add(%/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/conv1x1/conv_bn_relu/conv_bn_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_1070, %onnx::Conv_1071)
%/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/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/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_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/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/Constant_2_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_1076, %onnx::Conv_1077)
%/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_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/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_1082, %onnx::Conv_1083)
%/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_1085, %onnx::Conv_1086)
%/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_1088, %onnx::Conv_1089)
%/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_3_output_0 = Add(%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1091, %onnx::Conv_1092)
%/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_1094, %onnx::Conv_1095)
%/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_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/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/Constant_2_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_1097, %onnx::Conv_1098)
%/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_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/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_1103, %onnx::Conv_1104)
%/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_1106, %onnx::Conv_1107)
%/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_1109, %onnx::Conv_1110)
%/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_3_output_0 = Add(%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1112, %onnx::Conv_1113)
%/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/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/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_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/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/Constant_2_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_1118, %onnx::Conv_1119)
%/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_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/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_1124, %onnx::Conv_1125)
%/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_1127, %onnx::Conv_1128)
%/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_1130, %onnx::Conv_1131)
%/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_3_output_0 = Add(%/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/conv1x1/conv_bn_relu/conv_bn_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_1133, %onnx::Conv_1134)
%/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/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/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_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/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/Constant_2_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_1139, %onnx::Conv_1140)
%/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)
%948 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %948
}
|
val_accuracy
| 93.489581
| 6,891,776,000
| 23,295,370
|
{'zcp_epe_nas': 83.31488180442143, 'zcp_fisher': 43.43872833251953, 'zcp_flops': 110268416000.0, 'zcp_grad_norm': 116.63190460205078, 'zcp_grasp': 10.454833984375, 'zcp_jacov': -16.06186712481407, 'zcp_l2_norm': 1438.1717529296875, 'zcp_nwot': 237.30269028776468, 'zcp_params': 23295370.0, 'zcp_plain': 0.012835606001317001, 'zcp_snip': 972.2542114257812, 'zcp_synflow': 161.73269285058927, 'zcp_zen': 127.63028717041016, 'zcp_val_accuracy': 0.944110572338104}
| |
NASBench101_220762
|
NASBench101
|
220762
|
85c885244269609aa40db0fe63606dd0
|
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, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x1x1]
%onnx::Conv_851[FLOAT, 128x128x1x1]
%onnx::Conv_854[FLOAT, 128x128x1x1]
%onnx::Conv_857[FLOAT, 128x128x1x1]
%onnx::Conv_860[FLOAT, 128x128x1x1]
%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, 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, 128x128x1x1]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%onnx::Conv_899[FLOAT, 256x128x1x1]
%onnx::Conv_900[FLOAT, 256]
%onnx::Conv_902[FLOAT, 256x256x1x1]
%onnx::Conv_905[FLOAT, 256x128x1x1]
%onnx::Conv_908[FLOAT, 256x256x1x1]
%onnx::Conv_911[FLOAT, 256x256x1x1]
%onnx::Conv_914[FLOAT, 256x128x1x1]
%onnx::Conv_917[FLOAT, 256x256x1x1]
%onnx::Conv_920[FLOAT, 256x256x1x1]
%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, 256x256x1x1]
%onnx::Conv_941[FLOAT, 256x256x1x1]
%onnx::Conv_944[FLOAT, 256x256x1x1]
%onnx::Conv_947[FLOAT, 256x256x1x1]
%onnx::Conv_950[FLOAT, 256x256x1x1]
%onnx::Conv_953[FLOAT, 512x256x1x1]
%onnx::Conv_954[FLOAT, 512]
%onnx::Conv_956[FLOAT, 512x512x1x1]
%onnx::Conv_959[FLOAT, 512x256x1x1]
%onnx::Conv_962[FLOAT, 512x512x1x1]
%onnx::Conv_965[FLOAT, 512x512x1x1]
%onnx::Conv_968[FLOAT, 512x256x1x1]
%onnx::Conv_971[FLOAT, 512x512x1x1]
%onnx::Conv_974[FLOAT, 512x512x1x1]
%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, 512x512x1x1]
%onnx::Conv_995[FLOAT, 512x512x1x1]
%onnx::Conv_998[FLOAT, 512x512x1x1]
%onnx::Conv_1001[FLOAT, 512x512x1x1]
%onnx::Conv_1004[FLOAT, 512x512x1x1]
) {
%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_900)
%onnx::Conv_948 = Identity(%onnx::Conv_900)
%onnx::Conv_945 = Identity(%onnx::Conv_900)
%onnx::Conv_942 = Identity(%onnx::Conv_900)
%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_900)
%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_912 = 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_843)
%onnx::Conv_894 = Identity(%onnx::Conv_843)
%onnx::Conv_891 = Identity(%onnx::Conv_843)
%onnx::Conv_888 = Identity(%onnx::Conv_843)
%onnx::Conv_885 = Identity(%onnx::Conv_843)
%onnx::Conv_882 = Identity(%onnx::Conv_843)
%onnx::Conv_879 = Identity(%onnx::Conv_843)
%onnx::Conv_876 = Identity(%onnx::Conv_843)
%onnx::Conv_873 = Identity(%onnx::Conv_843)
%onnx::Conv_870 = Identity(%onnx::Conv_843)
%onnx::Conv_867 = Identity(%onnx::Conv_843)
%onnx::Conv_864 = Identity(%onnx::Conv_843)
%onnx::Conv_861 = Identity(%onnx::Conv_843)
%onnx::Conv_858 = Identity(%onnx::Conv_843)
%onnx::Conv_855 = Identity(%onnx::Conv_843)
%onnx::Conv_852 = Identity(%onnx::Conv_843)
%onnx::Conv_849 = Identity(%onnx::Conv_843)
%onnx::Conv_846 = Identity(%onnx::Conv_843)
%/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/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_851, %onnx::Conv_852)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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.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.3/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/conv1x1/conv_bn_relu/conv_bn_relu.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_857, %onnx::Conv_858)
%/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_860, %onnx::Conv_861)
%/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/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_4_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/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_869, %onnx::Conv_870)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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.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.3/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/conv1x1/conv_bn_relu/conv_bn_relu.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_875, %onnx::Conv_876)
%/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_4_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/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/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_4_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/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_887, %onnx::Conv_888)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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.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.3/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/conv1x1/conv_bn_relu/conv_bn_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_893, %onnx::Conv_894)
%/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_4_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/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/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_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_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/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_905, %onnx::Conv_906)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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.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.3/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/conv1x1/conv_bn_relu/conv_bn_relu.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_911, %onnx::Conv_912)
%/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_914, %onnx::Conv_915)
%/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/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_4_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/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_923, %onnx::Conv_924)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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.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.3/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/conv1x1/conv_bn_relu/conv_bn_relu.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_929, %onnx::Conv_930)
%/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_4_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/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/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_4_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/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_941, %onnx::Conv_942)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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.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.3/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/conv1x1/conv_bn_relu/conv_bn_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_947, %onnx::Conv_948)
%/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_4_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/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/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_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_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/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_959, %onnx::Conv_960)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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.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.3/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/conv1x1/conv_bn_relu/conv_bn_relu.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_965, %onnx::Conv_966)
%/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_968, %onnx::Conv_969)
%/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/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_4_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/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_977, %onnx::Conv_978)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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.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.3/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/conv1x1/conv_bn_relu/conv_bn_relu.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_983, %onnx::Conv_984)
%/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_4_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/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/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_4_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/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_995, %onnx::Conv_996)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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.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.3/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/conv1x1/conv_bn_relu/conv_bn_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_1001, %onnx::Conv_1002)
%/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_4_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/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/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_4_output_0)
%840 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %840
}
|
val_accuracy
| 91.075718
| 1,752,442,880
| 5,742,730
|
{'zcp_epe_nas': 71.99668627858661, 'zcp_fisher': 12.246392250061035, 'zcp_flops': 28039086080.0, 'zcp_grad_norm': 84.88272857666016, 'zcp_grasp': -3.280029296875, 'zcp_jacov': -16.063249814971236, 'zcp_l2_norm': 1225.87353515625, 'zcp_nwot': 235.47778287853433, 'zcp_params': 5742730.0, 'zcp_plain': 0.088475249707698, 'zcp_snip': 633.6135864257812, 'zcp_synflow': 110.47253300948647, 'zcp_zen': 99.24594116210938, 'zcp_val_accuracy': 0.8664863705635071}
| |
NASBench101_223044
|
NASBench101
|
223044
|
8724244730beea966e703b0c43a4ef90
|
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, 43x43x1x1]
%onnx::Conv_821[FLOAT, 43x128x1x1]
%onnx::Conv_824[FLOAT, 43x43x3x3]
%onnx::Conv_827[FLOAT, 42x42x1x1]
%onnx::Conv_828[FLOAT, 42]
%onnx::Conv_830[FLOAT, 43x128x1x1]
%onnx::Conv_833[FLOAT, 43x43x1x1]
%onnx::Conv_836[FLOAT, 43x128x1x1]
%onnx::Conv_839[FLOAT, 43x43x3x3]
%onnx::Conv_842[FLOAT, 42x42x1x1]
%onnx::Conv_845[FLOAT, 43x128x1x1]
%onnx::Conv_848[FLOAT, 43x43x1x1]
%onnx::Conv_851[FLOAT, 43x128x1x1]
%onnx::Conv_854[FLOAT, 43x43x3x3]
%onnx::Conv_857[FLOAT, 42x42x1x1]
%onnx::Conv_860[FLOAT, 86x128x1x1]
%onnx::Conv_861[FLOAT, 86]
%onnx::Conv_863[FLOAT, 86x86x1x1]
%onnx::Conv_866[FLOAT, 85x128x1x1]
%onnx::Conv_867[FLOAT, 85]
%onnx::Conv_869[FLOAT, 85x85x3x3]
%onnx::Conv_872[FLOAT, 85x85x1x1]
%onnx::Conv_875[FLOAT, 86x256x1x1]
%onnx::Conv_878[FLOAT, 86x86x1x1]
%onnx::Conv_881[FLOAT, 85x256x1x1]
%onnx::Conv_884[FLOAT, 85x85x3x3]
%onnx::Conv_887[FLOAT, 85x85x1x1]
%onnx::Conv_890[FLOAT, 86x256x1x1]
%onnx::Conv_893[FLOAT, 86x86x1x1]
%onnx::Conv_896[FLOAT, 85x256x1x1]
%onnx::Conv_899[FLOAT, 85x85x3x3]
%onnx::Conv_902[FLOAT, 85x85x1x1]
%onnx::Conv_905[FLOAT, 171x256x1x1]
%onnx::Conv_906[FLOAT, 171]
%onnx::Conv_908[FLOAT, 171x171x1x1]
%onnx::Conv_911[FLOAT, 171x256x1x1]
%onnx::Conv_914[FLOAT, 171x171x3x3]
%onnx::Conv_917[FLOAT, 170x170x1x1]
%onnx::Conv_918[FLOAT, 170]
%onnx::Conv_920[FLOAT, 171x512x1x1]
%onnx::Conv_923[FLOAT, 171x171x1x1]
%onnx::Conv_926[FLOAT, 171x512x1x1]
%onnx::Conv_929[FLOAT, 171x171x3x3]
%onnx::Conv_932[FLOAT, 170x170x1x1]
%onnx::Conv_935[FLOAT, 171x512x1x1]
%onnx::Conv_938[FLOAT, 171x171x1x1]
%onnx::Conv_941[FLOAT, 171x512x1x1]
%onnx::Conv_944[FLOAT, 171x171x3x3]
%onnx::Conv_947[FLOAT, 170x170x1x1]
) {
%onnx::Conv_948 = Identity(%onnx::Conv_918)
%onnx::Conv_945 = Identity(%onnx::Conv_906)
%onnx::Conv_942 = Identity(%onnx::Conv_906)
%onnx::Conv_939 = Identity(%onnx::Conv_906)
%onnx::Conv_936 = Identity(%onnx::Conv_906)
%onnx::Conv_933 = Identity(%onnx::Conv_918)
%onnx::Conv_930 = Identity(%onnx::Conv_906)
%onnx::Conv_927 = Identity(%onnx::Conv_906)
%onnx::Conv_924 = Identity(%onnx::Conv_906)
%onnx::Conv_921 = Identity(%onnx::Conv_906)
%onnx::Conv_915 = Identity(%onnx::Conv_906)
%onnx::Conv_912 = Identity(%onnx::Conv_906)
%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_828)
%onnx::Conv_855 = Identity(%onnx::Conv_816)
%onnx::Conv_852 = Identity(%onnx::Conv_816)
%onnx::Conv_849 = Identity(%onnx::Conv_816)
%onnx::Conv_846 = Identity(%onnx::Conv_816)
%onnx::Conv_843 = Identity(%onnx::Conv_828)
%onnx::Conv_840 = Identity(%onnx::Conv_816)
%onnx::Conv_837 = Identity(%onnx::Conv_816)
%onnx::Conv_834 = Identity(%onnx::Conv_816)
%onnx::Conv_831 = Identity(%onnx::Conv_816)
%onnx::Conv_825 = Identity(%onnx::Conv_816)
%onnx::Conv_822 = Identity(%onnx::Conv_816)
%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/conv1x1/conv_bn_relu/conv_bn_relu.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_818, %onnx::Conv_819)
%/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_821, %onnx::Conv_822)
%/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/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.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_824, %onnx::Conv_825)
%/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 = <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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_827, %onnx::Conv_828)
%/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_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_6_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_833, %onnx::Conv_834)
%/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_836, %onnx::Conv_837)
%/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/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.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_839, %onnx::Conv_840)
%/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 = <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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_842, %onnx::Conv_843)
%/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_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_6_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.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_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/conv1x1/conv_bn_relu/conv_bn_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_848, %onnx::Conv_849)
%/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_851, %onnx::Conv_852)
%/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/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.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_854, %onnx::Conv_855)
%/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 = <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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_857, %onnx::Conv_858)
%/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_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_6_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_863, %onnx::Conv_864)
%/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/input_op.3/conv_bn_relu/conv_bn_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_866, %onnx::Conv_867)
%/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_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/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/conv3x3/conv_bn_relu/conv_bn_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_869, %onnx::Conv_870)
%/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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_1_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/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_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_10_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_878, %onnx::Conv_879)
%/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/input_op.3/conv_bn_relu/conv_bn_relu.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_881, %onnx::Conv_882)
%/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_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/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/conv3x3/conv_bn_relu/conv_bn_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_884, %onnx::Conv_885)
%/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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_1_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/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_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_10_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.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_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/conv1x1/conv_bn_relu/conv_bn_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_893, %onnx::Conv_894)
%/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/input_op.3/conv_bn_relu/conv_bn_relu.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_896, %onnx::Conv_897)
%/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_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/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/conv3x3/conv_bn_relu/conv_bn_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_899, %onnx::Conv_900)
%/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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_1_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/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_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_10_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_908, %onnx::Conv_909)
%/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_911, %onnx::Conv_912)
%/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/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.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_914, %onnx::Conv_915)
%/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 = <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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_917, %onnx::Conv_918)
%/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_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_6_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_923, %onnx::Conv_924)
%/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_926, %onnx::Conv_927)
%/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/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.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_929, %onnx::Conv_930)
%/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 = <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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_932, %onnx::Conv_933)
%/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_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_6_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.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_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/conv1x1/conv_bn_relu/conv_bn_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_938, %onnx::Conv_939)
%/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_941, %onnx::Conv_942)
%/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/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.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_944, %onnx::Conv_945)
%/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 = <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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_947, %onnx::Conv_948)
%/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_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_6_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.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)
%810 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %810
}
|
val_accuracy
| 92.257613
| 567,190,784
| 1,861,666
|
{'zcp_epe_nas': 68.24538228635895, 'zcp_fisher': 6.212086677551269, 'zcp_flops': 9075052544.0, 'zcp_grad_norm': 51.85956954956055, 'zcp_grasp': 0.0302734375, 'zcp_jacov': -16.056312702618158, 'zcp_l2_norm': 763.6898193359375, 'zcp_nwot': 215.9204529775362, 'zcp_params': 1861666.0, 'zcp_plain': 0.011387299746274001, 'zcp_snip': 263.19744873046875, 'zcp_synflow': 80.015488821935, 'zcp_zen': 74.53358459472656, 'zcp_val_accuracy': 0.9387019276618951}
| |
NASBench101_69624
|
NASBench101
|
69624
|
2a4081831fe2b32e72ebb43817037808
|
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, 64x128x1x1]
%onnx::Conv_954[FLOAT, 64]
%onnx::Conv_956[FLOAT, 64x64x1x1]
%onnx::Conv_959[FLOAT, 64x64x1x1]
%onnx::Conv_962[FLOAT, 64x64x1x1]
%onnx::Conv_965[FLOAT, 64x128x1x1]
%onnx::Conv_968[FLOAT, 64x64x1x1]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%onnx::Conv_974[FLOAT, 64x128x1x1]
%onnx::Conv_977[FLOAT, 64x64x1x1]
%onnx::Conv_980[FLOAT, 64x64x1x1]
%onnx::Conv_983[FLOAT, 64x64x1x1]
%onnx::Conv_986[FLOAT, 64x128x1x1]
%onnx::Conv_989[FLOAT, 64x64x1x1]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 64x128x1x1]
%onnx::Conv_998[FLOAT, 64x64x1x1]
%onnx::Conv_1001[FLOAT, 64x64x1x1]
%onnx::Conv_1004[FLOAT, 64x64x1x1]
%onnx::Conv_1007[FLOAT, 64x128x1x1]
%onnx::Conv_1010[FLOAT, 64x64x1x1]
%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, 256x128x1x1]
%onnx::Conv_1035[FLOAT, 256]
%onnx::Conv_1037[FLOAT, 128x256x1x1]
%onnx::Conv_1040[FLOAT, 128x128x1x1]
%onnx::Conv_1043[FLOAT, 128x128x1x1]
%onnx::Conv_1046[FLOAT, 128x128x1x1]
%onnx::Conv_1049[FLOAT, 128x256x1x1]
%onnx::Conv_1052[FLOAT, 128x128x1x1]
%onnx::Conv_1055[FLOAT, 256x256x1x1]
%onnx::Conv_1058[FLOAT, 128x256x1x1]
%onnx::Conv_1061[FLOAT, 128x128x1x1]
%onnx::Conv_1064[FLOAT, 128x128x1x1]
%onnx::Conv_1067[FLOAT, 128x128x1x1]
%onnx::Conv_1070[FLOAT, 128x256x1x1]
%onnx::Conv_1073[FLOAT, 128x128x1x1]
%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, 512x256x1x1]
%onnx::Conv_1098[FLOAT, 512]
%onnx::Conv_1100[FLOAT, 256x512x1x1]
%onnx::Conv_1103[FLOAT, 256x256x1x1]
%onnx::Conv_1106[FLOAT, 256x256x1x1]
%onnx::Conv_1109[FLOAT, 256x256x1x1]
%onnx::Conv_1112[FLOAT, 256x512x1x1]
%onnx::Conv_1115[FLOAT, 256x256x1x1]
%onnx::Conv_1118[FLOAT, 512x512x1x1]
%onnx::Conv_1121[FLOAT, 256x512x1x1]
%onnx::Conv_1124[FLOAT, 256x256x1x1]
%onnx::Conv_1127[FLOAT, 256x256x1x1]
%onnx::Conv_1130[FLOAT, 256x256x1x1]
%onnx::Conv_1133[FLOAT, 256x512x1x1]
%onnx::Conv_1136[FLOAT, 256x256x1x1]
%onnx::Conv_1139[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1140 = Identity(%onnx::Conv_1098)
%onnx::Conv_1137 = Identity(%onnx::Conv_1035)
%onnx::Conv_1134 = Identity(%onnx::Conv_1035)
%onnx::Conv_1131 = Identity(%onnx::Conv_1035)
%onnx::Conv_1128 = Identity(%onnx::Conv_1035)
%onnx::Conv_1125 = Identity(%onnx::Conv_1035)
%onnx::Conv_1122 = Identity(%onnx::Conv_1035)
%onnx::Conv_1119 = Identity(%onnx::Conv_1098)
%onnx::Conv_1116 = Identity(%onnx::Conv_1035)
%onnx::Conv_1113 = Identity(%onnx::Conv_1035)
%onnx::Conv_1110 = Identity(%onnx::Conv_1035)
%onnx::Conv_1107 = Identity(%onnx::Conv_1035)
%onnx::Conv_1104 = Identity(%onnx::Conv_1035)
%onnx::Conv_1101 = Identity(%onnx::Conv_1035)
%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_951)
%onnx::Conv_1071 = Identity(%onnx::Conv_951)
%onnx::Conv_1068 = Identity(%onnx::Conv_951)
%onnx::Conv_1065 = Identity(%onnx::Conv_951)
%onnx::Conv_1062 = Identity(%onnx::Conv_951)
%onnx::Conv_1059 = Identity(%onnx::Conv_951)
%onnx::Conv_1056 = Identity(%onnx::Conv_1035)
%onnx::Conv_1053 = Identity(%onnx::Conv_951)
%onnx::Conv_1050 = Identity(%onnx::Conv_951)
%onnx::Conv_1047 = Identity(%onnx::Conv_951)
%onnx::Conv_1044 = Identity(%onnx::Conv_951)
%onnx::Conv_1041 = Identity(%onnx::Conv_951)
%onnx::Conv_1038 = Identity(%onnx::Conv_951)
%onnx::Conv_1032 = Identity(%onnx::Conv_951)
%onnx::Conv_1029 = Identity(%onnx::Conv_951)
%onnx::Conv_1026 = Identity(%onnx::Conv_951)
%onnx::Conv_1023 = Identity(%onnx::Conv_951)
%onnx::Conv_1020 = Identity(%onnx::Conv_951)
%onnx::Conv_1017 = Identity(%onnx::Conv_951)
%onnx::Conv_1014 = Identity(%onnx::Conv_951)
%onnx::Conv_1011 = Identity(%onnx::Conv_954)
%onnx::Conv_1008 = Identity(%onnx::Conv_954)
%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_951)
%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_951)
%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)
%/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/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_959, %onnx::Conv_960)
%/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/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_962, %onnx::Conv_963)
%/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_965, %onnx::Conv_966)
%/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_968, %onnx::Conv_969)
%/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.3/conv1x1/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_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/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_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/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_980, %onnx::Conv_981)
%/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/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_983, %onnx::Conv_984)
%/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_986, %onnx::Conv_987)
%/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_989, %onnx::Conv_990)
%/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.3/conv1x1/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_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/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_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/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_1001, %onnx::Conv_1002)
%/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/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_1004, %onnx::Conv_1005)
%/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_1007, %onnx::Conv_1008)
%/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_1010, %onnx::Conv_1011)
%/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.3/conv1x1/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_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/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_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/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_1022, %onnx::Conv_1023)
%/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/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_1025, %onnx::Conv_1026)
%/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_1028, %onnx::Conv_1029)
%/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_1031, %onnx::Conv_1032)
%/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.3/conv1x1/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_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/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_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/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_1043, %onnx::Conv_1044)
%/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/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_1046, %onnx::Conv_1047)
%/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_1049, %onnx::Conv_1050)
%/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_1052, %onnx::Conv_1053)
%/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.3/conv1x1/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_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/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_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/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_1064, %onnx::Conv_1065)
%/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/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_1067, %onnx::Conv_1068)
%/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_1070, %onnx::Conv_1071)
%/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_1073, %onnx::Conv_1074)
%/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.3/conv1x1/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_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/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_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/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_1085, %onnx::Conv_1086)
%/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/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_1088, %onnx::Conv_1089)
%/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_1091, %onnx::Conv_1092)
%/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_1094, %onnx::Conv_1095)
%/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.3/conv1x1/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_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/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_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/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_1106, %onnx::Conv_1107)
%/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/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_1109, %onnx::Conv_1110)
%/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_1112, %onnx::Conv_1113)
%/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_1115, %onnx::Conv_1116)
%/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.3/conv1x1/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_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/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_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/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_1127, %onnx::Conv_1128)
%/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/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_1130, %onnx::Conv_1131)
%/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_1133, %onnx::Conv_1134)
%/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_1136, %onnx::Conv_1137)
%/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.3/conv1x1/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_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/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_6_output_0)
%948 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %948
}
|
val_accuracy
| 83.273238
| 869,017,600
| 2,799,242
|
{'zcp_epe_nas': 105.90915364478448, 'zcp_fisher': 2.217731237411499, 'zcp_flops': 13904281600.0, 'zcp_grad_norm': 41.98161315917969, 'zcp_grasp': -2.661911010742187, 'zcp_jacov': -16.06622330996847, 'zcp_l2_norm': 1189.6402587890625, 'zcp_nwot': 229.13624465484094, 'zcp_params': 2799242.0, 'zcp_plain': 0.026267310604453004, 'zcp_snip': 242.84925842285156, 'zcp_synflow': 122.05300968703918, 'zcp_zen': 100.09110260009766, 'zcp_val_accuracy': 0.915665090084075}
| |
NASBench101_328301
|
NASBench101
|
328301
|
c69605d0ed0ee042d03629a04b306e8c
|
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, 128x128x1x1]
%onnx::Conv_839[FLOAT, 128x128x3x3]
%onnx::Conv_842[FLOAT, 128x128x3x3]
%onnx::Conv_845[FLOAT, 128x128x3x3]
%onnx::Conv_848[FLOAT, 128x128x1x1]
%onnx::Conv_851[FLOAT, 128x128x1x1]
%onnx::Conv_854[FLOAT, 128x128x1x1]
%onnx::Conv_857[FLOAT, 128x128x3x3]
%onnx::Conv_860[FLOAT, 128x128x3x3]
%onnx::Conv_863[FLOAT, 128x128x3x3]
%onnx::Conv_866[FLOAT, 128x128x1x1]
%onnx::Conv_869[FLOAT, 128x128x1x1]
%onnx::Conv_872[FLOAT, 128x128x1x1]
%onnx::Conv_875[FLOAT, 128x128x3x3]
%onnx::Conv_878[FLOAT, 128x128x3x3]
%onnx::Conv_881[FLOAT, 128x128x3x3]
%onnx::Conv_884[FLOAT, 128x128x1x1]
%onnx::Conv_887[FLOAT, 128x128x1x1]
%onnx::Conv_890[FLOAT, 256x128x1x1]
%onnx::Conv_891[FLOAT, 256]
%onnx::Conv_893[FLOAT, 256x256x3x3]
%onnx::Conv_896[FLOAT, 256x256x3x3]
%onnx::Conv_899[FLOAT, 256x256x3x3]
%onnx::Conv_902[FLOAT, 256x256x1x1]
%onnx::Conv_905[FLOAT, 256x128x1x1]
%onnx::Conv_908[FLOAT, 256x256x1x1]
%onnx::Conv_911[FLOAT, 256x256x3x3]
%onnx::Conv_914[FLOAT, 256x256x3x3]
%onnx::Conv_917[FLOAT, 256x256x3x3]
%onnx::Conv_920[FLOAT, 256x256x1x1]
%onnx::Conv_923[FLOAT, 256x256x1x1]
%onnx::Conv_926[FLOAT, 256x256x1x1]
%onnx::Conv_929[FLOAT, 256x256x3x3]
%onnx::Conv_932[FLOAT, 256x256x3x3]
%onnx::Conv_935[FLOAT, 256x256x3x3]
%onnx::Conv_938[FLOAT, 256x256x1x1]
%onnx::Conv_941[FLOAT, 256x256x1x1]
%onnx::Conv_944[FLOAT, 512x256x1x1]
%onnx::Conv_945[FLOAT, 512]
%onnx::Conv_947[FLOAT, 512x512x3x3]
%onnx::Conv_950[FLOAT, 512x512x3x3]
%onnx::Conv_953[FLOAT, 512x512x3x3]
%onnx::Conv_956[FLOAT, 512x512x1x1]
%onnx::Conv_959[FLOAT, 512x256x1x1]
%onnx::Conv_962[FLOAT, 512x512x1x1]
%onnx::Conv_965[FLOAT, 512x512x3x3]
%onnx::Conv_968[FLOAT, 512x512x3x3]
%onnx::Conv_971[FLOAT, 512x512x3x3]
%onnx::Conv_974[FLOAT, 512x512x1x1]
%onnx::Conv_977[FLOAT, 512x512x1x1]
%onnx::Conv_980[FLOAT, 512x512x1x1]
%onnx::Conv_983[FLOAT, 512x512x3x3]
%onnx::Conv_986[FLOAT, 512x512x3x3]
%onnx::Conv_989[FLOAT, 512x512x3x3]
%onnx::Conv_992[FLOAT, 512x512x1x1]
%onnx::Conv_995[FLOAT, 512x512x1x1]
) {
%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_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)
%onnx::Conv_888 = Identity(%onnx::Conv_834)
%onnx::Conv_885 = Identity(%onnx::Conv_834)
%onnx::Conv_882 = Identity(%onnx::Conv_834)
%onnx::Conv_879 = Identity(%onnx::Conv_834)
%onnx::Conv_876 = Identity(%onnx::Conv_834)
%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_834)
%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_846 = 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_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/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_5_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_5_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/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_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.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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_866, %onnx::Conv_867)
%/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_5_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_5_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_5_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/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_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.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_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/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/conv1x1/conv_bn_relu/conv_bn_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_884, %onnx::Conv_885)
%/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_5_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_5_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_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_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/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_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.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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_902, %onnx::Conv_903)
%/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_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_5_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_5_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/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_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.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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_920, %onnx::Conv_921)
%/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_5_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_5_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_5_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/conv3x3/conv_bn_relu/conv_bn_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.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_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/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/conv1x1/conv_bn_relu/conv_bn_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_938, %onnx::Conv_939)
%/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_5_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_5_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_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_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/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_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.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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_956, %onnx::Conv_957)
%/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_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_5_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_5_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/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_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.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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_974, %onnx::Conv_975)
%/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_5_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_5_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_5_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/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_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.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_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/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/conv1x1/conv_bn_relu/conv_bn_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_992, %onnx::Conv_993)
%/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_5_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_5_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_5_output_0)
%831 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %831
}
|
val_accuracy
| 93.880206
| 9,033,754,624
| 30,679,178
|
{'zcp_epe_nas': 144.33965282064236, 'zcp_fisher': 15.460285186767578, 'zcp_flops': 144540073984.0, 'zcp_grad_norm': 89.01377868652344, 'zcp_grasp': 2.12744140625, 'zcp_jacov': -16.054279940169593, 'zcp_l2_norm': 1242.5621337890625, 'zcp_nwot': 235.1164372640208, 'zcp_params': 30679178.0, 'zcp_plain': -0.011117444373667, 'zcp_snip': 753.5362548828125, 'zcp_synflow': 135.19337903159868, 'zcp_zen': 119.61199951171875, 'zcp_val_accuracy': 0.9114583134651181}
| |
NASBench101_73859
|
NASBench101
|
73859
|
2cce7ec26d5354ca24c3d524b4db41ba
|
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, 128x128x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x128x3x3]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 128x128x3x3]
%onnx::Conv_995[FLOAT, 128x128x3x3]
%onnx::Conv_998[FLOAT, 128x128x1x1]
%onnx::Conv_1001[FLOAT, 128x128x1x1]
%onnx::Conv_1004[FLOAT, 128x128x1x1]
%onnx::Conv_1007[FLOAT, 128x128x3x3]
%onnx::Conv_1010[FLOAT, 128x128x1x1]
%onnx::Conv_1013[FLOAT, 128x128x3x3]
%onnx::Conv_1016[FLOAT, 128x128x3x3]
%onnx::Conv_1019[FLOAT, 128x128x1x1]
%onnx::Conv_1022[FLOAT, 128x128x1x1]
%onnx::Conv_1025[FLOAT, 128x128x1x1]
%onnx::Conv_1028[FLOAT, 128x128x3x3]
%onnx::Conv_1031[FLOAT, 128x128x1x1]
%onnx::Conv_1034[FLOAT, 128x128x3x3]
%onnx::Conv_1037[FLOAT, 128x128x3x3]
%onnx::Conv_1040[FLOAT, 128x128x1x1]
%onnx::Conv_1043[FLOAT, 256x128x1x1]
%onnx::Conv_1044[FLOAT, 256]
%onnx::Conv_1046[FLOAT, 256x128x1x1]
%onnx::Conv_1049[FLOAT, 256x256x3x3]
%onnx::Conv_1052[FLOAT, 256x128x1x1]
%onnx::Conv_1055[FLOAT, 256x256x3x3]
%onnx::Conv_1058[FLOAT, 256x256x3x3]
%onnx::Conv_1061[FLOAT, 256x128x1x1]
%onnx::Conv_1064[FLOAT, 256x256x1x1]
%onnx::Conv_1067[FLOAT, 256x256x1x1]
%onnx::Conv_1070[FLOAT, 256x256x3x3]
%onnx::Conv_1073[FLOAT, 256x256x1x1]
%onnx::Conv_1076[FLOAT, 256x256x3x3]
%onnx::Conv_1079[FLOAT, 256x256x3x3]
%onnx::Conv_1082[FLOAT, 256x256x1x1]
%onnx::Conv_1085[FLOAT, 256x256x1x1]
%onnx::Conv_1088[FLOAT, 256x256x1x1]
%onnx::Conv_1091[FLOAT, 256x256x3x3]
%onnx::Conv_1094[FLOAT, 256x256x1x1]
%onnx::Conv_1097[FLOAT, 256x256x3x3]
%onnx::Conv_1100[FLOAT, 256x256x3x3]
%onnx::Conv_1103[FLOAT, 256x256x1x1]
%onnx::Conv_1106[FLOAT, 512x256x1x1]
%onnx::Conv_1107[FLOAT, 512]
%onnx::Conv_1109[FLOAT, 512x256x1x1]
%onnx::Conv_1112[FLOAT, 512x512x3x3]
%onnx::Conv_1115[FLOAT, 512x256x1x1]
%onnx::Conv_1118[FLOAT, 512x512x3x3]
%onnx::Conv_1121[FLOAT, 512x512x3x3]
%onnx::Conv_1124[FLOAT, 512x256x1x1]
%onnx::Conv_1127[FLOAT, 512x512x1x1]
%onnx::Conv_1130[FLOAT, 512x512x1x1]
%onnx::Conv_1133[FLOAT, 512x512x3x3]
%onnx::Conv_1136[FLOAT, 512x512x1x1]
%onnx::Conv_1139[FLOAT, 512x512x3x3]
%onnx::Conv_1142[FLOAT, 512x512x3x3]
%onnx::Conv_1145[FLOAT, 512x512x1x1]
%onnx::Conv_1148[FLOAT, 512x512x1x1]
%onnx::Conv_1151[FLOAT, 512x512x1x1]
%onnx::Conv_1154[FLOAT, 512x512x3x3]
%onnx::Conv_1157[FLOAT, 512x512x1x1]
%onnx::Conv_1160[FLOAT, 512x512x3x3]
%onnx::Conv_1163[FLOAT, 512x512x3x3]
%onnx::Conv_1166[FLOAT, 512x512x1x1]
) {
%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_1044)
%onnx::Conv_1101 = Identity(%onnx::Conv_1044)
%onnx::Conv_1098 = Identity(%onnx::Conv_1044)
%onnx::Conv_1095 = Identity(%onnx::Conv_1044)
%onnx::Conv_1092 = Identity(%onnx::Conv_1044)
%onnx::Conv_1089 = Identity(%onnx::Conv_1044)
%onnx::Conv_1086 = Identity(%onnx::Conv_1044)
%onnx::Conv_1083 = Identity(%onnx::Conv_1044)
%onnx::Conv_1080 = Identity(%onnx::Conv_1044)
%onnx::Conv_1077 = Identity(%onnx::Conv_1044)
%onnx::Conv_1074 = Identity(%onnx::Conv_1044)
%onnx::Conv_1071 = Identity(%onnx::Conv_1044)
%onnx::Conv_1068 = Identity(%onnx::Conv_1044)
%onnx::Conv_1065 = Identity(%onnx::Conv_1044)
%onnx::Conv_1062 = Identity(%onnx::Conv_1044)
%onnx::Conv_1059 = Identity(%onnx::Conv_1044)
%onnx::Conv_1056 = Identity(%onnx::Conv_1044)
%onnx::Conv_1053 = Identity(%onnx::Conv_1044)
%onnx::Conv_1050 = Identity(%onnx::Conv_1044)
%onnx::Conv_1047 = Identity(%onnx::Conv_1044)
%onnx::Conv_1041 = Identity(%onnx::Conv_978)
%onnx::Conv_1038 = Identity(%onnx::Conv_978)
%onnx::Conv_1035 = Identity(%onnx::Conv_978)
%onnx::Conv_1032 = Identity(%onnx::Conv_978)
%onnx::Conv_1029 = Identity(%onnx::Conv_978)
%onnx::Conv_1026 = Identity(%onnx::Conv_978)
%onnx::Conv_1023 = Identity(%onnx::Conv_978)
%onnx::Conv_1020 = Identity(%onnx::Conv_978)
%onnx::Conv_1017 = Identity(%onnx::Conv_978)
%onnx::Conv_1014 = Identity(%onnx::Conv_978)
%onnx::Conv_1011 = Identity(%onnx::Conv_978)
%onnx::Conv_1008 = Identity(%onnx::Conv_978)
%onnx::Conv_1005 = Identity(%onnx::Conv_978)
%onnx::Conv_1002 = Identity(%onnx::Conv_978)
%onnx::Conv_999 = Identity(%onnx::Conv_978)
%onnx::Conv_996 = Identity(%onnx::Conv_978)
%onnx::Conv_993 = Identity(%onnx::Conv_978)
%onnx::Conv_990 = Identity(%onnx::Conv_978)
%onnx::Conv_987 = Identity(%onnx::Conv_978)
%onnx::Conv_984 = Identity(%onnx::Conv_978)
%onnx::Conv_981 = Identity(%onnx::Conv_978)
%/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/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_983, %onnx::Conv_984)
%/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_986, %onnx::Conv_987)
%/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_989, %onnx::Conv_990)
%/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_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/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_992, %onnx::Conv_993)
%/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_995, %onnx::Conv_996)
%/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_998, %onnx::Conv_999)
%/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_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/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_1004, %onnx::Conv_1005)
%/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_1007, %onnx::Conv_1008)
%/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_6_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/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_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/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_1013, %onnx::Conv_1014)
%/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_1016, %onnx::Conv_1017)
%/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_1019, %onnx::Conv_1020)
%/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_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/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_1025, %onnx::Conv_1026)
%/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_1028, %onnx::Conv_1029)
%/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_6_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/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_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/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_1034, %onnx::Conv_1035)
%/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_1037, %onnx::Conv_1038)
%/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_1040, %onnx::Conv_1041)
%/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_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/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_1046, %onnx::Conv_1047)
%/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_1049, %onnx::Conv_1050)
%/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_1052, %onnx::Conv_1053)
%/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_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/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_1055, %onnx::Conv_1056)
%/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_1058, %onnx::Conv_1059)
%/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_1061, %onnx::Conv_1062)
%/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_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/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_1067, %onnx::Conv_1068)
%/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_1070, %onnx::Conv_1071)
%/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_6_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/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_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/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_1076, %onnx::Conv_1077)
%/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_1079, %onnx::Conv_1080)
%/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_1082, %onnx::Conv_1083)
%/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_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/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_1088, %onnx::Conv_1089)
%/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_1091, %onnx::Conv_1092)
%/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_6_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/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_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/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_1097, %onnx::Conv_1098)
%/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_1100, %onnx::Conv_1101)
%/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_1103, %onnx::Conv_1104)
%/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_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/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_1109, %onnx::Conv_1110)
%/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_1112, %onnx::Conv_1113)
%/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_1115, %onnx::Conv_1116)
%/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_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/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_1118, %onnx::Conv_1119)
%/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_1121, %onnx::Conv_1122)
%/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_1124, %onnx::Conv_1125)
%/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_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/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_1130, %onnx::Conv_1131)
%/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_1133, %onnx::Conv_1134)
%/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_6_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/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_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/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_1139, %onnx::Conv_1140)
%/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_1142, %onnx::Conv_1143)
%/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_1145, %onnx::Conv_1146)
%/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_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/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_1151, %onnx::Conv_1152)
%/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_1154, %onnx::Conv_1155)
%/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_6_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/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_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/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_1160, %onnx::Conv_1161)
%/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_1163, %onnx::Conv_1164)
%/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_1166, %onnx::Conv_1167)
%/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)
%975 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %975
}
|
val_accuracy
| 93.609774
| 9,274,140,672
| 31,389,066
|
{'zcp_epe_nas': 130.76392662523156, 'zcp_fisher': 18.231237411499023, 'zcp_flops': 148386250752.0, 'zcp_grad_norm': 84.8929214477539, 'zcp_grasp': -0.139495849609375, 'zcp_jacov': -16.05321854541625, 'zcp_l2_norm': 1422.23388671875, 'zcp_nwot': 237.28922299505683, 'zcp_params': 31389066.0, 'zcp_plain': 0.017570072785019, 'zcp_snip': 760.3729248046875, 'zcp_synflow': 145.4984164888829, 'zcp_zen': 143.0641632080078, 'zcp_val_accuracy': 0.9208734035491941}
| |
NASBench101_280941
|
NASBench101
|
280941
|
aa03fa88c3ef6da43d13bc80219b3c9d
|
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, 64x64x3x3]
%onnx::Conv_989[FLOAT, 64x64x1x1]
%onnx::Conv_992[FLOAT, 64x64x3x3]
%onnx::Conv_995[FLOAT, 64x128x1x1]
%onnx::Conv_998[FLOAT, 64x64x1x1]
%onnx::Conv_1001[FLOAT, 64x128x1x1]
%onnx::Conv_1004[FLOAT, 64x64x1x1]
%onnx::Conv_1007[FLOAT, 64x64x3x3]
%onnx::Conv_1010[FLOAT, 64x64x1x1]
%onnx::Conv_1013[FLOAT, 64x64x3x3]
%onnx::Conv_1016[FLOAT, 64x128x1x1]
%onnx::Conv_1019[FLOAT, 64x64x1x1]
%onnx::Conv_1022[FLOAT, 64x128x1x1]
%onnx::Conv_1025[FLOAT, 64x64x1x1]
%onnx::Conv_1028[FLOAT, 64x64x3x3]
%onnx::Conv_1031[FLOAT, 64x64x1x1]
%onnx::Conv_1034[FLOAT, 64x64x3x3]
%onnx::Conv_1037[FLOAT, 64x128x1x1]
%onnx::Conv_1040[FLOAT, 64x64x1x1]
%onnx::Conv_1043[FLOAT, 128x128x1x1]
%onnx::Conv_1046[FLOAT, 128x128x1x1]
%onnx::Conv_1049[FLOAT, 128x128x3x3]
%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, 128x128x3x3]
%onnx::Conv_1073[FLOAT, 128x128x1x1]
%onnx::Conv_1076[FLOAT, 128x128x3x3]
%onnx::Conv_1079[FLOAT, 128x256x1x1]
%onnx::Conv_1082[FLOAT, 128x128x1x1]
%onnx::Conv_1085[FLOAT, 128x256x1x1]
%onnx::Conv_1088[FLOAT, 128x128x1x1]
%onnx::Conv_1091[FLOAT, 128x128x3x3]
%onnx::Conv_1094[FLOAT, 128x128x1x1]
%onnx::Conv_1097[FLOAT, 128x128x3x3]
%onnx::Conv_1100[FLOAT, 128x256x1x1]
%onnx::Conv_1103[FLOAT, 128x128x1x1]
%onnx::Conv_1106[FLOAT, 256x256x1x1]
%onnx::Conv_1107[FLOAT, 256]
%onnx::Conv_1109[FLOAT, 256x256x1x1]
%onnx::Conv_1112[FLOAT, 256x256x3x3]
%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, 256x256x3x3]
%onnx::Conv_1136[FLOAT, 256x256x1x1]
%onnx::Conv_1139[FLOAT, 256x256x3x3]
%onnx::Conv_1142[FLOAT, 256x512x1x1]
%onnx::Conv_1145[FLOAT, 256x256x1x1]
%onnx::Conv_1148[FLOAT, 256x512x1x1]
%onnx::Conv_1151[FLOAT, 256x256x1x1]
%onnx::Conv_1154[FLOAT, 256x256x3x3]
%onnx::Conv_1157[FLOAT, 256x256x1x1]
%onnx::Conv_1160[FLOAT, 256x256x3x3]
%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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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/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_989, %onnx::Conv_990)
%/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/conv3x3/conv_bn_relu/conv_bn_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_992, %onnx::Conv_993)
%/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_995, %onnx::Conv_996)
%/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/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/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_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.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_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/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_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/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_1010, %onnx::Conv_1011)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1013, %onnx::Conv_1014)
%/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_1016, %onnx::Conv_1017)
%/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/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/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_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.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_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/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_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/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_1031, %onnx::Conv_1032)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1034, %onnx::Conv_1035)
%/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_1037, %onnx::Conv_1038)
%/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/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/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_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.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_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/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_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/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_1052, %onnx::Conv_1053)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1055, %onnx::Conv_1056)
%/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_1058, %onnx::Conv_1059)
%/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/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/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_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.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_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/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_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/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_1073, %onnx::Conv_1074)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1076, %onnx::Conv_1077)
%/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_1079, %onnx::Conv_1080)
%/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/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/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_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.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_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/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_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/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_1094, %onnx::Conv_1095)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1097, %onnx::Conv_1098)
%/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_1100, %onnx::Conv_1101)
%/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/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/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_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.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_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/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_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/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_1115, %onnx::Conv_1116)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1118, %onnx::Conv_1119)
%/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_1121, %onnx::Conv_1122)
%/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/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/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_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.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_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/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_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/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_1136, %onnx::Conv_1137)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1139, %onnx::Conv_1140)
%/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_1142, %onnx::Conv_1143)
%/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/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/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_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.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_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/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_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/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_1157, %onnx::Conv_1158)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1160, %onnx::Conv_1161)
%/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_1163, %onnx::Conv_1164)
%/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/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/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_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.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)
%975 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %975
}
|
val_accuracy
| 92.257613
| 1,881,286,656
| 6,315,018
|
{'zcp_epe_nas': 165.4578557969528, 'zcp_fisher': 75.80754852294922, 'zcp_flops': 30100586496.0, 'zcp_grad_norm': 212.20046997070312, 'zcp_grasp': -520.97265625, 'zcp_jacov': -16.050582966776844, 'zcp_l2_norm': 1143.0367431640625, 'zcp_nwot': 227.22189532126282, 'zcp_params': 6315018.0, 'zcp_plain': -0.010795682668685, 'zcp_snip': 1076.992431640625, 'zcp_synflow': 162.8735036919561, 'zcp_zen': 107.02433013916016, 'zcp_val_accuracy': 0.9162660241127011}
| |
NASBench101_300761
|
NASBench101
|
300761
|
b5f6f3fe3667d10fc2c8d9ab6763adba
|
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, 64x128x1x1]
%onnx::Conv_869[FLOAT, 64x64x3x3]
%onnx::Conv_872[FLOAT, 64x64x3x3]
%onnx::Conv_875[FLOAT, 64x64x1x1]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_884[FLOAT, 64x128x1x1]
%onnx::Conv_887[FLOAT, 64x64x3x3]
%onnx::Conv_890[FLOAT, 64x64x3x3]
%onnx::Conv_893[FLOAT, 64x64x1x1]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x128x1x1]
%onnx::Conv_905[FLOAT, 64x64x3x3]
%onnx::Conv_908[FLOAT, 64x64x3x3]
%onnx::Conv_911[FLOAT, 64x64x1x1]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 128x128x1x1]
%onnx::Conv_920[FLOAT, 128x128x1x1]
%onnx::Conv_923[FLOAT, 128x128x3x3]
%onnx::Conv_926[FLOAT, 128x128x3x3]
%onnx::Conv_929[FLOAT, 128x128x1x1]
%onnx::Conv_932[FLOAT, 256x128x1x1]
%onnx::Conv_933[FLOAT, 256]
%onnx::Conv_935[FLOAT, 128x256x1x1]
%onnx::Conv_938[FLOAT, 128x256x1x1]
%onnx::Conv_941[FLOAT, 128x128x3x3]
%onnx::Conv_944[FLOAT, 128x128x3x3]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 256x256x1x1]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x256x1x1]
%onnx::Conv_959[FLOAT, 128x128x3x3]
%onnx::Conv_962[FLOAT, 128x128x3x3]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 256x256x1x1]
%onnx::Conv_974[FLOAT, 256x256x1x1]
%onnx::Conv_977[FLOAT, 256x256x3x3]
%onnx::Conv_980[FLOAT, 256x256x3x3]
%onnx::Conv_983[FLOAT, 256x256x1x1]
%onnx::Conv_986[FLOAT, 512x256x1x1]
%onnx::Conv_987[FLOAT, 512]
%onnx::Conv_989[FLOAT, 256x512x1x1]
%onnx::Conv_992[FLOAT, 256x512x1x1]
%onnx::Conv_995[FLOAT, 256x256x3x3]
%onnx::Conv_998[FLOAT, 256x256x3x3]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 512x512x1x1]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x512x1x1]
%onnx::Conv_1013[FLOAT, 256x256x3x3]
%onnx::Conv_1016[FLOAT, 256x256x3x3]
%onnx::Conv_1019[FLOAT, 256x256x1x1]
%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/input_op.3/conv_bn_relu/conv_bn_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_866, %onnx::Conv_867)
%/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/conv3x3/conv_bn_relu/conv_bn_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.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.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/conv3x3/conv_bn_relu/conv_bn_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_872, %onnx::Conv_873)
%/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.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_3_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/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/maxpool/MaxPool_output_0, %/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.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/input_op.3/conv_bn_relu/conv_bn_relu.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.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/conv3x3/conv_bn_relu/conv_bn_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.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.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/conv3x3/conv_bn_relu/conv_bn_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_890, %onnx::Conv_891)
%/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.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_3_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/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/maxpool/MaxPool_output_0, %/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.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/input_op.3/conv_bn_relu/conv_bn_relu.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.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/conv3x3/conv_bn_relu/conv_bn_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.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.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/conv3x3/conv_bn_relu/conv_bn_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_908, %onnx::Conv_909)
%/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.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_3_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/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/maxpool/MaxPool_output_0, %/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.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/input_op.3/conv_bn_relu/conv_bn_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_920, %onnx::Conv_921)
%/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/conv3x3/conv_bn_relu/conv_bn_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.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.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/conv3x3/conv_bn_relu/conv_bn_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.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.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_3_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/maxpool/MaxPool_output_0, %/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.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/input_op.3/conv_bn_relu/conv_bn_relu.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.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/conv3x3/conv_bn_relu/conv_bn_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.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.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/conv3x3/conv_bn_relu/conv_bn_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_944, %onnx::Conv_945)
%/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.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_3_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/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/maxpool/MaxPool_output_0, %/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.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/input_op.3/conv_bn_relu/conv_bn_relu.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.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/conv3x3/conv_bn_relu/conv_bn_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.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.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/conv3x3/conv_bn_relu/conv_bn_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_962, %onnx::Conv_963)
%/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.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_3_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/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/maxpool/MaxPool_output_0, %/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.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/input_op.3/conv_bn_relu/conv_bn_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_974, %onnx::Conv_975)
%/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/conv3x3/conv_bn_relu/conv_bn_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.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.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/conv3x3/conv_bn_relu/conv_bn_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_980, %onnx::Conv_981)
%/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.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_3_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/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/maxpool/MaxPool_output_0, %/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.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/input_op.3/conv_bn_relu/conv_bn_relu.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.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/conv3x3/conv_bn_relu/conv_bn_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.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.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/conv3x3/conv_bn_relu/conv_bn_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_998, %onnx::Conv_999)
%/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.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_3_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/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/maxpool/MaxPool_output_0, %/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.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/input_op.3/conv_bn_relu/conv_bn_relu.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.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/conv3x3/conv_bn_relu/conv_bn_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.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.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/conv3x3/conv_bn_relu/conv_bn_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_1016, %onnx::Conv_1017)
%/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.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_3_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/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/maxpool/MaxPool_output_0, %/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.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
| 90.635014
| 1,998,727,168
| 6,667,274
|
{'zcp_epe_nas': 143.52862392307307, 'zcp_fisher': 3.882073402404785, 'zcp_flops': 31979634688.0, 'zcp_grad_norm': 45.6500244140625, 'zcp_grasp': -11.3472900390625, 'zcp_jacov': -16.043284107474935, 'zcp_l2_norm': 1039.8992919921875, 'zcp_nwot': 226.49065192689912, 'zcp_params': 6667274.0, 'zcp_plain': 0.09208730608224801, 'zcp_snip': 296.93353271484375, 'zcp_synflow': 116.7027840140238, 'zcp_zen': 106.32902526855469, 'zcp_val_accuracy': 0.90234375}
| |
NASBench101_371298
|
NASBench101
|
371298
|
e07ab6519b044a587387f7037f6ad36f
|
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, 64x128x1x1]
%onnx::Conv_779[FLOAT, 64x64x3x3]
%onnx::Conv_782[FLOAT, 64x64x3x3]
%onnx::Conv_785[FLOAT, 64x128x1x1]
%onnx::Conv_788[FLOAT, 64x128x1x1]
%onnx::Conv_791[FLOAT, 64x128x1x1]
%onnx::Conv_794[FLOAT, 64x64x3x3]
%onnx::Conv_797[FLOAT, 64x64x3x3]
%onnx::Conv_800[FLOAT, 64x128x1x1]
%onnx::Conv_803[FLOAT, 64x128x1x1]
%onnx::Conv_806[FLOAT, 64x128x1x1]
%onnx::Conv_809[FLOAT, 64x64x3x3]
%onnx::Conv_812[FLOAT, 64x64x3x3]
%onnx::Conv_815[FLOAT, 64x128x1x1]
%onnx::Conv_818[FLOAT, 128x128x1x1]
%onnx::Conv_821[FLOAT, 128x128x1x1]
%onnx::Conv_824[FLOAT, 128x128x3x3]
%onnx::Conv_827[FLOAT, 128x128x3x3]
%onnx::Conv_830[FLOAT, 128x128x1x1]
%onnx::Conv_833[FLOAT, 128x256x1x1]
%onnx::Conv_836[FLOAT, 128x256x1x1]
%onnx::Conv_839[FLOAT, 128x128x3x3]
%onnx::Conv_842[FLOAT, 128x128x3x3]
%onnx::Conv_845[FLOAT, 128x256x1x1]
%onnx::Conv_848[FLOAT, 128x256x1x1]
%onnx::Conv_851[FLOAT, 128x256x1x1]
%onnx::Conv_854[FLOAT, 128x128x3x3]
%onnx::Conv_857[FLOAT, 128x128x3x3]
%onnx::Conv_860[FLOAT, 128x256x1x1]
%onnx::Conv_863[FLOAT, 256x256x1x1]
%onnx::Conv_864[FLOAT, 256]
%onnx::Conv_866[FLOAT, 256x256x1x1]
%onnx::Conv_869[FLOAT, 256x256x3x3]
%onnx::Conv_872[FLOAT, 256x256x3x3]
%onnx::Conv_875[FLOAT, 256x256x1x1]
%onnx::Conv_878[FLOAT, 256x512x1x1]
%onnx::Conv_881[FLOAT, 256x512x1x1]
%onnx::Conv_884[FLOAT, 256x256x3x3]
%onnx::Conv_887[FLOAT, 256x256x3x3]
%onnx::Conv_890[FLOAT, 256x512x1x1]
%onnx::Conv_893[FLOAT, 256x512x1x1]
%onnx::Conv_896[FLOAT, 256x512x1x1]
%onnx::Conv_899[FLOAT, 256x256x3x3]
%onnx::Conv_902[FLOAT, 256x256x3x3]
%onnx::Conv_905[FLOAT, 256x512x1x1]
) {
%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/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_776, %onnx::Conv_777)
%/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_779, %onnx::Conv_780)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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/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_785, %onnx::Conv_786)
%/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_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/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/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.1/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_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/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_791, %onnx::Conv_792)
%/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_794, %onnx::Conv_795)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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/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_800, %onnx::Conv_801)
%/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_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/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/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.1/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_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/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_806, %onnx::Conv_807)
%/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_809, %onnx::Conv_810)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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/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_815, %onnx::Conv_816)
%/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_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/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/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.1/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_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/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_821, %onnx::Conv_822)
%/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_824, %onnx::Conv_825)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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/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_830, %onnx::Conv_831)
%/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_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/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/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.1/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_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/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/Concat_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/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_839, %onnx::Conv_840)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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/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_845, %onnx::Conv_846)
%/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_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/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/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.1/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_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/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/Concat_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/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_854, %onnx::Conv_855)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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/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_860, %onnx::Conv_861)
%/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_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/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/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.1/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_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/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_866, %onnx::Conv_867)
%/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_869, %onnx::Conv_870)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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/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_875, %onnx::Conv_876)
%/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_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/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/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.1/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_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/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_881, %onnx::Conv_882)
%/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_884, %onnx::Conv_885)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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/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_890, %onnx::Conv_891)
%/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_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/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/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.1/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_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/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_896, %onnx::Conv_897)
%/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_899, %onnx::Conv_900)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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/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_905, %onnx::Conv_906)
%/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_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/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/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.1/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)
%768 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %768
}
|
val_accuracy
| 91.626602
| 1,783,506,944
| 5,969,674
|
{'zcp_epe_nas': 99.37519250079546, 'zcp_fisher': 15.233342170715332, 'zcp_flops': 28536111104.0, 'zcp_grad_norm': 74.92969512939453, 'zcp_grasp': -4.185638427734375, 'zcp_jacov': -16.06572536355413, 'zcp_l2_norm': 890.2572021484375, 'zcp_nwot': 221.18216733235153, 'zcp_params': 5969674.0, 'zcp_plain': 0.037080649286508005, 'zcp_snip': 513.1226806640625, 'zcp_synflow': 94.34690017292093, 'zcp_zen': 94.63628387451172, 'zcp_val_accuracy': 0.925480782985687}
| |
NASBench101_194175
|
NASBench101
|
194175
|
757d72bb0d90a80e53c1a39f63b84430
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_824[FLOAT, 128x3x3x3]
%onnx::Conv_825[FLOAT, 128]
%onnx::Conv_827[FLOAT, 32x128x1x1]
%onnx::Conv_828[FLOAT, 32]
%onnx::Conv_830[FLOAT, 32x128x1x1]
%onnx::Conv_833[FLOAT, 32x32x1x1]
%onnx::Conv_836[FLOAT, 32x128x1x1]
%onnx::Conv_839[FLOAT, 32x32x3x3]
%onnx::Conv_842[FLOAT, 32x32x3x3]
%onnx::Conv_845[FLOAT, 32x128x1x1]
%onnx::Conv_848[FLOAT, 32x128x1x1]
%onnx::Conv_851[FLOAT, 32x32x1x1]
%onnx::Conv_854[FLOAT, 32x128x1x1]
%onnx::Conv_857[FLOAT, 32x32x3x3]
%onnx::Conv_860[FLOAT, 32x32x3x3]
%onnx::Conv_863[FLOAT, 32x128x1x1]
%onnx::Conv_866[FLOAT, 32x128x1x1]
%onnx::Conv_869[FLOAT, 32x32x1x1]
%onnx::Conv_872[FLOAT, 32x128x1x1]
%onnx::Conv_875[FLOAT, 32x32x3x3]
%onnx::Conv_878[FLOAT, 32x32x3x3]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_882[FLOAT, 64]
%onnx::Conv_884[FLOAT, 64x128x1x1]
%onnx::Conv_887[FLOAT, 64x64x1x1]
%onnx::Conv_890[FLOAT, 64x128x1x1]
%onnx::Conv_893[FLOAT, 64x64x3x3]
%onnx::Conv_896[FLOAT, 64x64x3x3]
%onnx::Conv_899[FLOAT, 64x256x1x1]
%onnx::Conv_902[FLOAT, 64x256x1x1]
%onnx::Conv_905[FLOAT, 64x64x1x1]
%onnx::Conv_908[FLOAT, 64x256x1x1]
%onnx::Conv_911[FLOAT, 64x64x3x3]
%onnx::Conv_914[FLOAT, 64x64x3x3]
%onnx::Conv_917[FLOAT, 64x256x1x1]
%onnx::Conv_920[FLOAT, 64x256x1x1]
%onnx::Conv_923[FLOAT, 64x64x1x1]
%onnx::Conv_926[FLOAT, 64x256x1x1]
%onnx::Conv_929[FLOAT, 64x64x3x3]
%onnx::Conv_932[FLOAT, 64x64x3x3]
%onnx::Conv_935[FLOAT, 128x256x1x1]
%onnx::Conv_938[FLOAT, 128x256x1x1]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 128x256x1x1]
%onnx::Conv_947[FLOAT, 128x128x3x3]
%onnx::Conv_950[FLOAT, 128x128x3x3]
%onnx::Conv_953[FLOAT, 128x512x1x1]
%onnx::Conv_956[FLOAT, 128x512x1x1]
%onnx::Conv_959[FLOAT, 128x128x1x1]
%onnx::Conv_962[FLOAT, 128x512x1x1]
%onnx::Conv_965[FLOAT, 128x128x3x3]
%onnx::Conv_968[FLOAT, 128x128x3x3]
%onnx::Conv_971[FLOAT, 128x512x1x1]
%onnx::Conv_974[FLOAT, 128x512x1x1]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 128x512x1x1]
%onnx::Conv_983[FLOAT, 128x128x3x3]
%onnx::Conv_986[FLOAT, 128x128x3x3]
) {
%onnx::Conv_987 = Identity(%onnx::Conv_825)
%onnx::Conv_984 = Identity(%onnx::Conv_825)
%onnx::Conv_981 = Identity(%onnx::Conv_825)
%onnx::Conv_978 = Identity(%onnx::Conv_825)
%onnx::Conv_975 = Identity(%onnx::Conv_825)
%onnx::Conv_972 = Identity(%onnx::Conv_825)
%onnx::Conv_969 = Identity(%onnx::Conv_825)
%onnx::Conv_966 = Identity(%onnx::Conv_825)
%onnx::Conv_963 = Identity(%onnx::Conv_825)
%onnx::Conv_960 = Identity(%onnx::Conv_825)
%onnx::Conv_957 = Identity(%onnx::Conv_825)
%onnx::Conv_954 = Identity(%onnx::Conv_825)
%onnx::Conv_951 = Identity(%onnx::Conv_825)
%onnx::Conv_948 = Identity(%onnx::Conv_825)
%onnx::Conv_945 = Identity(%onnx::Conv_825)
%onnx::Conv_942 = Identity(%onnx::Conv_825)
%onnx::Conv_939 = Identity(%onnx::Conv_825)
%onnx::Conv_936 = Identity(%onnx::Conv_825)
%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)
%onnx::Conv_879 = Identity(%onnx::Conv_828)
%onnx::Conv_876 = Identity(%onnx::Conv_828)
%onnx::Conv_873 = Identity(%onnx::Conv_828)
%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)
%/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_824, %onnx::Conv_825)
%/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_827, %onnx::Conv_828)
%/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_830, %onnx::Conv_831)
%/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_833, %onnx::Conv_834)
%/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_836, %onnx::Conv_837)
%/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_839, %onnx::Conv_840)
%/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.1/maxpool/MaxPool_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/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.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.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_845, %onnx::Conv_846)
%/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_848, %onnx::Conv_849)
%/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_851, %onnx::Conv_852)
%/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_854, %onnx::Conv_855)
%/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_857, %onnx::Conv_858)
%/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.1/maxpool/MaxPool_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/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/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.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_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/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_866, %onnx::Conv_867)
%/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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_875, %onnx::Conv_876)
%/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.1/maxpool/MaxPool_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/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.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.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_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/input_op.2/conv_bn_relu/conv_bn_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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/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_893, %onnx::Conv_894)
%/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.1/maxpool/MaxPool_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/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.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.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_899, %onnx::Conv_900)
%/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/Concat_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/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_905, %onnx::Conv_906)
%/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_908, %onnx::Conv_909)
%/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_911, %onnx::Conv_912)
%/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.1/maxpool/MaxPool_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/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.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.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_917, %onnx::Conv_918)
%/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/Concat_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/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_923, %onnx::Conv_924)
%/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_926, %onnx::Conv_927)
%/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_929, %onnx::Conv_930)
%/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.1/maxpool/MaxPool_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/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.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.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_935, %onnx::Conv_936)
%/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_938, %onnx::Conv_939)
%/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_941, %onnx::Conv_942)
%/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_944, %onnx::Conv_945)
%/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_947, %onnx::Conv_948)
%/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.1/maxpool/MaxPool_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/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.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.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_953, %onnx::Conv_954)
%/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_956, %onnx::Conv_957)
%/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_959, %onnx::Conv_960)
%/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_962, %onnx::Conv_963)
%/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_965, %onnx::Conv_966)
%/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.1/maxpool/MaxPool_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/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.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.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_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/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_974, %onnx::Conv_975)
%/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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_983, %onnx::Conv_984)
%/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.1/maxpool/MaxPool_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/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.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.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)
%822 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %822
}
|
val_accuracy
| 92.748398
| 576,333,824
| 1,893,898
|
{'zcp_epe_nas': 124.6990946280927, 'zcp_fisher': 1.315778017044067, 'zcp_flops': 9221341184.0, 'zcp_grad_norm': 24.907779693603516, 'zcp_grasp': -0.168228149414062, 'zcp_jacov': -16.05897954187499, 'zcp_l2_norm': 908.6142578125, 'zcp_nwot': 214.19279397782472, 'zcp_params': 1893898.0, 'zcp_plain': 0.004140050150454, 'zcp_snip': 122.97354125976562, 'zcp_synflow': 76.47008577792295, 'zcp_zen': 90.21129608154297, 'zcp_val_accuracy': 0.9125601053237911}
| |
NASBench101_131707
|
NASBench101
|
131707
|
4fa07b17b1a0fb1f7dd69cf68ad34293
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_1007[FLOAT, 128x3x3x3]
%onnx::Conv_1008[FLOAT, 128]
%onnx::Conv_1010[FLOAT, 43x128x1x1]
%onnx::Conv_1011[FLOAT, 43]
%onnx::Conv_1013[FLOAT, 43x128x1x1]
%onnx::Conv_1016[FLOAT, 43x43x1x1]
%onnx::Conv_1019[FLOAT, 43x43x3x3]
%onnx::Conv_1022[FLOAT, 42x128x1x1]
%onnx::Conv_1023[FLOAT, 42]
%onnx::Conv_1025[FLOAT, 42x42x1x1]
%onnx::Conv_1028[FLOAT, 42x42x1x1]
%onnx::Conv_1031[FLOAT, 43x128x1x1]
%onnx::Conv_1034[FLOAT, 43x128x1x1]
%onnx::Conv_1037[FLOAT, 43x43x1x1]
%onnx::Conv_1040[FLOAT, 43x43x3x3]
%onnx::Conv_1043[FLOAT, 42x128x1x1]
%onnx::Conv_1046[FLOAT, 42x42x1x1]
%onnx::Conv_1049[FLOAT, 42x42x1x1]
%onnx::Conv_1052[FLOAT, 43x128x1x1]
%onnx::Conv_1055[FLOAT, 43x128x1x1]
%onnx::Conv_1058[FLOAT, 43x43x1x1]
%onnx::Conv_1061[FLOAT, 43x43x3x3]
%onnx::Conv_1064[FLOAT, 42x128x1x1]
%onnx::Conv_1067[FLOAT, 42x42x1x1]
%onnx::Conv_1070[FLOAT, 42x42x1x1]
%onnx::Conv_1073[FLOAT, 86x128x1x1]
%onnx::Conv_1074[FLOAT, 86]
%onnx::Conv_1076[FLOAT, 85x128x1x1]
%onnx::Conv_1077[FLOAT, 85]
%onnx::Conv_1079[FLOAT, 85x85x1x1]
%onnx::Conv_1082[FLOAT, 85x85x3x3]
%onnx::Conv_1085[FLOAT, 85x128x1x1]
%onnx::Conv_1088[FLOAT, 85x85x1x1]
%onnx::Conv_1091[FLOAT, 85x85x1x1]
%onnx::Conv_1094[FLOAT, 86x256x1x1]
%onnx::Conv_1097[FLOAT, 85x256x1x1]
%onnx::Conv_1100[FLOAT, 85x85x1x1]
%onnx::Conv_1103[FLOAT, 85x85x3x3]
%onnx::Conv_1106[FLOAT, 85x256x1x1]
%onnx::Conv_1109[FLOAT, 85x85x1x1]
%onnx::Conv_1112[FLOAT, 85x85x1x1]
%onnx::Conv_1115[FLOAT, 86x256x1x1]
%onnx::Conv_1118[FLOAT, 85x256x1x1]
%onnx::Conv_1121[FLOAT, 85x85x1x1]
%onnx::Conv_1124[FLOAT, 85x85x3x3]
%onnx::Conv_1127[FLOAT, 85x256x1x1]
%onnx::Conv_1130[FLOAT, 85x85x1x1]
%onnx::Conv_1133[FLOAT, 85x85x1x1]
%onnx::Conv_1136[FLOAT, 171x256x1x1]
%onnx::Conv_1137[FLOAT, 171]
%onnx::Conv_1139[FLOAT, 171x256x1x1]
%onnx::Conv_1142[FLOAT, 171x171x1x1]
%onnx::Conv_1145[FLOAT, 171x171x3x3]
%onnx::Conv_1148[FLOAT, 170x256x1x1]
%onnx::Conv_1149[FLOAT, 170]
%onnx::Conv_1151[FLOAT, 170x170x1x1]
%onnx::Conv_1154[FLOAT, 170x170x1x1]
%onnx::Conv_1157[FLOAT, 171x512x1x1]
%onnx::Conv_1160[FLOAT, 171x512x1x1]
%onnx::Conv_1163[FLOAT, 171x171x1x1]
%onnx::Conv_1166[FLOAT, 171x171x3x3]
%onnx::Conv_1169[FLOAT, 170x512x1x1]
%onnx::Conv_1172[FLOAT, 170x170x1x1]
%onnx::Conv_1175[FLOAT, 170x170x1x1]
%onnx::Conv_1178[FLOAT, 171x512x1x1]
%onnx::Conv_1181[FLOAT, 171x512x1x1]
%onnx::Conv_1184[FLOAT, 171x171x1x1]
%onnx::Conv_1187[FLOAT, 171x171x3x3]
%onnx::Conv_1190[FLOAT, 170x512x1x1]
%onnx::Conv_1193[FLOAT, 170x170x1x1]
%onnx::Conv_1196[FLOAT, 170x170x1x1]
) {
%onnx::Conv_1197 = Identity(%onnx::Conv_1149)
%onnx::Conv_1194 = Identity(%onnx::Conv_1149)
%onnx::Conv_1191 = Identity(%onnx::Conv_1149)
%onnx::Conv_1188 = Identity(%onnx::Conv_1137)
%onnx::Conv_1185 = Identity(%onnx::Conv_1137)
%onnx::Conv_1182 = Identity(%onnx::Conv_1137)
%onnx::Conv_1179 = Identity(%onnx::Conv_1137)
%onnx::Conv_1176 = Identity(%onnx::Conv_1149)
%onnx::Conv_1173 = Identity(%onnx::Conv_1149)
%onnx::Conv_1170 = Identity(%onnx::Conv_1149)
%onnx::Conv_1167 = Identity(%onnx::Conv_1137)
%onnx::Conv_1164 = Identity(%onnx::Conv_1137)
%onnx::Conv_1161 = Identity(%onnx::Conv_1137)
%onnx::Conv_1158 = Identity(%onnx::Conv_1137)
%onnx::Conv_1155 = Identity(%onnx::Conv_1149)
%onnx::Conv_1152 = Identity(%onnx::Conv_1149)
%onnx::Conv_1146 = Identity(%onnx::Conv_1137)
%onnx::Conv_1143 = Identity(%onnx::Conv_1137)
%onnx::Conv_1140 = Identity(%onnx::Conv_1137)
%onnx::Conv_1134 = Identity(%onnx::Conv_1077)
%onnx::Conv_1131 = Identity(%onnx::Conv_1077)
%onnx::Conv_1128 = Identity(%onnx::Conv_1077)
%onnx::Conv_1125 = Identity(%onnx::Conv_1077)
%onnx::Conv_1122 = Identity(%onnx::Conv_1077)
%onnx::Conv_1119 = Identity(%onnx::Conv_1077)
%onnx::Conv_1116 = Identity(%onnx::Conv_1074)
%onnx::Conv_1113 = Identity(%onnx::Conv_1077)
%onnx::Conv_1110 = Identity(%onnx::Conv_1077)
%onnx::Conv_1107 = Identity(%onnx::Conv_1077)
%onnx::Conv_1104 = Identity(%onnx::Conv_1077)
%onnx::Conv_1101 = Identity(%onnx::Conv_1077)
%onnx::Conv_1098 = Identity(%onnx::Conv_1077)
%onnx::Conv_1095 = Identity(%onnx::Conv_1074)
%onnx::Conv_1092 = Identity(%onnx::Conv_1077)
%onnx::Conv_1089 = Identity(%onnx::Conv_1077)
%onnx::Conv_1086 = Identity(%onnx::Conv_1077)
%onnx::Conv_1083 = Identity(%onnx::Conv_1077)
%onnx::Conv_1080 = Identity(%onnx::Conv_1077)
%onnx::Conv_1071 = Identity(%onnx::Conv_1023)
%onnx::Conv_1068 = Identity(%onnx::Conv_1023)
%onnx::Conv_1065 = Identity(%onnx::Conv_1023)
%onnx::Conv_1062 = Identity(%onnx::Conv_1011)
%onnx::Conv_1059 = Identity(%onnx::Conv_1011)
%onnx::Conv_1056 = Identity(%onnx::Conv_1011)
%onnx::Conv_1053 = Identity(%onnx::Conv_1011)
%onnx::Conv_1050 = Identity(%onnx::Conv_1023)
%onnx::Conv_1047 = Identity(%onnx::Conv_1023)
%onnx::Conv_1044 = Identity(%onnx::Conv_1023)
%onnx::Conv_1041 = Identity(%onnx::Conv_1011)
%onnx::Conv_1038 = Identity(%onnx::Conv_1011)
%onnx::Conv_1035 = Identity(%onnx::Conv_1011)
%onnx::Conv_1032 = Identity(%onnx::Conv_1011)
%onnx::Conv_1029 = Identity(%onnx::Conv_1023)
%onnx::Conv_1026 = Identity(%onnx::Conv_1023)
%onnx::Conv_1020 = Identity(%onnx::Conv_1011)
%onnx::Conv_1017 = Identity(%onnx::Conv_1011)
%onnx::Conv_1014 = Identity(%onnx::Conv_1011)
%/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_1007, %onnx::Conv_1008)
%/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_1010, %onnx::Conv_1011)
%/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_1013, %onnx::Conv_1014)
%/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_1016, %onnx::Conv_1017)
%/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_1019, %onnx::Conv_1020)
%/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_1022, %onnx::Conv_1023)
%/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/input_op.4/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_3_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/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/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_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/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_1028, %onnx::Conv_1029)
%/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/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/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_1031, %onnx::Conv_1032)
%/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_1034, %onnx::Conv_1035)
%/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_1037, %onnx::Conv_1038)
%/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_1040, %onnx::Conv_1041)
%/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_1043, %onnx::Conv_1044)
%/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/input_op.4/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_3_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/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/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_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/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_1049, %onnx::Conv_1050)
%/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/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/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_1052, %onnx::Conv_1053)
%/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_1055, %onnx::Conv_1056)
%/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_1058, %onnx::Conv_1059)
%/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_1061, %onnx::Conv_1062)
%/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_1064, %onnx::Conv_1065)
%/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/input_op.4/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_3_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/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/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_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/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_1070, %onnx::Conv_1071)
%/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/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/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_1073, %onnx::Conv_1074)
%/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_1076, %onnx::Conv_1077)
%/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_1079, %onnx::Conv_1080)
%/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_1082, %onnx::Conv_1083)
%/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_1085, %onnx::Conv_1086)
%/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/input_op.4/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_3_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/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_4_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_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_1091, %onnx::Conv_1092)
%/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/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/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_1094, %onnx::Conv_1095)
%/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/Concat_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/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_1100, %onnx::Conv_1101)
%/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_1103, %onnx::Conv_1104)
%/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_1106, %onnx::Conv_1107)
%/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/input_op.4/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_3_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/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_4_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_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_1112, %onnx::Conv_1113)
%/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/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/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_1115, %onnx::Conv_1116)
%/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/Concat_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/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_1121, %onnx::Conv_1122)
%/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_1124, %onnx::Conv_1125)
%/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_1127, %onnx::Conv_1128)
%/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/input_op.4/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_3_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/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_4_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_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_1133, %onnx::Conv_1134)
%/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/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/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_1136, %onnx::Conv_1137)
%/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_1139, %onnx::Conv_1140)
%/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_1142, %onnx::Conv_1143)
%/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_1145, %onnx::Conv_1146)
%/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_1148, %onnx::Conv_1149)
%/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/input_op.4/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_3_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/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/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_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/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_1154, %onnx::Conv_1155)
%/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/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/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_1157, %onnx::Conv_1158)
%/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_1160, %onnx::Conv_1161)
%/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_1163, %onnx::Conv_1164)
%/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_1166, %onnx::Conv_1167)
%/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_1169, %onnx::Conv_1170)
%/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/input_op.4/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_3_output_0, %onnx::Conv_1172, %onnx::Conv_1173)
%/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/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_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/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_1175, %onnx::Conv_1176)
%/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/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/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_1178, %onnx::Conv_1179)
%/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_1181, %onnx::Conv_1182)
%/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_1184, %onnx::Conv_1185)
%/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_1187, %onnx::Conv_1188)
%/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_1190, %onnx::Conv_1191)
%/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/input_op.4/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_3_output_0, %onnx::Conv_1193, %onnx::Conv_1194)
%/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/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_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/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_1196, %onnx::Conv_1197)
%/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/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/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)
%1005 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %1005
}
|
val_accuracy
| 91.756809
| 692,322,048
| 2,266,506
|
{'zcp_epe_nas': 121.94040407666357, 'zcp_fisher': 6.24843692779541, 'zcp_flops': 11077152768.0, 'zcp_grad_norm': 61.9678840637207, 'zcp_grasp': -8.8702392578125, 'zcp_jacov': -16.035926617539204, 'zcp_l2_norm': 1078.3516845703125, 'zcp_nwot': 221.07499538630327, 'zcp_params': 2266506.0, 'zcp_plain': -0.018460212275385003, 'zcp_snip': 301.0548400878906, 'zcp_synflow': 100.50369964403917, 'zcp_zen': 91.35502624511719, 'zcp_val_accuracy': 0.867988765239715}
| |
NASBench101_107280
|
NASBench101
|
107280
|
40d136282d84490c83702b56b5636d9b
|
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, 64x128x1x1]
%onnx::Conv_683[FLOAT, 64x64x1x1]
%onnx::Conv_686[FLOAT, 64x128x1x1]
%onnx::Conv_689[FLOAT, 64x64x1x1]
%onnx::Conv_692[FLOAT, 64x128x1x1]
%onnx::Conv_695[FLOAT, 64x64x1x1]
%onnx::Conv_698[FLOAT, 64x128x1x1]
%onnx::Conv_701[FLOAT, 64x64x1x1]
%onnx::Conv_704[FLOAT, 64x128x1x1]
%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, 128x256x1x1]
%onnx::Conv_731[FLOAT, 128x128x1x1]
%onnx::Conv_734[FLOAT, 128x256x1x1]
%onnx::Conv_737[FLOAT, 128x128x1x1]
%onnx::Conv_740[FLOAT, 128x256x1x1]
%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, 256x512x1x1]
%onnx::Conv_767[FLOAT, 256x256x1x1]
%onnx::Conv_770[FLOAT, 256x512x1x1]
%onnx::Conv_773[FLOAT, 256x256x1x1]
%onnx::Conv_776[FLOAT, 256x512x1x1]
%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/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_677, %onnx::Conv_678)
%/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_680, %onnx::Conv_681)
%/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/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.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_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/Add_3_output_0 = Add(%/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/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_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.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.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_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/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_689, %onnx::Conv_690)
%/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_692, %onnx::Conv_693)
%/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/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.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_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/Add_3_output_0 = Add(%/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/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_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.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.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_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/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_701, %onnx::Conv_702)
%/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_704, %onnx::Conv_705)
%/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/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.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_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/Add_3_output_0 = Add(%/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/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_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.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.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_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/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_713, %onnx::Conv_714)
%/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_716, %onnx::Conv_717)
%/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/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.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_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/Add_3_output_0 = Add(%/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/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_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.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.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_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/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_725, %onnx::Conv_726)
%/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_728, %onnx::Conv_729)
%/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/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.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_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/Add_3_output_0 = Add(%/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/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_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.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.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_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/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_737, %onnx::Conv_738)
%/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_740, %onnx::Conv_741)
%/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/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.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_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/Add_3_output_0 = Add(%/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/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_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.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.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_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/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_749, %onnx::Conv_750)
%/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_752, %onnx::Conv_753)
%/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/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.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_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/Add_3_output_0 = Add(%/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/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_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.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.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_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/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_761, %onnx::Conv_762)
%/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_764, %onnx::Conv_765)
%/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/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.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_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/Add_3_output_0 = Add(%/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/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_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.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.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_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/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_773, %onnx::Conv_774)
%/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_776, %onnx::Conv_777)
%/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/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.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_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/Add_3_output_0 = Add(%/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/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_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.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.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)
%669 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %669
}
|
val_accuracy
| 88.010818
| 438,577,152
| 1,404,042
|
{'zcp_epe_nas': 115.33622188139135, 'zcp_fisher': 21.793611526489258, 'zcp_flops': 7017234432.0, 'zcp_grad_norm': 90.1445083618164, 'zcp_grasp': -16.5106201171875, 'zcp_jacov': -16.043815264847865, 'zcp_l2_norm': 695.2999267578125, 'zcp_nwot': 218.71428528332808, 'zcp_params': 1404042.0, 'zcp_plain': 0.025717597454786002, 'zcp_snip': 508.3374328613281, 'zcp_synflow': 81.33486217544149, 'zcp_zen': 62.771305084228516, 'zcp_val_accuracy': 0.933293282985687}
| |
NASBench101_250728
|
NASBench101
|
250728
|
97c87c870ec585efc31409d076127ff4
|
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, 128x128x1x1]
%onnx::Conv_800[FLOAT, 128x128x3x3]
%onnx::Conv_803[FLOAT, 128x128x3x3]
%onnx::Conv_806[FLOAT, 128x128x1x1]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 128x128x3x3]
%onnx::Conv_818[FLOAT, 128x128x3x3]
%onnx::Conv_821[FLOAT, 128x128x1x1]
%onnx::Conv_824[FLOAT, 128x128x1x1]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 128x128x3x3]
%onnx::Conv_833[FLOAT, 128x128x3x3]
%onnx::Conv_836[FLOAT, 256x128x1x1]
%onnx::Conv_837[FLOAT, 256]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x128x1x1]
%onnx::Conv_845[FLOAT, 256x256x3x3]
%onnx::Conv_848[FLOAT, 256x256x3x3]
%onnx::Conv_851[FLOAT, 256x256x1x1]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_857[FLOAT, 256x256x1x1]
%onnx::Conv_860[FLOAT, 256x256x3x3]
%onnx::Conv_863[FLOAT, 256x256x3x3]
%onnx::Conv_866[FLOAT, 256x256x1x1]
%onnx::Conv_869[FLOAT, 256x256x1x1]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_875[FLOAT, 256x256x3x3]
%onnx::Conv_878[FLOAT, 256x256x3x3]
%onnx::Conv_881[FLOAT, 512x256x1x1]
%onnx::Conv_882[FLOAT, 512]
%onnx::Conv_884[FLOAT, 512x512x1x1]
%onnx::Conv_887[FLOAT, 512x256x1x1]
%onnx::Conv_890[FLOAT, 512x512x3x3]
%onnx::Conv_893[FLOAT, 512x512x3x3]
%onnx::Conv_896[FLOAT, 512x512x1x1]
%onnx::Conv_899[FLOAT, 512x512x1x1]
%onnx::Conv_902[FLOAT, 512x512x1x1]
%onnx::Conv_905[FLOAT, 512x512x3x3]
%onnx::Conv_908[FLOAT, 512x512x3x3]
%onnx::Conv_911[FLOAT, 512x512x1x1]
%onnx::Conv_914[FLOAT, 512x512x1x1]
%onnx::Conv_917[FLOAT, 512x512x1x1]
%onnx::Conv_920[FLOAT, 512x512x3x3]
%onnx::Conv_923[FLOAT, 512x512x3x3]
) {
%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/input_op.2/conv_bn_relu/conv_bn_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/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_800, %onnx::Conv_801)
%/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/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 = <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/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_803, %onnx::Conv_804)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_815, %onnx::Conv_816)
%/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/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 = <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/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_818, %onnx::Conv_819)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_830, %onnx::Conv_831)
%/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/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 = <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/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_833, %onnx::Conv_834)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_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/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_845, %onnx::Conv_846)
%/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/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/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/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_848, %onnx::Conv_849)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_860, %onnx::Conv_861)
%/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/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/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/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_863, %onnx::Conv_864)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_875, %onnx::Conv_876)
%/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/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/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/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_878, %onnx::Conv_879)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_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/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_890, %onnx::Conv_891)
%/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/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 = <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/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_893, %onnx::Conv_894)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_905, %onnx::Conv_906)
%/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/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 = <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/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_908, %onnx::Conv_909)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_920, %onnx::Conv_921)
%/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/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 = <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/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_923, %onnx::Conv_924)
%/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)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%786 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %786
}
|
val_accuracy
| 90.254408
| 6,310,340,608
| 21,384,074
|
{'zcp_epe_nas': 60.02020813687927, 'zcp_fisher': 734.7810668945312, 'zcp_flops': 100965449728.0, 'zcp_grad_norm': 432.9894714355469, 'zcp_grasp': 160.95703125, 'zcp_jacov': -16.054449443252402, 'zcp_l2_norm': 1029.9827880859375, 'zcp_nwot': 231.9524992853714, 'zcp_params': 21384074.0, 'zcp_plain': 0.10432896763086301, 'zcp_snip': 3497.302001953125, 'zcp_synflow': 130.3383204505653, 'zcp_zen': 101.6578140258789, 'zcp_val_accuracy': 0.9134615659713741}
| |
NASBench101_113951
|
NASBench101
|
113951
|
44d3234d42fbd92aba41df2471fb5c57
|
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, 64x64x1x1]
%onnx::Conv_890[FLOAT, 64x64x3x3]
%onnx::Conv_893[FLOAT, 64x64x3x3]
%onnx::Conv_896[FLOAT, 64x64x1x1]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x64x1x1]
%onnx::Conv_908[FLOAT, 64x64x3x3]
%onnx::Conv_911[FLOAT, 64x64x3x3]
%onnx::Conv_914[FLOAT, 64x64x1x1]
%onnx::Conv_917[FLOAT, 64x128x1x1]
%onnx::Conv_920[FLOAT, 64x64x3x3]
%onnx::Conv_923[FLOAT, 64x64x1x1]
%onnx::Conv_926[FLOAT, 64x64x3x3]
%onnx::Conv_929[FLOAT, 64x64x3x3]
%onnx::Conv_932[FLOAT, 64x64x1x1]
%onnx::Conv_935[FLOAT, 128x128x1x1]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 128x128x3x3]
%onnx::Conv_947[FLOAT, 128x128x3x3]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x128x1x1]
%onnx::Conv_962[FLOAT, 128x128x3x3]
%onnx::Conv_965[FLOAT, 128x128x3x3]
%onnx::Conv_968[FLOAT, 128x128x1x1]
%onnx::Conv_971[FLOAT, 128x256x1x1]
%onnx::Conv_974[FLOAT, 128x128x3x3]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 128x128x3x3]
%onnx::Conv_983[FLOAT, 128x128x3x3]
%onnx::Conv_986[FLOAT, 128x128x1x1]
%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, 256x256x3x3]
%onnx::Conv_1004[FLOAT, 256x256x1x1]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x256x1x1]
%onnx::Conv_1016[FLOAT, 256x256x3x3]
%onnx::Conv_1019[FLOAT, 256x256x3x3]
%onnx::Conv_1022[FLOAT, 256x256x1x1]
%onnx::Conv_1025[FLOAT, 256x512x1x1]
%onnx::Conv_1028[FLOAT, 256x256x3x3]
%onnx::Conv_1031[FLOAT, 256x256x1x1]
%onnx::Conv_1034[FLOAT, 256x256x3x3]
%onnx::Conv_1037[FLOAT, 256x256x3x3]
%onnx::Conv_1040[FLOAT, 256x256x1x1]
) {
%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/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_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/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_890, %onnx::Conv_891)
%/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_893, %onnx::Conv_894)
%/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.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/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_896, %onnx::Conv_897)
%/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_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/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_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/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_908, %onnx::Conv_909)
%/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_911, %onnx::Conv_912)
%/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.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/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_914, %onnx::Conv_915)
%/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_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/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_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/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_926, %onnx::Conv_927)
%/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_929, %onnx::Conv_930)
%/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.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/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_932, %onnx::Conv_933)
%/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_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/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_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/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_944, %onnx::Conv_945)
%/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_947, %onnx::Conv_948)
%/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.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/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_950, %onnx::Conv_951)
%/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_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/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_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/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_962, %onnx::Conv_963)
%/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_965, %onnx::Conv_966)
%/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.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/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_968, %onnx::Conv_969)
%/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_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/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_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/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_980, %onnx::Conv_981)
%/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_983, %onnx::Conv_984)
%/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.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/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_986, %onnx::Conv_987)
%/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_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/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_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/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_998, %onnx::Conv_999)
%/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_1001, %onnx::Conv_1002)
%/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.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/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_1004, %onnx::Conv_1005)
%/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_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/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_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/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_1016, %onnx::Conv_1017)
%/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_1019, %onnx::Conv_1020)
%/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.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/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_1022, %onnx::Conv_1023)
%/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_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/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_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/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_1034, %onnx::Conv_1035)
%/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_1037, %onnx::Conv_1038)
%/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.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/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_1040, %onnx::Conv_1041)
%/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)
%876 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %876
}
|
val_accuracy
| 91.065705
| 2,348,296,192
| 7,942,538
|
{'zcp_epe_nas': 68.4175022567079, 'zcp_fisher': 4025.938720703125, 'zcp_flops': 37572739072.0, 'zcp_grad_norm': 1080.3812255859375, 'zcp_grasp': 3357.5625, 'zcp_jacov': -16.066589486906757, 'zcp_l2_norm': 948.0304565429688, 'zcp_nwot': 224.6093184684003, 'zcp_params': 7942538.0, 'zcp_plain': 0.0040742754936210004, 'zcp_snip': 5660.3779296875, 'zcp_synflow': 173.14917937847167, 'zcp_zen': 102.19981384277344, 'zcp_val_accuracy': 0.9258813858032221}
| |
NASBench101_25943
|
NASBench101
|
25943
|
0fac15c45d422b9c0a46bde06ad1c0a5
|
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, 64x64x1x1]
%onnx::Conv_899[FLOAT, 64x64x1x1]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 128x128x1x1]
%onnx::Conv_908[FLOAT, 64x128x1x1]
%onnx::Conv_911[FLOAT, 64x64x1x1]
%onnx::Conv_914[FLOAT, 64x64x1x1]
%onnx::Conv_917[FLOAT, 64x64x1x1]
%onnx::Conv_920[FLOAT, 64x64x3x3]
%onnx::Conv_923[FLOAT, 128x128x1x1]
%onnx::Conv_926[FLOAT, 64x128x1x1]
%onnx::Conv_929[FLOAT, 64x64x1x1]
%onnx::Conv_932[FLOAT, 64x64x1x1]
%onnx::Conv_935[FLOAT, 64x64x1x1]
%onnx::Conv_938[FLOAT, 64x64x3x3]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%onnx::Conv_953[FLOAT, 128x128x1x1]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 256x128x1x1]
%onnx::Conv_960[FLOAT, 256]
%onnx::Conv_962[FLOAT, 128x256x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x128x1x1]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%onnx::Conv_974[FLOAT, 128x128x3x3]
%onnx::Conv_977[FLOAT, 256x256x1x1]
%onnx::Conv_980[FLOAT, 128x256x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x128x1x1]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 128x128x3x3]
%onnx::Conv_995[FLOAT, 256x256x1x1]
%onnx::Conv_998[FLOAT, 256x256x1x1]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 256x256x1x1]
%onnx::Conv_1007[FLOAT, 256x256x1x1]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 512x256x1x1]
%onnx::Conv_1014[FLOAT, 512]
%onnx::Conv_1016[FLOAT, 256x512x1x1]
%onnx::Conv_1019[FLOAT, 256x256x1x1]
%onnx::Conv_1022[FLOAT, 256x256x1x1]
%onnx::Conv_1025[FLOAT, 256x256x1x1]
%onnx::Conv_1028[FLOAT, 256x256x3x3]
%onnx::Conv_1031[FLOAT, 512x512x1x1]
%onnx::Conv_1034[FLOAT, 256x512x1x1]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 256x256x1x1]
%onnx::Conv_1043[FLOAT, 256x256x1x1]
%onnx::Conv_1046[FLOAT, 256x256x3x3]
%onnx::Conv_1049[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1050 = Identity(%onnx::Conv_1014)
%onnx::Conv_1047 = Identity(%onnx::Conv_960)
%onnx::Conv_1044 = Identity(%onnx::Conv_960)
%onnx::Conv_1041 = Identity(%onnx::Conv_960)
%onnx::Conv_1038 = Identity(%onnx::Conv_960)
%onnx::Conv_1035 = Identity(%onnx::Conv_960)
%onnx::Conv_1032 = Identity(%onnx::Conv_1014)
%onnx::Conv_1029 = Identity(%onnx::Conv_960)
%onnx::Conv_1026 = Identity(%onnx::Conv_960)
%onnx::Conv_1023 = Identity(%onnx::Conv_960)
%onnx::Conv_1020 = Identity(%onnx::Conv_960)
%onnx::Conv_1017 = 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_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_960)
%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_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_888)
%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_888)
%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_888)
%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/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/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.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_899, %onnx::Conv_900)
%/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_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/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.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_6_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_6_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/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.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_917, %onnx::Conv_918)
%/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_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/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.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_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_6_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_6_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/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.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_935, %onnx::Conv_936)
%/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_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/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.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_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_6_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_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_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/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.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_953, %onnx::Conv_954)
%/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_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/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.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_6_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_6_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/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.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_971, %onnx::Conv_972)
%/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_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/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.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_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_6_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_6_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/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.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_989, %onnx::Conv_990)
%/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_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/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.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_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_6_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_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_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/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.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_1007, %onnx::Conv_1008)
%/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_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/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.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_6_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_6_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/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.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_1025, %onnx::Conv_1026)
%/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_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/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.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_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_6_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_6_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/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.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_1043, %onnx::Conv_1044)
%/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_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/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)
%/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_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_6_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_6_output_0)
%885 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %885
}
|
val_accuracy
| 92.96875
| 1,336,027,136
| 4,426,762
|
{'zcp_epe_nas': 72.50376881491677, 'zcp_fisher': 6.620876312255859, 'zcp_flops': 21376434176.0, 'zcp_grad_norm': 67.53312683105469, 'zcp_grasp': 0.2965087890625, 'zcp_jacov': -16.063362687924744, 'zcp_l2_norm': 993.9755859375, 'zcp_nwot': 227.0245827358862, 'zcp_params': 4426762.0, 'zcp_plain': 0.0074452599510550005, 'zcp_snip': 397.85302734375, 'zcp_synflow': 131.0815220165892, 'zcp_zen': 90.75906372070312, 'zcp_val_accuracy': 0.9164663553237911}
| |
NASBench101_56557
|
NASBench101
|
56557
|
2265a8567cb0bea2ef20ab277f123934
|
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, 64x64x3x3]
%onnx::Conv_806[FLOAT, 64x64x3x3]
%onnx::Conv_809[FLOAT, 64x64x3x3]
%onnx::Conv_812[FLOAT, 64x128x1x1]
%onnx::Conv_815[FLOAT, 64x128x1x1]
%onnx::Conv_818[FLOAT, 64x64x3x3]
%onnx::Conv_821[FLOAT, 64x64x3x3]
%onnx::Conv_824[FLOAT, 64x64x3x3]
%onnx::Conv_827[FLOAT, 64x128x1x1]
%onnx::Conv_830[FLOAT, 64x128x1x1]
%onnx::Conv_833[FLOAT, 64x64x3x3]
%onnx::Conv_836[FLOAT, 64x64x3x3]
%onnx::Conv_839[FLOAT, 64x64x3x3]
%onnx::Conv_842[FLOAT, 64x128x1x1]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x3x3]
%onnx::Conv_851[FLOAT, 128x128x3x3]
%onnx::Conv_854[FLOAT, 128x128x3x3]
%onnx::Conv_857[FLOAT, 128x128x1x1]
%onnx::Conv_860[FLOAT, 128x256x1x1]
%onnx::Conv_863[FLOAT, 128x128x3x3]
%onnx::Conv_866[FLOAT, 128x128x3x3]
%onnx::Conv_869[FLOAT, 128x128x3x3]
%onnx::Conv_872[FLOAT, 128x256x1x1]
%onnx::Conv_875[FLOAT, 128x256x1x1]
%onnx::Conv_878[FLOAT, 128x128x3x3]
%onnx::Conv_881[FLOAT, 128x128x3x3]
%onnx::Conv_884[FLOAT, 128x128x3x3]
%onnx::Conv_887[FLOAT, 128x256x1x1]
%onnx::Conv_890[FLOAT, 256x256x1x1]
%onnx::Conv_891[FLOAT, 256]
%onnx::Conv_893[FLOAT, 256x256x3x3]
%onnx::Conv_896[FLOAT, 256x256x3x3]
%onnx::Conv_899[FLOAT, 256x256x3x3]
%onnx::Conv_902[FLOAT, 256x256x1x1]
%onnx::Conv_905[FLOAT, 256x512x1x1]
%onnx::Conv_908[FLOAT, 256x256x3x3]
%onnx::Conv_911[FLOAT, 256x256x3x3]
%onnx::Conv_914[FLOAT, 256x256x3x3]
%onnx::Conv_917[FLOAT, 256x512x1x1]
%onnx::Conv_920[FLOAT, 256x512x1x1]
%onnx::Conv_923[FLOAT, 256x256x3x3]
%onnx::Conv_926[FLOAT, 256x256x3x3]
%onnx::Conv_929[FLOAT, 256x256x3x3]
%onnx::Conv_932[FLOAT, 256x512x1x1]
) {
%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/conv3x3/conv_bn_relu/conv_bn_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_803, %onnx::Conv_804)
%/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_806, %onnx::Conv_807)
%/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_809, %onnx::Conv_810)
%/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_812, %onnx::Conv_813)
%/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/input_op.4/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.2/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_818, %onnx::Conv_819)
%/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_821, %onnx::Conv_822)
%/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_824, %onnx::Conv_825)
%/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_827, %onnx::Conv_828)
%/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/input_op.4/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.2/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_833, %onnx::Conv_834)
%/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_836, %onnx::Conv_837)
%/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_839, %onnx::Conv_840)
%/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_842, %onnx::Conv_843)
%/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/input_op.4/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.2/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_848, %onnx::Conv_849)
%/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_851, %onnx::Conv_852)
%/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_854, %onnx::Conv_855)
%/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_857, %onnx::Conv_858)
%/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/input_op.4/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.2/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_863, %onnx::Conv_864)
%/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_866, %onnx::Conv_867)
%/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_869, %onnx::Conv_870)
%/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_872, %onnx::Conv_873)
%/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/input_op.4/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.2/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_878, %onnx::Conv_879)
%/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_881, %onnx::Conv_882)
%/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_884, %onnx::Conv_885)
%/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_887, %onnx::Conv_888)
%/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/input_op.4/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.2/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_893, %onnx::Conv_894)
%/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_896, %onnx::Conv_897)
%/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_899, %onnx::Conv_900)
%/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_902, %onnx::Conv_903)
%/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/input_op.4/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.2/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_908, %onnx::Conv_909)
%/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_911, %onnx::Conv_912)
%/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_914, %onnx::Conv_915)
%/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_917, %onnx::Conv_918)
%/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/input_op.4/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.2/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_923, %onnx::Conv_924)
%/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_926, %onnx::Conv_927)
%/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_929, %onnx::Conv_930)
%/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_932, %onnx::Conv_933)
%/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/input_op.4/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.2/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/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)
%795 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %795
}
|
val_accuracy
| 91.115785
| 2,328,766,464
| 7,857,930
|
{'zcp_epe_nas': 58.258540581209125, 'zcp_fisher': 138.51600646972656, 'zcp_flops': 37260263424.0, 'zcp_grad_norm': 225.34312438964844, 'zcp_grasp': -38.01904296875, 'zcp_jacov': -16.060527326328515, 'zcp_l2_norm': 843.6163330078125, 'zcp_nwot': 221.58132165170827, 'zcp_params': 7857930.0, 'zcp_plain': 0.022788263857364002, 'zcp_snip': 1359.5733642578125, 'zcp_synflow': 103.69847260190707, 'zcp_zen': 97.36097717285156, 'zcp_val_accuracy': 0.9367988705635071}
| |
NASBench101_417799
|
NASBench101
|
417799
|
fc7dbd40bdc95a3bfc63dcadbe216c4a
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_794[FLOAT, 128x3x3x3]
%onnx::Conv_795[FLOAT, 128]
%onnx::Conv_797[FLOAT, 43x128x1x1]
%onnx::Conv_798[FLOAT, 43]
%onnx::Conv_800[FLOAT, 43x43x1x1]
%onnx::Conv_803[FLOAT, 43x43x3x3]
%onnx::Conv_806[FLOAT, 42x42x3x3]
%onnx::Conv_807[FLOAT, 42]
%onnx::Conv_809[FLOAT, 42x42x3x3]
%onnx::Conv_812[FLOAT, 43x128x1x1]
%onnx::Conv_815[FLOAT, 43x43x1x1]
%onnx::Conv_818[FLOAT, 43x43x3x3]
%onnx::Conv_821[FLOAT, 42x42x3x3]
%onnx::Conv_824[FLOAT, 42x42x3x3]
%onnx::Conv_827[FLOAT, 43x128x1x1]
%onnx::Conv_830[FLOAT, 43x43x1x1]
%onnx::Conv_833[FLOAT, 43x43x3x3]
%onnx::Conv_836[FLOAT, 42x42x3x3]
%onnx::Conv_839[FLOAT, 42x42x3x3]
%onnx::Conv_842[FLOAT, 86x128x1x1]
%onnx::Conv_843[FLOAT, 86]
%onnx::Conv_845[FLOAT, 86x86x1x1]
%onnx::Conv_848[FLOAT, 85x85x3x3]
%onnx::Conv_849[FLOAT, 85]
%onnx::Conv_851[FLOAT, 85x85x3x3]
%onnx::Conv_854[FLOAT, 85x85x3x3]
%onnx::Conv_857[FLOAT, 86x256x1x1]
%onnx::Conv_860[FLOAT, 86x86x1x1]
%onnx::Conv_863[FLOAT, 85x85x3x3]
%onnx::Conv_866[FLOAT, 85x85x3x3]
%onnx::Conv_869[FLOAT, 85x85x3x3]
%onnx::Conv_872[FLOAT, 86x256x1x1]
%onnx::Conv_875[FLOAT, 86x86x1x1]
%onnx::Conv_878[FLOAT, 85x85x3x3]
%onnx::Conv_881[FLOAT, 85x85x3x3]
%onnx::Conv_884[FLOAT, 85x85x3x3]
%onnx::Conv_887[FLOAT, 171x256x1x1]
%onnx::Conv_888[FLOAT, 171]
%onnx::Conv_890[FLOAT, 171x171x1x1]
%onnx::Conv_893[FLOAT, 171x171x3x3]
%onnx::Conv_896[FLOAT, 170x170x3x3]
%onnx::Conv_897[FLOAT, 170]
%onnx::Conv_899[FLOAT, 170x170x3x3]
%onnx::Conv_902[FLOAT, 171x512x1x1]
%onnx::Conv_905[FLOAT, 171x171x1x1]
%onnx::Conv_908[FLOAT, 171x171x3x3]
%onnx::Conv_911[FLOAT, 170x170x3x3]
%onnx::Conv_914[FLOAT, 170x170x3x3]
%onnx::Conv_917[FLOAT, 171x512x1x1]
%onnx::Conv_920[FLOAT, 171x171x1x1]
%onnx::Conv_923[FLOAT, 171x171x3x3]
%onnx::Conv_926[FLOAT, 170x170x3x3]
%onnx::Conv_929[FLOAT, 170x170x3x3]
) {
%onnx::Conv_930 = Identity(%onnx::Conv_897)
%onnx::Conv_927 = Identity(%onnx::Conv_897)
%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_897)
%onnx::Conv_912 = Identity(%onnx::Conv_897)
%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_897)
%onnx::Conv_894 = Identity(%onnx::Conv_888)
%onnx::Conv_891 = Identity(%onnx::Conv_888)
%onnx::Conv_885 = Identity(%onnx::Conv_849)
%onnx::Conv_882 = Identity(%onnx::Conv_849)
%onnx::Conv_879 = Identity(%onnx::Conv_849)
%onnx::Conv_876 = Identity(%onnx::Conv_843)
%onnx::Conv_873 = Identity(%onnx::Conv_843)
%onnx::Conv_870 = Identity(%onnx::Conv_849)
%onnx::Conv_867 = Identity(%onnx::Conv_849)
%onnx::Conv_864 = Identity(%onnx::Conv_849)
%onnx::Conv_861 = Identity(%onnx::Conv_843)
%onnx::Conv_858 = Identity(%onnx::Conv_843)
%onnx::Conv_855 = Identity(%onnx::Conv_849)
%onnx::Conv_852 = Identity(%onnx::Conv_849)
%onnx::Conv_846 = Identity(%onnx::Conv_843)
%onnx::Conv_840 = Identity(%onnx::Conv_807)
%onnx::Conv_837 = Identity(%onnx::Conv_807)
%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_807)
%onnx::Conv_822 = Identity(%onnx::Conv_807)
%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_807)
%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_794, %onnx::Conv_795)
%/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_797, %onnx::Conv_798)
%/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_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_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/conv3x3/conv_bn_relu/conv_bn_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_803, %onnx::Conv_804)
%/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 = <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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_806, %onnx::Conv_807)
%/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_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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_809, %onnx::Conv_810)
%/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.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_812, %onnx::Conv_813)
%/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_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_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/conv3x3/conv_bn_relu/conv_bn_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_818, %onnx::Conv_819)
%/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 = <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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_821, %onnx::Conv_822)
%/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_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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_824, %onnx::Conv_825)
%/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.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_827, %onnx::Conv_828)
%/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_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_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/conv3x3/conv_bn_relu/conv_bn_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_833, %onnx::Conv_834)
%/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 = <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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_836, %onnx::Conv_837)
%/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_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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_839, %onnx::Conv_840)
%/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.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_842, %onnx::Conv_843)
%/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_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_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/conv3x3/conv_bn_relu/conv_bn_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_848, %onnx::Conv_849)
%/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_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_1_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/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_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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_854, %onnx::Conv_855)
%/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.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_857, %onnx::Conv_858)
%/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_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_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/conv3x3/conv_bn_relu/conv_bn_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_863, %onnx::Conv_864)
%/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_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_1_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/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_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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_869, %onnx::Conv_870)
%/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.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_872, %onnx::Conv_873)
%/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_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_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/conv3x3/conv_bn_relu/conv_bn_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_878, %onnx::Conv_879)
%/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_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_1_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/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_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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_884, %onnx::Conv_885)
%/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.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_887, %onnx::Conv_888)
%/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_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_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/conv3x3/conv_bn_relu/conv_bn_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_893, %onnx::Conv_894)
%/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 = <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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_896, %onnx::Conv_897)
%/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_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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_899, %onnx::Conv_900)
%/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.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_902, %onnx::Conv_903)
%/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_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_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/conv3x3/conv_bn_relu/conv_bn_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_908, %onnx::Conv_909)
%/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 = <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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_911, %onnx::Conv_912)
%/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_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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_914, %onnx::Conv_915)
%/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.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_917, %onnx::Conv_918)
%/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_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_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/conv3x3/conv_bn_relu/conv_bn_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_923, %onnx::Conv_924)
%/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 = <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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_926, %onnx::Conv_927)
%/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_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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_929, %onnx::Conv_930)
%/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.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)
%792 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %792
}
|
val_accuracy
| 90.745193
| 1,039,043,328
| 3,504,201
|
{'zcp_epe_nas': 124.75636995339022, 'zcp_fisher': 22.81601333618164, 'zcp_flops': 16624693248.0, 'zcp_grad_norm': 98.23223876953125, 'zcp_grasp': -13.8515625, 'zcp_jacov': -16.051654589657126, 'zcp_l2_norm': 687.5061645507812, 'zcp_nwot': 215.70672605622426, 'zcp_params': 3504201.0, 'zcp_plain': -0.016056226566433, 'zcp_snip': 484.94866943359375, 'zcp_synflow': 90.88504410159031, 'zcp_zen': 84.77229309082031, 'zcp_val_accuracy': 0.918569684028625}
| |
NASBench101_395616
|
NASBench101
|
395616
|
ef22a8fd0efba3225aa846fb678b84e7
|
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, 128x128x3x3]
%onnx::Conv_1001[FLOAT, 128x128x3x3]
%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, 128x128x3x3]
%onnx::Conv_1022[FLOAT, 128x128x3x3]
%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, 128x128x3x3]
%onnx::Conv_1043[FLOAT, 128x128x3x3]
%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, 256x128x1x1]
%onnx::Conv_1061[FLOAT, 256x256x3x3]
%onnx::Conv_1064[FLOAT, 256x256x3x3]
%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, 256x256x3x3]
%onnx::Conv_1085[FLOAT, 256x256x3x3]
%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, 256x256x3x3]
%onnx::Conv_1106[FLOAT, 256x256x3x3]
%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, 512x256x1x1]
%onnx::Conv_1124[FLOAT, 512x512x3x3]
%onnx::Conv_1127[FLOAT, 512x512x3x3]
%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, 512x512x3x3]
%onnx::Conv_1148[FLOAT, 512x512x3x3]
%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, 512x512x3x3]
%onnx::Conv_1169[FLOAT, 512x512x3x3]
%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/input_op.2/conv_bn_relu/conv_bn_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/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_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/Constant_2_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_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_1001, %onnx::Conv_1002)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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/Constant_2_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_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_1022, %onnx::Conv_1023)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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/Constant_2_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_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_1043, %onnx::Conv_1044)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_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/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_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 = <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_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_1064, %onnx::Conv_1065)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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 = <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_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_1085, %onnx::Conv_1086)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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 = <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_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_1106, %onnx::Conv_1107)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_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/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_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/Constant_2_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_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_1127, %onnx::Conv_1128)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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/Constant_2_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_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_1148, %onnx::Conv_1149)
%/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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/Constant_2_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_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_1169, %onnx::Conv_1170)
%/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.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_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
| 93.349361
| 9,307,695,104
| 31,552,906
|
{'zcp_epe_nas': 212.44726048419807, 'zcp_fisher': 54.67691421508789, 'zcp_flops': 148923121664.0, 'zcp_grad_norm': 139.9815216064453, 'zcp_grasp': -4.5137939453125, 'zcp_jacov': -16.053710687096782, 'zcp_l2_norm': 1437.466064453125, 'zcp_nwot': 237.2272058080655, 'zcp_params': 31552906.0, 'zcp_plain': 0.031689591705799006, 'zcp_snip': 1235.39501953125, 'zcp_synflow': 166.05925875663561, 'zcp_zen': 140.2421875, 'zcp_val_accuracy': 0.9093549847602841}
| |
NASBench101_282125
|
NASBench101
|
282125
|
aaba42dc57bdcebb5b4d8916d6d9a1c5
|
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, 128x128x1x1]
%onnx::Conv_983[FLOAT, 128x128x3x3]
%onnx::Conv_986[FLOAT, 128x128x1x1]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 128x128x3x3]
%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, 128x128x3x3]
%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, 128x128x3x3]
%onnx::Conv_1037[FLOAT, 128x128x1x1]
%onnx::Conv_1040[FLOAT, 128x128x1x1]
%onnx::Conv_1043[FLOAT, 256x128x1x1]
%onnx::Conv_1044[FLOAT, 256]
%onnx::Conv_1046[FLOAT, 256x256x3x3]
%onnx::Conv_1049[FLOAT, 256x128x1x1]
%onnx::Conv_1052[FLOAT, 256x128x1x1]
%onnx::Conv_1055[FLOAT, 256x256x3x3]
%onnx::Conv_1058[FLOAT, 256x128x1x1]
%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, 256x256x3x3]
%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, 256x256x3x3]
%onnx::Conv_1100[FLOAT, 256x256x1x1]
%onnx::Conv_1103[FLOAT, 256x256x1x1]
%onnx::Conv_1106[FLOAT, 512x256x1x1]
%onnx::Conv_1107[FLOAT, 512]
%onnx::Conv_1109[FLOAT, 512x512x3x3]
%onnx::Conv_1112[FLOAT, 512x256x1x1]
%onnx::Conv_1115[FLOAT, 512x256x1x1]
%onnx::Conv_1118[FLOAT, 512x512x3x3]
%onnx::Conv_1121[FLOAT, 512x256x1x1]
%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, 512x512x3x3]
%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, 512x512x3x3]
%onnx::Conv_1163[FLOAT, 512x512x1x1]
%onnx::Conv_1166[FLOAT, 512x512x1x1]
) {
%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_1044)
%onnx::Conv_1101 = Identity(%onnx::Conv_1044)
%onnx::Conv_1098 = Identity(%onnx::Conv_1044)
%onnx::Conv_1095 = Identity(%onnx::Conv_1044)
%onnx::Conv_1092 = Identity(%onnx::Conv_1044)
%onnx::Conv_1089 = Identity(%onnx::Conv_1044)
%onnx::Conv_1086 = Identity(%onnx::Conv_1044)
%onnx::Conv_1083 = Identity(%onnx::Conv_1044)
%onnx::Conv_1080 = Identity(%onnx::Conv_1044)
%onnx::Conv_1077 = Identity(%onnx::Conv_1044)
%onnx::Conv_1074 = Identity(%onnx::Conv_1044)
%onnx::Conv_1071 = Identity(%onnx::Conv_1044)
%onnx::Conv_1068 = Identity(%onnx::Conv_1044)
%onnx::Conv_1065 = Identity(%onnx::Conv_1044)
%onnx::Conv_1062 = Identity(%onnx::Conv_1044)
%onnx::Conv_1059 = Identity(%onnx::Conv_1044)
%onnx::Conv_1056 = Identity(%onnx::Conv_1044)
%onnx::Conv_1053 = Identity(%onnx::Conv_1044)
%onnx::Conv_1050 = Identity(%onnx::Conv_1044)
%onnx::Conv_1047 = Identity(%onnx::Conv_1044)
%onnx::Conv_1041 = Identity(%onnx::Conv_978)
%onnx::Conv_1038 = Identity(%onnx::Conv_978)
%onnx::Conv_1035 = Identity(%onnx::Conv_978)
%onnx::Conv_1032 = Identity(%onnx::Conv_978)
%onnx::Conv_1029 = Identity(%onnx::Conv_978)
%onnx::Conv_1026 = Identity(%onnx::Conv_978)
%onnx::Conv_1023 = Identity(%onnx::Conv_978)
%onnx::Conv_1020 = Identity(%onnx::Conv_978)
%onnx::Conv_1017 = Identity(%onnx::Conv_978)
%onnx::Conv_1014 = Identity(%onnx::Conv_978)
%onnx::Conv_1011 = Identity(%onnx::Conv_978)
%onnx::Conv_1008 = Identity(%onnx::Conv_978)
%onnx::Conv_1005 = Identity(%onnx::Conv_978)
%onnx::Conv_1002 = Identity(%onnx::Conv_978)
%onnx::Conv_999 = Identity(%onnx::Conv_978)
%onnx::Conv_996 = Identity(%onnx::Conv_978)
%onnx::Conv_993 = Identity(%onnx::Conv_978)
%onnx::Conv_990 = Identity(%onnx::Conv_978)
%onnx::Conv_987 = Identity(%onnx::Conv_978)
%onnx::Conv_984 = Identity(%onnx::Conv_978)
%onnx::Conv_981 = Identity(%onnx::Conv_978)
%/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/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_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/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_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/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/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/Add_6_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_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.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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/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_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_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/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/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/Add_6_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_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.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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/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_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_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/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/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/Add_6_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_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.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_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/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_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/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_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/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/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/Add_6_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_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.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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/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_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_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/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/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/Add_6_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_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.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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/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_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_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/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/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/Add_6_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_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.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_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/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_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/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_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/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/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/Add_6_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_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.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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/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_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_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/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/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/Add_6_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_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.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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/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_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_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/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/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/Add_6_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_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)
%/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)
%975 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %975
}
|
val_accuracy
| 92.08734
| 6,858,221,568
| 23,131,530
|
{'zcp_epe_nas': 80.66697103156896, 'zcp_fisher': 37.74352264404297, 'zcp_flops': 109731545088.0, 'zcp_grad_norm': 120.75973510742188, 'zcp_grasp': 0.5911865234375, 'zcp_jacov': -16.06135753113601, 'zcp_l2_norm': 1423.058837890625, 'zcp_nwot': 237.08190483835915, 'zcp_params': 23131530.0, 'zcp_plain': 0.00426941178739, 'zcp_snip': 1058.0560302734375, 'zcp_synflow': 100.03533384261873, 'zcp_zen': 122.83711242675781, 'zcp_val_accuracy': 0.9075520634651181}
| |
NASBench101_367745
|
NASBench101
|
367745
|
de5b7c7de0b1bfc0d2c50af0e2cd7baf
|
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, 64x64x3x3]
%onnx::Conv_896[FLOAT, 64x64x3x3]
%onnx::Conv_899[FLOAT, 64x64x3x3]
%onnx::Conv_902[FLOAT, 64x128x1x1]
%onnx::Conv_905[FLOAT, 64x64x3x3]
%onnx::Conv_908[FLOAT, 64x128x1x1]
%onnx::Conv_911[FLOAT, 64x64x3x3]
%onnx::Conv_914[FLOAT, 64x64x3x3]
%onnx::Conv_917[FLOAT, 64x64x3x3]
%onnx::Conv_920[FLOAT, 64x128x1x1]
%onnx::Conv_923[FLOAT, 64x64x3x3]
%onnx::Conv_926[FLOAT, 64x128x1x1]
%onnx::Conv_929[FLOAT, 64x64x3x3]
%onnx::Conv_932[FLOAT, 64x64x3x3]
%onnx::Conv_935[FLOAT, 64x64x3x3]
%onnx::Conv_938[FLOAT, 64x128x1x1]
%onnx::Conv_941[FLOAT, 64x64x3x3]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x3x3]
%onnx::Conv_950[FLOAT, 128x128x3x3]
%onnx::Conv_953[FLOAT, 128x128x3x3]
%onnx::Conv_956[FLOAT, 128x128x1x1]
%onnx::Conv_959[FLOAT, 128x128x3x3]
%onnx::Conv_962[FLOAT, 128x256x1x1]
%onnx::Conv_965[FLOAT, 128x128x3x3]
%onnx::Conv_968[FLOAT, 128x128x3x3]
%onnx::Conv_971[FLOAT, 128x128x3x3]
%onnx::Conv_974[FLOAT, 128x256x1x1]
%onnx::Conv_977[FLOAT, 128x128x3x3]
%onnx::Conv_980[FLOAT, 128x256x1x1]
%onnx::Conv_983[FLOAT, 128x128x3x3]
%onnx::Conv_986[FLOAT, 128x128x3x3]
%onnx::Conv_989[FLOAT, 128x128x3x3]
%onnx::Conv_992[FLOAT, 128x256x1x1]
%onnx::Conv_995[FLOAT, 128x128x3x3]
%onnx::Conv_998[FLOAT, 256x256x1x1]
%onnx::Conv_999[FLOAT, 256]
%onnx::Conv_1001[FLOAT, 256x256x3x3]
%onnx::Conv_1004[FLOAT, 256x256x3x3]
%onnx::Conv_1007[FLOAT, 256x256x3x3]
%onnx::Conv_1010[FLOAT, 256x256x1x1]
%onnx::Conv_1013[FLOAT, 256x256x3x3]
%onnx::Conv_1016[FLOAT, 256x512x1x1]
%onnx::Conv_1019[FLOAT, 256x256x3x3]
%onnx::Conv_1022[FLOAT, 256x256x3x3]
%onnx::Conv_1025[FLOAT, 256x256x3x3]
%onnx::Conv_1028[FLOAT, 256x512x1x1]
%onnx::Conv_1031[FLOAT, 256x256x3x3]
%onnx::Conv_1034[FLOAT, 256x512x1x1]
%onnx::Conv_1037[FLOAT, 256x256x3x3]
%onnx::Conv_1040[FLOAT, 256x256x3x3]
%onnx::Conv_1043[FLOAT, 256x256x3x3]
%onnx::Conv_1046[FLOAT, 256x512x1x1]
%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/conv3x3/conv_bn_relu/conv_bn_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_893, %onnx::Conv_894)
%/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_896, %onnx::Conv_897)
%/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_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/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_902, %onnx::Conv_903)
%/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.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/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/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/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_6_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_911, %onnx::Conv_912)
%/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_914, %onnx::Conv_915)
%/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_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/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_920, %onnx::Conv_921)
%/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.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/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/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/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_6_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_929, %onnx::Conv_930)
%/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_932, %onnx::Conv_933)
%/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_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/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_938, %onnx::Conv_939)
%/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.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/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/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/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_6_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_947, %onnx::Conv_948)
%/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_950, %onnx::Conv_951)
%/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_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/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_956, %onnx::Conv_957)
%/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.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/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/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/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_6_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_965, %onnx::Conv_966)
%/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_968, %onnx::Conv_969)
%/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_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/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_974, %onnx::Conv_975)
%/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.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/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/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/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_6_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_983, %onnx::Conv_984)
%/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_986, %onnx::Conv_987)
%/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_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/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_992, %onnx::Conv_993)
%/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.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/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/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/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_6_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_1001, %onnx::Conv_1002)
%/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_1004, %onnx::Conv_1005)
%/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_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/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_1010, %onnx::Conv_1011)
%/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.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/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/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/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_6_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_1019, %onnx::Conv_1020)
%/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_1022, %onnx::Conv_1023)
%/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_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/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_1028, %onnx::Conv_1029)
%/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.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/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/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/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_6_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_1037, %onnx::Conv_1038)
%/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_1040, %onnx::Conv_1041)
%/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_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/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_1046, %onnx::Conv_1047)
%/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.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/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/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/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_6_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/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_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.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)
%885 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %885
}
|
val_accuracy
| 90.755206
| 3,010,996,224
| 10,183,050
|
{'zcp_epe_nas': 53.63444255585073, 'zcp_fisher': 3106.021240234375, 'zcp_flops': 48175939584.0, 'zcp_grad_norm': 1015.7911376953125, 'zcp_grasp': -8876.984375, 'zcp_jacov': -16.043170529318573, 'zcp_l2_norm': 993.6525268554688, 'zcp_nwot': 224.30052565437313, 'zcp_params': 10183050.0, 'zcp_plain': 0.24726670980453402, 'zcp_snip': 5906.39990234375, 'zcp_synflow': 158.99742831128046, 'zcp_zen': 116.43207550048828, 'zcp_val_accuracy': 0.931290090084075}
| |
NASBench101_220776
|
NASBench101
|
220776
|
85cb7c745b60dc88f521e12a3868d7e0
|
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, 43x128x1x1]
%onnx::Conv_801[FLOAT, 43]
%onnx::Conv_803[FLOAT, 43x43x1x1]
%onnx::Conv_806[FLOAT, 43x43x1x1]
%onnx::Conv_809[FLOAT, 42x42x1x1]
%onnx::Conv_810[FLOAT, 42]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 43x128x1x1]
%onnx::Conv_818[FLOAT, 43x43x1x1]
%onnx::Conv_821[FLOAT, 43x43x1x1]
%onnx::Conv_824[FLOAT, 42x42x1x1]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 43x128x1x1]
%onnx::Conv_833[FLOAT, 43x43x1x1]
%onnx::Conv_836[FLOAT, 43x43x1x1]
%onnx::Conv_839[FLOAT, 42x42x1x1]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 86x128x1x1]
%onnx::Conv_846[FLOAT, 86]
%onnx::Conv_848[FLOAT, 86x86x1x1]
%onnx::Conv_851[FLOAT, 85x85x1x1]
%onnx::Conv_852[FLOAT, 85]
%onnx::Conv_854[FLOAT, 85x85x1x1]
%onnx::Conv_857[FLOAT, 256x128x1x1]
%onnx::Conv_858[FLOAT, 256]
%onnx::Conv_860[FLOAT, 86x256x1x1]
%onnx::Conv_863[FLOAT, 86x86x1x1]
%onnx::Conv_866[FLOAT, 85x85x1x1]
%onnx::Conv_869[FLOAT, 85x85x1x1]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_875[FLOAT, 86x256x1x1]
%onnx::Conv_878[FLOAT, 86x86x1x1]
%onnx::Conv_881[FLOAT, 85x85x1x1]
%onnx::Conv_884[FLOAT, 85x85x1x1]
%onnx::Conv_887[FLOAT, 256x256x1x1]
%onnx::Conv_890[FLOAT, 171x256x1x1]
%onnx::Conv_891[FLOAT, 171]
%onnx::Conv_893[FLOAT, 171x171x1x1]
%onnx::Conv_896[FLOAT, 171x171x1x1]
%onnx::Conv_899[FLOAT, 170x170x1x1]
%onnx::Conv_900[FLOAT, 170]
%onnx::Conv_902[FLOAT, 512x256x1x1]
%onnx::Conv_903[FLOAT, 512]
%onnx::Conv_905[FLOAT, 171x512x1x1]
%onnx::Conv_908[FLOAT, 171x171x1x1]
%onnx::Conv_911[FLOAT, 171x171x1x1]
%onnx::Conv_914[FLOAT, 170x170x1x1]
%onnx::Conv_917[FLOAT, 512x512x1x1]
%onnx::Conv_920[FLOAT, 171x512x1x1]
%onnx::Conv_923[FLOAT, 171x171x1x1]
%onnx::Conv_926[FLOAT, 171x171x1x1]
%onnx::Conv_929[FLOAT, 170x170x1x1]
%onnx::Conv_932[FLOAT, 512x512x1x1]
) {
%onnx::Conv_933 = Identity(%onnx::Conv_903)
%onnx::Conv_930 = Identity(%onnx::Conv_900)
%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_903)
%onnx::Conv_915 = Identity(%onnx::Conv_900)
%onnx::Conv_912 = Identity(%onnx::Conv_891)
%onnx::Conv_909 = Identity(%onnx::Conv_891)
%onnx::Conv_906 = Identity(%onnx::Conv_891)
%onnx::Conv_897 = Identity(%onnx::Conv_891)
%onnx::Conv_894 = Identity(%onnx::Conv_891)
%onnx::Conv_888 = Identity(%onnx::Conv_858)
%onnx::Conv_885 = Identity(%onnx::Conv_852)
%onnx::Conv_882 = Identity(%onnx::Conv_852)
%onnx::Conv_879 = Identity(%onnx::Conv_846)
%onnx::Conv_876 = Identity(%onnx::Conv_846)
%onnx::Conv_873 = Identity(%onnx::Conv_858)
%onnx::Conv_870 = Identity(%onnx::Conv_852)
%onnx::Conv_867 = Identity(%onnx::Conv_852)
%onnx::Conv_864 = Identity(%onnx::Conv_846)
%onnx::Conv_861 = Identity(%onnx::Conv_846)
%onnx::Conv_855 = Identity(%onnx::Conv_852)
%onnx::Conv_849 = Identity(%onnx::Conv_846)
%onnx::Conv_843 = Identity(%onnx::Conv_798)
%onnx::Conv_840 = Identity(%onnx::Conv_810)
%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_798)
%onnx::Conv_825 = Identity(%onnx::Conv_810)
%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_798)
%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/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_803, %onnx::Conv_804)
%/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_806, %onnx::Conv_807)
%/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 = <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.4/conv1x1/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.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_2_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/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.4/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.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_812, %onnx::Conv_813)
%/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_3_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_3_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/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_818, %onnx::Conv_819)
%/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_821, %onnx::Conv_822)
%/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 = <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.4/conv1x1/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.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_2_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/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.4/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.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_3_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/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_3_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_3_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/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_833, %onnx::Conv_834)
%/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/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/conv1x1/conv_bn_relu/conv_bn_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_836, %onnx::Conv_837)
%/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 = <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.4/conv1x1/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.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_2_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/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.4/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.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_3_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/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_3_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_3_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/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_848, %onnx::Conv_849)
%/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_851, %onnx::Conv_852)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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.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.4/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.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_857, %onnx::Conv_858)
%/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_3_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_3_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/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_863, %onnx::Conv_864)
%/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_866, %onnx::Conv_867)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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.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.4/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.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_3_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/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_3_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_3_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/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_878, %onnx::Conv_879)
%/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/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/conv1x1/conv_bn_relu/conv_bn_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_881, %onnx::Conv_882)
%/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/conv1x1/conv_bn_relu/conv_bn_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.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.4/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.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_3_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/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_3_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_3_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/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_893, %onnx::Conv_894)
%/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_896, %onnx::Conv_897)
%/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 = <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.4/conv1x1/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.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_2_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/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.4/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.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_902, %onnx::Conv_903)
%/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_3_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_3_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/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_908, %onnx::Conv_909)
%/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_911, %onnx::Conv_912)
%/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 = <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.4/conv1x1/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.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_2_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/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.4/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.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_3_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/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_3_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_3_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/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_923, %onnx::Conv_924)
%/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/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/conv1x1/conv_bn_relu/conv_bn_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_926, %onnx::Conv_927)
%/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 = <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.4/conv1x1/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.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_2_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/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.4/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)
%/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_3_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/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_3_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_3_output_0)
%795 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %795
}
|
val_accuracy
| 89.052486
| 480,112,384
| 1,524,248
|
{'zcp_epe_nas': 135.7963396292819, 'zcp_fisher': 11.586870193481445, 'zcp_flops': 7681798144.0, 'zcp_grad_norm': 75.65713500976562, 'zcp_grasp': -15.721435546875, 'zcp_jacov': -16.054301965344578, 'zcp_l2_norm': 762.14404296875, 'zcp_nwot': 221.01316074356993, 'zcp_params': 1524248.0, 'zcp_plain': 0.030685735866427002, 'zcp_snip': 392.9276428222656, 'zcp_synflow': 91.14033355715844, 'zcp_zen': 66.57095336914062, 'zcp_val_accuracy': 0.882612168788909}
| |
NASBench101_115282
|
NASBench101
|
115282
|
4596895ad034fcd78b4e8a0ee462ae79
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_617[FLOAT, 128x3x3x3]
%onnx::Conv_618[FLOAT, 128]
%onnx::Conv_620[FLOAT, 64x128x1x1]
%onnx::Conv_621[FLOAT, 64]
%onnx::Conv_623[FLOAT, 64x64x3x3]
%onnx::Conv_626[FLOAT, 64x128x1x1]
%onnx::Conv_629[FLOAT, 64x64x1x1]
%onnx::Conv_632[FLOAT, 64x128x1x1]
%onnx::Conv_635[FLOAT, 64x64x3x3]
%onnx::Conv_638[FLOAT, 64x128x1x1]
%onnx::Conv_641[FLOAT, 64x64x1x1]
%onnx::Conv_644[FLOAT, 64x128x1x1]
%onnx::Conv_647[FLOAT, 64x64x3x3]
%onnx::Conv_650[FLOAT, 64x128x1x1]
%onnx::Conv_653[FLOAT, 64x64x1x1]
%onnx::Conv_656[FLOAT, 128x128x1x1]
%onnx::Conv_659[FLOAT, 128x128x3x3]
%onnx::Conv_662[FLOAT, 128x128x1x1]
%onnx::Conv_665[FLOAT, 128x128x1x1]
%onnx::Conv_668[FLOAT, 128x256x1x1]
%onnx::Conv_671[FLOAT, 128x128x3x3]
%onnx::Conv_674[FLOAT, 128x256x1x1]
%onnx::Conv_677[FLOAT, 128x128x1x1]
%onnx::Conv_680[FLOAT, 128x256x1x1]
%onnx::Conv_683[FLOAT, 128x128x3x3]
%onnx::Conv_686[FLOAT, 128x256x1x1]
%onnx::Conv_689[FLOAT, 128x128x1x1]
%onnx::Conv_692[FLOAT, 256x256x1x1]
%onnx::Conv_693[FLOAT, 256]
%onnx::Conv_695[FLOAT, 256x256x3x3]
%onnx::Conv_698[FLOAT, 256x256x1x1]
%onnx::Conv_701[FLOAT, 256x256x1x1]
%onnx::Conv_704[FLOAT, 256x512x1x1]
%onnx::Conv_707[FLOAT, 256x256x3x3]
%onnx::Conv_710[FLOAT, 256x512x1x1]
%onnx::Conv_713[FLOAT, 256x256x1x1]
%onnx::Conv_716[FLOAT, 256x512x1x1]
%onnx::Conv_719[FLOAT, 256x256x3x3]
%onnx::Conv_722[FLOAT, 256x512x1x1]
%onnx::Conv_725[FLOAT, 256x256x1x1]
) {
%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_618)
%onnx::Conv_687 = Identity(%onnx::Conv_618)
%onnx::Conv_684 = Identity(%onnx::Conv_618)
%onnx::Conv_681 = Identity(%onnx::Conv_618)
%onnx::Conv_678 = Identity(%onnx::Conv_618)
%onnx::Conv_675 = Identity(%onnx::Conv_618)
%onnx::Conv_672 = Identity(%onnx::Conv_618)
%onnx::Conv_669 = Identity(%onnx::Conv_618)
%onnx::Conv_666 = Identity(%onnx::Conv_618)
%onnx::Conv_663 = Identity(%onnx::Conv_618)
%onnx::Conv_660 = Identity(%onnx::Conv_618)
%onnx::Conv_657 = Identity(%onnx::Conv_618)
%onnx::Conv_654 = Identity(%onnx::Conv_621)
%onnx::Conv_651 = Identity(%onnx::Conv_621)
%onnx::Conv_648 = Identity(%onnx::Conv_621)
%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)
%/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_617, %onnx::Conv_618)
%/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_620, %onnx::Conv_621)
%/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_623, %onnx::Conv_624)
%/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_626, %onnx::Conv_627)
%/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/vertex_op.3/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.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_3_output_0, %onnx::Conv_629, %onnx::Conv_630)
%/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/maxpool/MaxPool_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_632, %onnx::Conv_633)
%/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_635, %onnx::Conv_636)
%/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_638, %onnx::Conv_639)
%/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/vertex_op.3/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.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_3_output_0, %onnx::Conv_641, %onnx::Conv_642)
%/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/maxpool/MaxPool_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_644, %onnx::Conv_645)
%/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_647, %onnx::Conv_648)
%/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_650, %onnx::Conv_651)
%/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/vertex_op.3/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.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_3_output_0, %onnx::Conv_653, %onnx::Conv_654)
%/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/maxpool/MaxPool_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_656, %onnx::Conv_657)
%/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_659, %onnx::Conv_660)
%/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_662, %onnx::Conv_663)
%/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/vertex_op.3/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.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_3_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/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/maxpool/MaxPool_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_668, %onnx::Conv_669)
%/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_671, %onnx::Conv_672)
%/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_674, %onnx::Conv_675)
%/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/vertex_op.3/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.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_3_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/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/maxpool/MaxPool_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_680, %onnx::Conv_681)
%/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_683, %onnx::Conv_684)
%/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_686, %onnx::Conv_687)
%/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/vertex_op.3/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.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_3_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/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/maxpool/MaxPool_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_692, %onnx::Conv_693)
%/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_695, %onnx::Conv_696)
%/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_698, %onnx::Conv_699)
%/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/vertex_op.3/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.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_3_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/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/maxpool/MaxPool_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_704, %onnx::Conv_705)
%/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_707, %onnx::Conv_708)
%/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_710, %onnx::Conv_711)
%/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/vertex_op.3/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.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_3_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/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/maxpool/MaxPool_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_716, %onnx::Conv_717)
%/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_719, %onnx::Conv_720)
%/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_722, %onnx::Conv_723)
%/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/vertex_op.3/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.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_3_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/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/maxpool/MaxPool_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)
%615 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %615
}
|
val_accuracy
| 91.486377
| 1,042,556,928
| 3,468,426
|
{'zcp_epe_nas': 96.7912312385615, 'zcp_fisher': 2.015370368957519, 'zcp_flops': 16680910848.0, 'zcp_grad_norm': 25.50383949279785, 'zcp_grasp': 0.022720336914062, 'zcp_jacov': -16.06071099193894, 'zcp_l2_norm': 694.5811157226562, 'zcp_nwot': 218.2607743378809, 'zcp_params': 3468426.0, 'zcp_plain': 0.0010049091652030002, 'zcp_snip': 150.56646728515625, 'zcp_synflow': 84.74289616304671, 'zcp_zen': 73.33332061767578, 'zcp_val_accuracy': 0.916566491127014}
| |
NASBench101_398675
|
NASBench101
|
398675
|
f0fddc4dc5c279ba4c527a470dc0bad4
|
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, 128x128x3x3]
%onnx::Conv_776[FLOAT, 128x128x1x1]
%onnx::Conv_779[FLOAT, 128x128x1x1]
%onnx::Conv_782[FLOAT, 128x128x3x3]
%onnx::Conv_785[FLOAT, 128x128x1x1]
%onnx::Conv_788[FLOAT, 128x128x3x3]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 128x128x1x1]
%onnx::Conv_797[FLOAT, 128x128x3x3]
%onnx::Conv_800[FLOAT, 128x128x1x1]
%onnx::Conv_803[FLOAT, 128x128x3x3]
%onnx::Conv_806[FLOAT, 128x128x1x1]
%onnx::Conv_809[FLOAT, 256x128x1x1]
%onnx::Conv_810[FLOAT, 256]
%onnx::Conv_812[FLOAT, 256x256x3x3]
%onnx::Conv_815[FLOAT, 256x128x1x1]
%onnx::Conv_818[FLOAT, 256x256x3x3]
%onnx::Conv_821[FLOAT, 256x128x1x1]
%onnx::Conv_824[FLOAT, 256x256x1x1]
%onnx::Conv_827[FLOAT, 256x256x3x3]
%onnx::Conv_830[FLOAT, 256x256x1x1]
%onnx::Conv_833[FLOAT, 256x256x3x3]
%onnx::Conv_836[FLOAT, 256x256x1x1]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x256x3x3]
%onnx::Conv_845[FLOAT, 256x256x1x1]
%onnx::Conv_848[FLOAT, 256x256x3x3]
%onnx::Conv_851[FLOAT, 256x256x1x1]
%onnx::Conv_854[FLOAT, 512x256x1x1]
%onnx::Conv_855[FLOAT, 512]
%onnx::Conv_857[FLOAT, 512x512x3x3]
%onnx::Conv_860[FLOAT, 512x256x1x1]
%onnx::Conv_863[FLOAT, 512x512x3x3]
%onnx::Conv_866[FLOAT, 512x256x1x1]
%onnx::Conv_869[FLOAT, 512x512x1x1]
%onnx::Conv_872[FLOAT, 512x512x3x3]
%onnx::Conv_875[FLOAT, 512x512x1x1]
%onnx::Conv_878[FLOAT, 512x512x3x3]
%onnx::Conv_881[FLOAT, 512x512x1x1]
%onnx::Conv_884[FLOAT, 512x512x1x1]
%onnx::Conv_887[FLOAT, 512x512x3x3]
%onnx::Conv_890[FLOAT, 512x512x1x1]
%onnx::Conv_893[FLOAT, 512x512x3x3]
%onnx::Conv_896[FLOAT, 512x512x1x1]
) {
%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/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_773, %onnx::Conv_774)
%/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_776, %onnx::Conv_777)
%/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/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/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/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/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_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.4/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.4/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/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_788, %onnx::Conv_789)
%/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/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/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/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/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/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/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_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.4/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.4/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/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_803, %onnx::Conv_804)
%/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/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/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/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/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/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/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_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.4/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/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_818, %onnx::Conv_819)
%/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_821, %onnx::Conv_822)
%/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/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/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/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/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_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.4/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.4/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/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_833, %onnx::Conv_834)
%/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/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/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/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/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/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/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_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.4/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.4/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/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_848, %onnx::Conv_849)
%/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/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/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/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/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/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/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_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.4/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/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_863, %onnx::Conv_864)
%/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_866, %onnx::Conv_867)
%/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/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/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/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/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_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.4/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.4/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/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_878, %onnx::Conv_879)
%/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/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/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/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/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/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/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_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.4/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.4/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/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_893, %onnx::Conv_894)
%/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/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/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/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/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/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/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_6_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%759 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %759
}
|
val_accuracy
| 91.40625
| 6,276,786,176
| 21,220,234
|
{'zcp_epe_nas': 108.35797030536874, 'zcp_fisher': 149.90301513671875, 'zcp_flops': 100428578816.0, 'zcp_grad_norm': 228.31138610839844, 'zcp_grasp': -124.109130859375, 'zcp_jacov': -16.055526817706394, 'zcp_l2_norm': 1015.4381713867188, 'zcp_nwot': 232.12522249392885, 'zcp_params': 21220234.0, 'zcp_plain': 0.24240611493587402, 'zcp_snip': 1981.759521484375, 'zcp_synflow': 103.82078187160673, 'zcp_zen': 108.97248077392578, 'zcp_val_accuracy': 0.9271835088729851}
| |
NASBench101_124410
|
NASBench101
|
124410
|
4b279502fa2d5624fa233336ee8d5f6d
|
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, 64x128x1x1]
%onnx::Conv_644[FLOAT, 64x64x1x1]
%onnx::Conv_647[FLOAT, 128x128x1x1]
%onnx::Conv_650[FLOAT, 64x128x1x1]
%onnx::Conv_653[FLOAT, 64x128x1x1]
%onnx::Conv_656[FLOAT, 64x64x1x1]
%onnx::Conv_659[FLOAT, 128x128x1x1]
%onnx::Conv_662[FLOAT, 64x128x1x1]
%onnx::Conv_665[FLOAT, 64x128x1x1]
%onnx::Conv_668[FLOAT, 64x64x1x1]
%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, 128x256x1x1]
%onnx::Conv_689[FLOAT, 128x256x1x1]
%onnx::Conv_692[FLOAT, 128x128x1x1]
%onnx::Conv_695[FLOAT, 256x256x1x1]
%onnx::Conv_698[FLOAT, 128x256x1x1]
%onnx::Conv_701[FLOAT, 128x256x1x1]
%onnx::Conv_704[FLOAT, 128x128x1x1]
%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, 256x512x1x1]
%onnx::Conv_725[FLOAT, 256x512x1x1]
%onnx::Conv_728[FLOAT, 256x256x1x1]
%onnx::Conv_731[FLOAT, 512x512x1x1]
%onnx::Conv_734[FLOAT, 256x512x1x1]
%onnx::Conv_737[FLOAT, 256x512x1x1]
%onnx::Conv_740[FLOAT, 256x256x1x1]
%onnx::Conv_743[FLOAT, 512x512x1x1]
) {
%onnx::Conv_744 = Identity(%onnx::Conv_720)
%onnx::Conv_741 = Identity(%onnx::Conv_684)
%onnx::Conv_738 = Identity(%onnx::Conv_684)
%onnx::Conv_735 = Identity(%onnx::Conv_684)
%onnx::Conv_732 = Identity(%onnx::Conv_720)
%onnx::Conv_729 = Identity(%onnx::Conv_684)
%onnx::Conv_726 = Identity(%onnx::Conv_684)
%onnx::Conv_723 = Identity(%onnx::Conv_684)
%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_636)
%onnx::Conv_702 = Identity(%onnx::Conv_636)
%onnx::Conv_699 = Identity(%onnx::Conv_636)
%onnx::Conv_696 = Identity(%onnx::Conv_684)
%onnx::Conv_693 = Identity(%onnx::Conv_636)
%onnx::Conv_690 = Identity(%onnx::Conv_636)
%onnx::Conv_687 = 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_636)
%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_636)
%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_636)
%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/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_641, %onnx::Conv_642)
%/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_644, %onnx::Conv_645)
%/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.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/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.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_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_3_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_3_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/input_op.3/conv_bn_relu/conv_bn_relu.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_653, %onnx::Conv_654)
%/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_656, %onnx::Conv_657)
%/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.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/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.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_3_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_3_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_3_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/input_op.3/conv_bn_relu/conv_bn_relu.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_665, %onnx::Conv_666)
%/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_668, %onnx::Conv_669)
%/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.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/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.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_3_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_3_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_3_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/input_op.3/conv_bn_relu/conv_bn_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_677, %onnx::Conv_678)
%/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_680, %onnx::Conv_681)
%/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.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/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.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_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_3_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_3_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/input_op.3/conv_bn_relu/conv_bn_relu.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_689, %onnx::Conv_690)
%/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_692, %onnx::Conv_693)
%/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.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/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.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_3_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_3_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_3_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/input_op.3/conv_bn_relu/conv_bn_relu.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_701, %onnx::Conv_702)
%/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_704, %onnx::Conv_705)
%/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.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/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.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_3_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_3_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_3_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/input_op.3/conv_bn_relu/conv_bn_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_713, %onnx::Conv_714)
%/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_716, %onnx::Conv_717)
%/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.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/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.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_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_3_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_3_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/input_op.3/conv_bn_relu/conv_bn_relu.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_725, %onnx::Conv_726)
%/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_728, %onnx::Conv_729)
%/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.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/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.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_3_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_3_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_3_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/input_op.3/conv_bn_relu/conv_bn_relu.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_737, %onnx::Conv_738)
%/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_740, %onnx::Conv_741)
%/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.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/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.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_3_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_3_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_3_output_0)
%633 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %633
}
|
val_accuracy
| 88.060898
| 634,267,648
| 2,017,034
|
{'zcp_epe_nas': 81.80486056378334, 'zcp_fisher': 4.501388072967529, 'zcp_flops': 10148282368.0, 'zcp_grad_norm': 43.883480072021484, 'zcp_grasp': -15.190841674804688, 'zcp_jacov': -16.061729193151024, 'zcp_l2_norm': 740.48583984375, 'zcp_nwot': 222.0413493678736, 'zcp_params': 2017034.0, 'zcp_plain': 0.21154835820198, 'zcp_snip': 261.14544677734375, 'zcp_synflow': 53.14013609158869, 'zcp_zen': 66.9716796875, 'zcp_val_accuracy': 0.905849337577819}
| |
NASBench101_393567
|
NASBench101
|
393567
|
edeb18422fa5b6335ad7e5c836ae95ef
|
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, 128x128x3x3]
%onnx::Conv_872[FLOAT, 128x128x3x3]
%onnx::Conv_875[FLOAT, 128x128x1x1]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 128x128x1x1]
%onnx::Conv_884[FLOAT, 128x128x1x1]
%onnx::Conv_887[FLOAT, 128x128x3x3]
%onnx::Conv_890[FLOAT, 128x128x3x3]
%onnx::Conv_893[FLOAT, 128x128x1x1]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%onnx::Conv_899[FLOAT, 128x128x1x1]
%onnx::Conv_902[FLOAT, 128x128x1x1]
%onnx::Conv_905[FLOAT, 128x128x3x3]
%onnx::Conv_908[FLOAT, 128x128x3x3]
%onnx::Conv_911[FLOAT, 128x128x1x1]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 256x128x1x1]
%onnx::Conv_918[FLOAT, 256]
%onnx::Conv_920[FLOAT, 256x128x1x1]
%onnx::Conv_923[FLOAT, 256x256x3x3]
%onnx::Conv_926[FLOAT, 256x256x3x3]
%onnx::Conv_929[FLOAT, 256x256x1x1]
%onnx::Conv_932[FLOAT, 256x128x1x1]
%onnx::Conv_935[FLOAT, 256x256x1x1]
%onnx::Conv_938[FLOAT, 256x256x1x1]
%onnx::Conv_941[FLOAT, 256x256x3x3]
%onnx::Conv_944[FLOAT, 256x256x3x3]
%onnx::Conv_947[FLOAT, 256x256x1x1]
%onnx::Conv_950[FLOAT, 256x256x1x1]
%onnx::Conv_953[FLOAT, 256x256x1x1]
%onnx::Conv_956[FLOAT, 256x256x1x1]
%onnx::Conv_959[FLOAT, 256x256x3x3]
%onnx::Conv_962[FLOAT, 256x256x3x3]
%onnx::Conv_965[FLOAT, 256x256x1x1]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 512x256x1x1]
%onnx::Conv_972[FLOAT, 512]
%onnx::Conv_974[FLOAT, 512x256x1x1]
%onnx::Conv_977[FLOAT, 512x512x3x3]
%onnx::Conv_980[FLOAT, 512x512x3x3]
%onnx::Conv_983[FLOAT, 512x512x1x1]
%onnx::Conv_986[FLOAT, 512x256x1x1]
%onnx::Conv_989[FLOAT, 512x512x1x1]
%onnx::Conv_992[FLOAT, 512x512x1x1]
%onnx::Conv_995[FLOAT, 512x512x3x3]
%onnx::Conv_998[FLOAT, 512x512x3x3]
%onnx::Conv_1001[FLOAT, 512x512x1x1]
%onnx::Conv_1004[FLOAT, 512x512x1x1]
%onnx::Conv_1007[FLOAT, 512x512x1x1]
%onnx::Conv_1010[FLOAT, 512x512x1x1]
%onnx::Conv_1013[FLOAT, 512x512x3x3]
%onnx::Conv_1016[FLOAT, 512x512x3x3]
%onnx::Conv_1019[FLOAT, 512x512x1x1]
%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/input_op.2/conv_bn_relu/conv_bn_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_866, %onnx::Conv_867)
%/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_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/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/conv3x3/conv_bn_relu/conv_bn_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_872, %onnx::Conv_873)
%/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.3/conv3x3/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_3_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/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_878, %onnx::Conv_879)
%/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.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/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/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_884, %onnx::Conv_885)
%/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_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/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/conv3x3/conv_bn_relu/conv_bn_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_890, %onnx::Conv_891)
%/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.3/conv3x3/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_3_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/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_896, %onnx::Conv_897)
%/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.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/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/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_902, %onnx::Conv_903)
%/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_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/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/conv3x3/conv_bn_relu/conv_bn_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_908, %onnx::Conv_909)
%/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.3/conv3x3/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_3_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/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_914, %onnx::Conv_915)
%/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.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/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/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.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_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/input_op.2/conv_bn_relu/conv_bn_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_920, %onnx::Conv_921)
%/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_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/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/conv3x3/conv_bn_relu/conv_bn_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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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/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_932, %onnx::Conv_933)
%/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.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/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/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_938, %onnx::Conv_939)
%/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_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/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/conv3x3/conv_bn_relu/conv_bn_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_944, %onnx::Conv_945)
%/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.3/conv3x3/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_3_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/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_950, %onnx::Conv_951)
%/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.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/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/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_956, %onnx::Conv_957)
%/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_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/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/conv3x3/conv_bn_relu/conv_bn_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_962, %onnx::Conv_963)
%/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.3/conv3x3/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_3_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/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_968, %onnx::Conv_969)
%/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.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/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/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.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_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/input_op.2/conv_bn_relu/conv_bn_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_974, %onnx::Conv_975)
%/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_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/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/conv3x3/conv_bn_relu/conv_bn_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_980, %onnx::Conv_981)
%/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.3/conv3x3/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_3_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/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_986, %onnx::Conv_987)
%/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.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/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/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_992, %onnx::Conv_993)
%/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_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/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/conv3x3/conv_bn_relu/conv_bn_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_998, %onnx::Conv_999)
%/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.3/conv3x3/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_3_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/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_1004, %onnx::Conv_1005)
%/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.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/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/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_1010, %onnx::Conv_1011)
%/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_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/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/conv3x3/conv_bn_relu/conv_bn_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_1016, %onnx::Conv_1017)
%/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.3/conv3x3/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_3_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/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_1022, %onnx::Conv_1023)
%/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.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/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/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)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%858 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %858
}
|
val_accuracy
| 91.336137
| 6,584,281,088
| 22,257,802
|
{'zcp_epe_nas': 112.70341766469899, 'zcp_fisher': 80.57763671875, 'zcp_flops': 105348497408.0, 'zcp_grad_norm': 193.398681640625, 'zcp_grasp': 15.10791015625, 'zcp_jacov': -16.05827771055025, 'zcp_l2_norm': 1225.5762939453125, 'zcp_nwot': 234.67060886065437, 'zcp_params': 22257802.0, 'zcp_plain': -0.073862969875335, 'zcp_snip': 1672.6806640625, 'zcp_synflow': 129.81474233305778, 'zcp_zen': 123.60662078857422, 'zcp_val_accuracy': 0.877804458141326}
| |
NASBench101_110986
|
NASBench101
|
110986
|
43040efc2751cc5090cbeb076c86979a
|
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, 64x64x3x3]
%onnx::Conv_998[FLOAT, 64x128x1x1]
%onnx::Conv_1001[FLOAT, 64x64x1x1]
%onnx::Conv_1004[FLOAT, 64x128x1x1]
%onnx::Conv_1007[FLOAT, 64x64x1x1]
%onnx::Conv_1010[FLOAT, 64x128x1x1]
%onnx::Conv_1013[FLOAT, 64x64x3x3]
%onnx::Conv_1016[FLOAT, 64x64x3x3]
%onnx::Conv_1019[FLOAT, 64x128x1x1]
%onnx::Conv_1022[FLOAT, 64x64x1x1]
%onnx::Conv_1025[FLOAT, 64x128x1x1]
%onnx::Conv_1028[FLOAT, 64x64x1x1]
%onnx::Conv_1031[FLOAT, 64x128x1x1]
%onnx::Conv_1034[FLOAT, 64x64x3x3]
%onnx::Conv_1037[FLOAT, 64x64x3x3]
%onnx::Conv_1040[FLOAT, 64x128x1x1]
%onnx::Conv_1043[FLOAT, 64x64x1x1]
%onnx::Conv_1046[FLOAT, 64x128x1x1]
%onnx::Conv_1049[FLOAT, 64x64x1x1]
%onnx::Conv_1052[FLOAT, 128x128x1x1]
%onnx::Conv_1055[FLOAT, 128x128x3x3]
%onnx::Conv_1058[FLOAT, 128x128x3x3]
%onnx::Conv_1061[FLOAT, 128x128x1x1]
%onnx::Conv_1064[FLOAT, 128x128x1x1]
%onnx::Conv_1067[FLOAT, 128x128x1x1]
%onnx::Conv_1070[FLOAT, 128x128x1x1]
%onnx::Conv_1073[FLOAT, 128x256x1x1]
%onnx::Conv_1076[FLOAT, 128x128x3x3]
%onnx::Conv_1079[FLOAT, 128x128x3x3]
%onnx::Conv_1082[FLOAT, 128x256x1x1]
%onnx::Conv_1085[FLOAT, 128x128x1x1]
%onnx::Conv_1088[FLOAT, 128x256x1x1]
%onnx::Conv_1091[FLOAT, 128x128x1x1]
%onnx::Conv_1094[FLOAT, 128x256x1x1]
%onnx::Conv_1097[FLOAT, 128x128x3x3]
%onnx::Conv_1100[FLOAT, 128x128x3x3]
%onnx::Conv_1103[FLOAT, 128x256x1x1]
%onnx::Conv_1106[FLOAT, 128x128x1x1]
%onnx::Conv_1109[FLOAT, 128x256x1x1]
%onnx::Conv_1112[FLOAT, 128x128x1x1]
%onnx::Conv_1115[FLOAT, 256x256x1x1]
%onnx::Conv_1116[FLOAT, 256]
%onnx::Conv_1118[FLOAT, 256x256x3x3]
%onnx::Conv_1121[FLOAT, 256x256x3x3]
%onnx::Conv_1124[FLOAT, 256x256x1x1]
%onnx::Conv_1127[FLOAT, 256x256x1x1]
%onnx::Conv_1130[FLOAT, 256x256x1x1]
%onnx::Conv_1133[FLOAT, 256x256x1x1]
%onnx::Conv_1136[FLOAT, 256x512x1x1]
%onnx::Conv_1139[FLOAT, 256x256x3x3]
%onnx::Conv_1142[FLOAT, 256x256x3x3]
%onnx::Conv_1145[FLOAT, 256x512x1x1]
%onnx::Conv_1148[FLOAT, 256x256x1x1]
%onnx::Conv_1151[FLOAT, 256x512x1x1]
%onnx::Conv_1154[FLOAT, 256x256x1x1]
%onnx::Conv_1157[FLOAT, 256x512x1x1]
%onnx::Conv_1160[FLOAT, 256x256x3x3]
%onnx::Conv_1163[FLOAT, 256x256x3x3]
%onnx::Conv_1166[FLOAT, 256x512x1x1]
%onnx::Conv_1169[FLOAT, 256x256x1x1]
%onnx::Conv_1172[FLOAT, 256x512x1x1]
%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/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_995, %onnx::Conv_996)
%/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_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/input_op.4/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_3_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_4_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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/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_1016, %onnx::Conv_1017)
%/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_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/input_op.4/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_3_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/Concat_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_4_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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/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_1037, %onnx::Conv_1038)
%/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_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/input_op.4/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_3_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/Concat_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_4_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_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/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/conv1x1/conv_bn_relu/conv_bn_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.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_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/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_1058, %onnx::Conv_1059)
%/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_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/input_op.4/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_3_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_4_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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/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_1079, %onnx::Conv_1080)
%/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_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/input_op.4/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_3_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/Concat_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_4_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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/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_1100, %onnx::Conv_1101)
%/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_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/input_op.4/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_3_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/Concat_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_4_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_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/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/conv1x1/conv_bn_relu/conv_bn_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.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_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/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_1121, %onnx::Conv_1122)
%/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_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/input_op.4/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_3_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_4_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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/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_1142, %onnx::Conv_1143)
%/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_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/input_op.4/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_3_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/Concat_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_4_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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/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_1163, %onnx::Conv_1164)
%/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_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/input_op.4/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_3_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/Concat_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_4_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_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/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/conv1x1/conv_bn_relu/conv_bn_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.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)
%984 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %984
}
|
val_accuracy
| 92.157453
| 1,940,006,912
| 6,491,146
|
{'zcp_epe_nas': 100.52998571001727, 'zcp_fisher': 155.1638641357422, 'zcp_flops': 31040110592.0, 'zcp_grad_norm': 245.4639129638672, 'zcp_grasp': -12.376953125, 'zcp_jacov': -16.05707923231678, 'zcp_l2_norm': 1190.7498779296875, 'zcp_nwot': 226.85904473740106, 'zcp_params': 6491146.0, 'zcp_plain': 0.046028438955545, 'zcp_snip': 1402.4444580078125, 'zcp_synflow': 117.23519144509831, 'zcp_zen': 110.54884338378906, 'zcp_val_accuracy': 0.9210737347602841}
| |
NASBench101_355479
|
NASBench101
|
355479
|
d6e059e1a4edb22cea631d4f4a10ae44
|
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, 64x128x1x1]
%onnx::Conv_881[FLOAT, 64x64x1x1]
%onnx::Conv_884[FLOAT, 64x64x3x3]
%onnx::Conv_887[FLOAT, 64x64x3x3]
%onnx::Conv_890[FLOAT, 64x128x1x1]
%onnx::Conv_893[FLOAT, 64x64x3x3]
%onnx::Conv_896[FLOAT, 64x128x1x1]
%onnx::Conv_899[FLOAT, 64x64x1x1]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x64x3x3]
%onnx::Conv_908[FLOAT, 64x128x1x1]
%onnx::Conv_911[FLOAT, 64x64x3x3]
%onnx::Conv_914[FLOAT, 64x128x1x1]
%onnx::Conv_917[FLOAT, 64x64x1x1]
%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, 128x128x1x1]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 128x128x3x3]
%onnx::Conv_944[FLOAT, 128x256x1x1]
%onnx::Conv_947[FLOAT, 128x128x3x3]
%onnx::Conv_950[FLOAT, 128x256x1x1]
%onnx::Conv_953[FLOAT, 128x128x1x1]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x128x3x3]
%onnx::Conv_962[FLOAT, 128x256x1x1]
%onnx::Conv_965[FLOAT, 128x128x3x3]
%onnx::Conv_968[FLOAT, 128x256x1x1]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%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, 256x256x1x1]
%onnx::Conv_992[FLOAT, 256x256x3x3]
%onnx::Conv_995[FLOAT, 256x256x3x3]
%onnx::Conv_998[FLOAT, 256x512x1x1]
%onnx::Conv_1001[FLOAT, 256x256x3x3]
%onnx::Conv_1004[FLOAT, 256x512x1x1]
%onnx::Conv_1007[FLOAT, 256x256x1x1]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x256x3x3]
%onnx::Conv_1016[FLOAT, 256x512x1x1]
%onnx::Conv_1019[FLOAT, 256x256x3x3]
%onnx::Conv_1022[FLOAT, 256x512x1x1]
%onnx::Conv_1025[FLOAT, 256x256x1x1]
%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/input_op.2/conv_bn_relu/conv_bn_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/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_881, %onnx::Conv_882)
%/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/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_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_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_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.2/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_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/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/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_899, %onnx::Conv_900)
%/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/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_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_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_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.2/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_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/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/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_917, %onnx::Conv_918)
%/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/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_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_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_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.2/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_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/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_935, %onnx::Conv_936)
%/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/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/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_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_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_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.2/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_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/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/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_953, %onnx::Conv_954)
%/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/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/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_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_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_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.2/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_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/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/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_971, %onnx::Conv_972)
%/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/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/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_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_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_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.2/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_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/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_989, %onnx::Conv_990)
%/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/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_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_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_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.2/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_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/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/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_1007, %onnx::Conv_1008)
%/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/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_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_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_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.2/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_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/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/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_1025, %onnx::Conv_1026)
%/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/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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_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_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_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.2/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)
%867 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %867
}
|
val_accuracy
| 92.898637
| 2,407,016,448
| 8,118,666
|
{'zcp_epe_nas': 159.0930125445446, 'zcp_fisher': 192.1544189453125, 'zcp_flops': 38512263168.0, 'zcp_grad_norm': 230.05015563964844, 'zcp_grasp': -345.91015625, 'zcp_jacov': -16.05456536222379, 'zcp_l2_norm': 994.157958984375, 'zcp_nwot': 224.07375320342513, 'zcp_params': 8118666.0, 'zcp_plain': -0.024299168959259, 'zcp_snip': 1343.0550537109375, 'zcp_synflow': 150.78714898288823, 'zcp_zen': 108.47611999511719, 'zcp_val_accuracy': 0.908753991127014}
| |
NASBench101_243212
|
NASBench101
|
243212
|
9336dfa1bb5c3f40ff6e2308b4629785
|
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, 128x128x3x3]
%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, 128x128x3x3]
%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, 128x128x3x3]
%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, 256x128x1x1]
%onnx::Conv_1043[FLOAT, 256x256x3x3]
%onnx::Conv_1046[FLOAT, 256x256x3x3]
%onnx::Conv_1049[FLOAT, 256x128x1x1]
%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, 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, 256x256x3x3]
%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, 512x256x1x1]
%onnx::Conv_1106[FLOAT, 512x512x3x3]
%onnx::Conv_1109[FLOAT, 512x512x3x3]
%onnx::Conv_1112[FLOAT, 512x256x1x1]
%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, 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, 512x512x3x3]
%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/input_op.2/conv_bn_relu/conv_bn_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/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/conv3x3/conv_bn_relu/conv_bn_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_980, %onnx::Conv_981)
%/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/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/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_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/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_986, %onnx::Conv_987)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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/conv3x3/conv_bn_relu/conv_bn_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_1001, %onnx::Conv_1002)
%/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/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/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_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/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_1007, %onnx::Conv_1008)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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/conv3x3/conv_bn_relu/conv_bn_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_1022, %onnx::Conv_1023)
%/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/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/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_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/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_1028, %onnx::Conv_1029)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_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/input_op.2/conv_bn_relu/conv_bn_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/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/conv3x3/conv_bn_relu/conv_bn_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_1043, %onnx::Conv_1044)
%/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/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/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_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/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_1049, %onnx::Conv_1050)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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/conv3x3/conv_bn_relu/conv_bn_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_1064, %onnx::Conv_1065)
%/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/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/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_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/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_1070, %onnx::Conv_1071)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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/conv3x3/conv_bn_relu/conv_bn_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_1085, %onnx::Conv_1086)
%/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/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/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_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/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_1091, %onnx::Conv_1092)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_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/input_op.2/conv_bn_relu/conv_bn_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/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/conv3x3/conv_bn_relu/conv_bn_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_1106, %onnx::Conv_1107)
%/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/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/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_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/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_1112, %onnx::Conv_1113)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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/conv3x3/conv_bn_relu/conv_bn_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_1127, %onnx::Conv_1128)
%/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/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/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_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/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_1133, %onnx::Conv_1134)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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/conv3x3/conv_bn_relu/conv_bn_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_1148, %onnx::Conv_1149)
%/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/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/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_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/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_1154, %onnx::Conv_1155)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_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
| 93.870193
| 6,891,776,000
| 23,295,370
|
{'zcp_epe_nas': 111.05891310055082, 'zcp_fisher': 52.794185638427734, 'zcp_flops': 110268416000.0, 'zcp_grad_norm': 134.86199951171875, 'zcp_grasp': -5.56982421875, 'zcp_jacov': -16.067385007395913, 'zcp_l2_norm': 1438.3179931640625, 'zcp_nwot': 237.49831980411332, 'zcp_params': 23295370.0, 'zcp_plain': -0.009306873194873, 'zcp_snip': 1061.9488525390625, 'zcp_synflow': 156.34958733749875, 'zcp_zen': 126.44164276123047, 'zcp_val_accuracy': 0.9169671535491941}
| |
NASBench101_332629
|
NASBench101
|
332629
|
c93195659d7c54921f0917c7b9a34697
|
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, 128x128x1x1]
%onnx::Conv_749[FLOAT, 128x128x3x3]
%onnx::Conv_752[FLOAT, 128x128x1x1]
%onnx::Conv_755[FLOAT, 128x128x1x1]
%onnx::Conv_758[FLOAT, 128x128x3x3]
%onnx::Conv_761[FLOAT, 128x128x1x1]
%onnx::Conv_764[FLOAT, 128x128x3x3]
%onnx::Conv_767[FLOAT, 128x128x1x1]
%onnx::Conv_770[FLOAT, 128x128x1x1]
%onnx::Conv_773[FLOAT, 128x128x3x3]
%onnx::Conv_776[FLOAT, 128x128x1x1]
%onnx::Conv_779[FLOAT, 128x128x3x3]
%onnx::Conv_782[FLOAT, 128x128x1x1]
%onnx::Conv_785[FLOAT, 128x128x1x1]
%onnx::Conv_788[FLOAT, 128x128x3x3]
%onnx::Conv_791[FLOAT, 256x128x1x1]
%onnx::Conv_792[FLOAT, 256]
%onnx::Conv_794[FLOAT, 256x256x3x3]
%onnx::Conv_797[FLOAT, 256x128x1x1]
%onnx::Conv_800[FLOAT, 256x128x1x1]
%onnx::Conv_803[FLOAT, 256x256x3x3]
%onnx::Conv_806[FLOAT, 256x256x1x1]
%onnx::Conv_809[FLOAT, 256x256x3x3]
%onnx::Conv_812[FLOAT, 256x256x1x1]
%onnx::Conv_815[FLOAT, 256x256x1x1]
%onnx::Conv_818[FLOAT, 256x256x3x3]
%onnx::Conv_821[FLOAT, 256x256x1x1]
%onnx::Conv_824[FLOAT, 256x256x3x3]
%onnx::Conv_827[FLOAT, 256x256x1x1]
%onnx::Conv_830[FLOAT, 256x256x1x1]
%onnx::Conv_833[FLOAT, 256x256x3x3]
%onnx::Conv_836[FLOAT, 512x256x1x1]
%onnx::Conv_837[FLOAT, 512]
%onnx::Conv_839[FLOAT, 512x512x3x3]
%onnx::Conv_842[FLOAT, 512x256x1x1]
%onnx::Conv_845[FLOAT, 512x256x1x1]
%onnx::Conv_848[FLOAT, 512x512x3x3]
%onnx::Conv_851[FLOAT, 512x512x1x1]
%onnx::Conv_854[FLOAT, 512x512x3x3]
%onnx::Conv_857[FLOAT, 512x512x1x1]
%onnx::Conv_860[FLOAT, 512x512x1x1]
%onnx::Conv_863[FLOAT, 512x512x3x3]
%onnx::Conv_866[FLOAT, 512x512x1x1]
%onnx::Conv_869[FLOAT, 512x512x3x3]
%onnx::Conv_872[FLOAT, 512x512x1x1]
%onnx::Conv_875[FLOAT, 512x512x1x1]
%onnx::Conv_878[FLOAT, 512x512x3x3]
) {
%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_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)
%onnx::Conv_789 = Identity(%onnx::Conv_744)
%onnx::Conv_786 = Identity(%onnx::Conv_744)
%onnx::Conv_783 = Identity(%onnx::Conv_744)
%onnx::Conv_780 = Identity(%onnx::Conv_744)
%onnx::Conv_777 = Identity(%onnx::Conv_744)
%onnx::Conv_774 = Identity(%onnx::Conv_744)
%onnx::Conv_771 = Identity(%onnx::Conv_744)
%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)
%/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/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/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/Constant_2_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_2_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_758, %onnx::Conv_759)
%/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_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_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_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/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.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_2_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_2_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_773, %onnx::Conv_774)
%/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_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_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_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/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.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_2_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_2_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_788, %onnx::Conv_789)
%/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_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/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/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/Constant_2_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_2_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_803, %onnx::Conv_804)
%/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_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_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_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/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.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_2_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_2_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_818, %onnx::Conv_819)
%/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_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_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_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/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.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_2_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_2_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_833, %onnx::Conv_834)
%/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_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/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/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/Constant_2_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_2_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_848, %onnx::Conv_849)
%/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_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_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_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/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.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_2_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_2_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_863, %onnx::Conv_864)
%/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_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_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_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/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.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_2_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_2_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_878, %onnx::Conv_879)
%/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)
%741 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %741
}
|
val_accuracy
| 92.628205
| 6,276,786,176
| 21,220,234
|
{'zcp_epe_nas': 78.69061562777797, 'zcp_fisher': 18.2948055267334, 'zcp_flops': 100428578816.0, 'zcp_grad_norm': 59.352046966552734, 'zcp_grasp': -0.066986083984375, 'zcp_jacov': -16.05798905896245, 'zcp_l2_norm': 1014.6238403320312, 'zcp_nwot': 231.524697425699, 'zcp_params': 21220234.0, 'zcp_plain': 0.004880242515355001, 'zcp_snip': 583.785888671875, 'zcp_synflow': 109.65122547153213, 'zcp_zen': 100.40250396728516, 'zcp_val_accuracy': 0.9278846383094781}
| |
NASBench101_248192
|
NASBench101
|
248192
|
96432b667ff6b36f2e98f6d790c58b76
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_884[FLOAT, 128x3x3x3]
%onnx::Conv_885[FLOAT, 128]
%onnx::Conv_887[FLOAT, 43x128x1x1]
%onnx::Conv_888[FLOAT, 43]
%onnx::Conv_890[FLOAT, 43x43x1x1]
%onnx::Conv_893[FLOAT, 43x43x1x1]
%onnx::Conv_896[FLOAT, 42x42x3x3]
%onnx::Conv_897[FLOAT, 42]
%onnx::Conv_899[FLOAT, 42x42x3x3]
%onnx::Conv_902[FLOAT, 43x128x1x1]
%onnx::Conv_905[FLOAT, 43x43x1x1]
%onnx::Conv_908[FLOAT, 43x43x1x1]
%onnx::Conv_911[FLOAT, 42x42x3x3]
%onnx::Conv_914[FLOAT, 42x42x3x3]
%onnx::Conv_917[FLOAT, 43x128x1x1]
%onnx::Conv_920[FLOAT, 43x43x1x1]
%onnx::Conv_923[FLOAT, 43x43x1x1]
%onnx::Conv_926[FLOAT, 42x42x3x3]
%onnx::Conv_929[FLOAT, 42x42x3x3]
%onnx::Conv_932[FLOAT, 86x128x1x1]
%onnx::Conv_933[FLOAT, 86]
%onnx::Conv_935[FLOAT, 86x86x1x1]
%onnx::Conv_938[FLOAT, 86x86x1x1]
%onnx::Conv_941[FLOAT, 85x85x3x3]
%onnx::Conv_942[FLOAT, 85]
%onnx::Conv_944[FLOAT, 85x85x3x3]
%onnx::Conv_947[FLOAT, 86x256x1x1]
%onnx::Conv_950[FLOAT, 86x86x1x1]
%onnx::Conv_953[FLOAT, 86x86x1x1]
%onnx::Conv_956[FLOAT, 85x85x3x3]
%onnx::Conv_959[FLOAT, 85x85x3x3]
%onnx::Conv_962[FLOAT, 86x256x1x1]
%onnx::Conv_965[FLOAT, 86x86x1x1]
%onnx::Conv_968[FLOAT, 86x86x1x1]
%onnx::Conv_971[FLOAT, 85x85x3x3]
%onnx::Conv_974[FLOAT, 85x85x3x3]
%onnx::Conv_977[FLOAT, 171x256x1x1]
%onnx::Conv_978[FLOAT, 171]
%onnx::Conv_980[FLOAT, 171x171x1x1]
%onnx::Conv_983[FLOAT, 171x171x1x1]
%onnx::Conv_986[FLOAT, 170x170x3x3]
%onnx::Conv_987[FLOAT, 170]
%onnx::Conv_989[FLOAT, 170x170x3x3]
%onnx::Conv_992[FLOAT, 171x512x1x1]
%onnx::Conv_995[FLOAT, 171x171x1x1]
%onnx::Conv_998[FLOAT, 171x171x1x1]
%onnx::Conv_1001[FLOAT, 170x170x3x3]
%onnx::Conv_1004[FLOAT, 170x170x3x3]
%onnx::Conv_1007[FLOAT, 171x512x1x1]
%onnx::Conv_1010[FLOAT, 171x171x1x1]
%onnx::Conv_1013[FLOAT, 171x171x1x1]
%onnx::Conv_1016[FLOAT, 170x170x3x3]
%onnx::Conv_1019[FLOAT, 170x170x3x3]
) {
%onnx::Conv_1020 = Identity(%onnx::Conv_987)
%onnx::Conv_1017 = Identity(%onnx::Conv_987)
%onnx::Conv_1014 = Identity(%onnx::Conv_978)
%onnx::Conv_1011 = Identity(%onnx::Conv_978)
%onnx::Conv_1008 = Identity(%onnx::Conv_978)
%onnx::Conv_1005 = Identity(%onnx::Conv_987)
%onnx::Conv_1002 = Identity(%onnx::Conv_987)
%onnx::Conv_999 = Identity(%onnx::Conv_978)
%onnx::Conv_996 = Identity(%onnx::Conv_978)
%onnx::Conv_993 = Identity(%onnx::Conv_978)
%onnx::Conv_990 = Identity(%onnx::Conv_987)
%onnx::Conv_984 = Identity(%onnx::Conv_978)
%onnx::Conv_981 = Identity(%onnx::Conv_978)
%onnx::Conv_975 = Identity(%onnx::Conv_942)
%onnx::Conv_972 = Identity(%onnx::Conv_942)
%onnx::Conv_969 = Identity(%onnx::Conv_933)
%onnx::Conv_966 = Identity(%onnx::Conv_933)
%onnx::Conv_963 = Identity(%onnx::Conv_933)
%onnx::Conv_960 = Identity(%onnx::Conv_942)
%onnx::Conv_957 = Identity(%onnx::Conv_942)
%onnx::Conv_954 = Identity(%onnx::Conv_933)
%onnx::Conv_951 = Identity(%onnx::Conv_933)
%onnx::Conv_948 = Identity(%onnx::Conv_933)
%onnx::Conv_945 = Identity(%onnx::Conv_942)
%onnx::Conv_939 = Identity(%onnx::Conv_933)
%onnx::Conv_936 = Identity(%onnx::Conv_933)
%onnx::Conv_930 = Identity(%onnx::Conv_897)
%onnx::Conv_927 = Identity(%onnx::Conv_897)
%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_897)
%onnx::Conv_912 = Identity(%onnx::Conv_897)
%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_897)
%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_884, %onnx::Conv_885)
%/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_887, %onnx::Conv_888)
%/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_890, %onnx::Conv_891)
%/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_893, %onnx::Conv_894)
%/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 = <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/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_896, %onnx::Conv_897)
%/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.2/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/conv3x3/conv_bn_relu/conv_bn_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_899, %onnx::Conv_900)
%/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.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_902, %onnx::Conv_903)
%/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_905, %onnx::Conv_906)
%/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_908, %onnx::Conv_909)
%/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 = <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/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_911, %onnx::Conv_912)
%/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.2/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/conv3x3/conv_bn_relu/conv_bn_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.2/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/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/conv1x1/conv_bn_relu/conv_bn_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/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 = <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/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_926, %onnx::Conv_927)
%/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.2/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/conv3x3/conv_bn_relu/conv_bn_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_929, %onnx::Conv_930)
%/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.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_932, %onnx::Conv_933)
%/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_935, %onnx::Conv_936)
%/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_938, %onnx::Conv_939)
%/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/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/conv1x1/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/conv3x3/conv_bn_relu/conv_bn_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_941, %onnx::Conv_942)
%/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 = <Tensor>]()
%/layers.5/Constant_13_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_14_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_15_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_2_output_0 = Slice(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_13_output_0, %/layers.5/Constant_14_output_0, %/layers.5/Constant_12_output_0, %/layers.5/Constant_15_output_0)
%/layers.5/Constant_16_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/Slice_2_output_0, %/layers.5/Constant_16_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_944, %onnx::Conv_945)
%/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.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_947, %onnx::Conv_948)
%/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_950, %onnx::Conv_951)
%/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_953, %onnx::Conv_954)
%/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/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/conv1x1/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/conv3x3/conv_bn_relu/conv_bn_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_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/Constant_15_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_2_output_0 = Slice(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_13_output_0, %/layers.6/Constant_14_output_0, %/layers.6/Constant_12_output_0, %/layers.6/Constant_15_output_0)
%/layers.6/Constant_16_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/Slice_2_output_0, %/layers.6/Constant_16_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.2/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/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/conv1x1/conv_bn_relu/conv_bn_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/conv1x1/conv_bn_relu/conv_bn_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 = <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/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/conv1x1/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/conv3x3/conv_bn_relu/conv_bn_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_971, %onnx::Conv_972)
%/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 = <Tensor>]()
%/layers.7/Constant_13_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_14_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_15_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_2_output_0 = Slice(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_13_output_0, %/layers.7/Constant_14_output_0, %/layers.7/Constant_12_output_0, %/layers.7/Constant_15_output_0)
%/layers.7/Constant_16_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/Slice_2_output_0, %/layers.7/Constant_16_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_974, %onnx::Conv_975)
%/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.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_977, %onnx::Conv_978)
%/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_980, %onnx::Conv_981)
%/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_983, %onnx::Conv_984)
%/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 = <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/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_986, %onnx::Conv_987)
%/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.2/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/conv3x3/conv_bn_relu/conv_bn_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_989, %onnx::Conv_990)
%/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.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_992, %onnx::Conv_993)
%/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_995, %onnx::Conv_996)
%/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_998, %onnx::Conv_999)
%/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 = <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/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_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/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.2/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/conv3x3/conv_bn_relu/conv_bn_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.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/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_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/conv1x1/conv_bn_relu/conv_bn_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_1013, %onnx::Conv_1014)
%/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 = <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/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_1016, %onnx::Conv_1017)
%/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.2/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/conv3x3/conv_bn_relu/conv_bn_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_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/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/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)
%882 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %882
}
|
val_accuracy
| 89.89383
| 769,820,928
| 2,585,160
|
{'zcp_epe_nas': 88.22954478828694, 'zcp_fisher': 83.04293060302734, 'zcp_flops': 12317134848.0, 'zcp_grad_norm': 191.7967071533203, 'zcp_grasp': 69.90625, 'zcp_jacov': -16.04388021971949, 'zcp_l2_norm': 688.4580078125, 'zcp_nwot': 215.9671718615665, 'zcp_params': 2585160.0, 'zcp_plain': -0.004092516377568, 'zcp_snip': 835.21630859375, 'zcp_synflow': 111.86100647228508, 'zcp_zen': 75.98910522460938, 'zcp_val_accuracy': 0.880508840084075}
| |
NASBench101_346379
|
NASBench101
|
346379
|
d164844aebcbc607a4297d201f834a90
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_662[FLOAT, 128x3x3x3]
%onnx::Conv_663[FLOAT, 128]
%onnx::Conv_665[FLOAT, 128x128x1x1]
%onnx::Conv_668[FLOAT, 128x128x3x3]
%onnx::Conv_671[FLOAT, 128x128x3x3]
%onnx::Conv_674[FLOAT, 128x128x3x3]
%onnx::Conv_677[FLOAT, 128x128x1x1]
%onnx::Conv_680[FLOAT, 128x128x3x3]
%onnx::Conv_683[FLOAT, 128x128x3x3]
%onnx::Conv_686[FLOAT, 128x128x3x3]
%onnx::Conv_689[FLOAT, 128x128x1x1]
%onnx::Conv_692[FLOAT, 128x128x3x3]
%onnx::Conv_695[FLOAT, 128x128x3x3]
%onnx::Conv_698[FLOAT, 128x128x3x3]
%onnx::Conv_701[FLOAT, 256x128x1x1]
%onnx::Conv_702[FLOAT, 256]
%onnx::Conv_704[FLOAT, 256x256x3x3]
%onnx::Conv_707[FLOAT, 256x256x3x3]
%onnx::Conv_710[FLOAT, 256x256x3x3]
%onnx::Conv_713[FLOAT, 256x256x1x1]
%onnx::Conv_716[FLOAT, 256x256x3x3]
%onnx::Conv_719[FLOAT, 256x256x3x3]
%onnx::Conv_722[FLOAT, 256x256x3x3]
%onnx::Conv_725[FLOAT, 256x256x1x1]
%onnx::Conv_728[FLOAT, 256x256x3x3]
%onnx::Conv_731[FLOAT, 256x256x3x3]
%onnx::Conv_734[FLOAT, 256x256x3x3]
%onnx::Conv_737[FLOAT, 512x256x1x1]
%onnx::Conv_738[FLOAT, 512]
%onnx::Conv_740[FLOAT, 512x512x3x3]
%onnx::Conv_743[FLOAT, 512x512x3x3]
%onnx::Conv_746[FLOAT, 512x512x3x3]
%onnx::Conv_749[FLOAT, 512x512x1x1]
%onnx::Conv_752[FLOAT, 512x512x3x3]
%onnx::Conv_755[FLOAT, 512x512x3x3]
%onnx::Conv_758[FLOAT, 512x512x3x3]
%onnx::Conv_761[FLOAT, 512x512x1x1]
%onnx::Conv_764[FLOAT, 512x512x3x3]
%onnx::Conv_767[FLOAT, 512x512x3x3]
%onnx::Conv_770[FLOAT, 512x512x3x3]
) {
%onnx::Conv_771 = Identity(%onnx::Conv_738)
%onnx::Conv_768 = Identity(%onnx::Conv_738)
%onnx::Conv_765 = Identity(%onnx::Conv_738)
%onnx::Conv_762 = Identity(%onnx::Conv_738)
%onnx::Conv_759 = Identity(%onnx::Conv_738)
%onnx::Conv_756 = Identity(%onnx::Conv_738)
%onnx::Conv_753 = Identity(%onnx::Conv_738)
%onnx::Conv_750 = Identity(%onnx::Conv_738)
%onnx::Conv_747 = Identity(%onnx::Conv_738)
%onnx::Conv_744 = Identity(%onnx::Conv_738)
%onnx::Conv_741 = Identity(%onnx::Conv_738)
%onnx::Conv_735 = Identity(%onnx::Conv_702)
%onnx::Conv_732 = Identity(%onnx::Conv_702)
%onnx::Conv_729 = Identity(%onnx::Conv_702)
%onnx::Conv_726 = Identity(%onnx::Conv_702)
%onnx::Conv_723 = Identity(%onnx::Conv_702)
%onnx::Conv_720 = Identity(%onnx::Conv_702)
%onnx::Conv_717 = Identity(%onnx::Conv_702)
%onnx::Conv_714 = Identity(%onnx::Conv_702)
%onnx::Conv_711 = Identity(%onnx::Conv_702)
%onnx::Conv_708 = Identity(%onnx::Conv_702)
%onnx::Conv_705 = Identity(%onnx::Conv_702)
%onnx::Conv_699 = Identity(%onnx::Conv_663)
%onnx::Conv_696 = Identity(%onnx::Conv_663)
%onnx::Conv_693 = Identity(%onnx::Conv_663)
%onnx::Conv_690 = Identity(%onnx::Conv_663)
%onnx::Conv_687 = Identity(%onnx::Conv_663)
%onnx::Conv_684 = Identity(%onnx::Conv_663)
%onnx::Conv_681 = Identity(%onnx::Conv_663)
%onnx::Conv_678 = Identity(%onnx::Conv_663)
%onnx::Conv_675 = Identity(%onnx::Conv_663)
%onnx::Conv_672 = Identity(%onnx::Conv_663)
%onnx::Conv_669 = Identity(%onnx::Conv_663)
%onnx::Conv_666 = Identity(%onnx::Conv_663)
%/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_662, %onnx::Conv_663)
%/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_665, %onnx::Conv_666)
%/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_668, %onnx::Conv_669)
%/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_671, %onnx::Conv_672)
%/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/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/Add_4_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_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_674, %onnx::Conv_675)
%/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_677, %onnx::Conv_678)
%/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_680, %onnx::Conv_681)
%/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_683, %onnx::Conv_684)
%/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/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/Add_4_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_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_686, %onnx::Conv_687)
%/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_689, %onnx::Conv_690)
%/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_692, %onnx::Conv_693)
%/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_695, %onnx::Conv_696)
%/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/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/Add_4_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_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_698, %onnx::Conv_699)
%/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_701, %onnx::Conv_702)
%/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_704, %onnx::Conv_705)
%/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_707, %onnx::Conv_708)
%/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/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.1/maxpool/MaxPool_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.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_710, %onnx::Conv_711)
%/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_713, %onnx::Conv_714)
%/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_716, %onnx::Conv_717)
%/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_719, %onnx::Conv_720)
%/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/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.1/maxpool/MaxPool_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.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_722, %onnx::Conv_723)
%/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_725, %onnx::Conv_726)
%/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_728, %onnx::Conv_729)
%/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_731, %onnx::Conv_732)
%/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/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.1/maxpool/MaxPool_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.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_734, %onnx::Conv_735)
%/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_737, %onnx::Conv_738)
%/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_740, %onnx::Conv_741)
%/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_743, %onnx::Conv_744)
%/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/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/Add_4_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_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_746, %onnx::Conv_747)
%/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_749, %onnx::Conv_750)
%/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_752, %onnx::Conv_753)
%/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_755, %onnx::Conv_756)
%/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/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/Add_4_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_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_758, %onnx::Conv_759)
%/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_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/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_764, %onnx::Conv_765)
%/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_767, %onnx::Conv_768)
%/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/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/Add_4_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_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_770, %onnx::Conv_771)
%/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)
%660 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %660
}
|
val_accuracy
| 90.645033
| 8,452,319,232
| 28,767,882
|
{'zcp_epe_nas': 85.38858880557078, 'zcp_fisher': 48.77724838256836, 'zcp_flops': 135237107712.0, 'zcp_grad_norm': 101.56060028076172, 'zcp_grasp': 1.13568115234375, 'zcp_jacov': -16.05498421729334, 'zcp_l2_norm': 835.0948486328125, 'zcp_nwot': 227.94141390052764, 'zcp_params': 28767882.0, 'zcp_plain': -0.032914862036705, 'zcp_snip': 956.9404296875, 'zcp_synflow': 139.83997527662493, 'zcp_zen': 98.40277099609375, 'zcp_val_accuracy': 0.940204322338104}
| |
NASBench101_398718
|
NASBench101
|
398718
|
f105c29440451c9692a97ffbd99215f2
|
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, 43x43x1x1]
%onnx::Conv_818[FLOAT, 43x43x3x3]
%onnx::Conv_821[FLOAT, 42x42x1x1]
%onnx::Conv_822[FLOAT, 42]
%onnx::Conv_824[FLOAT, 128x128x1x1]
%onnx::Conv_827[FLOAT, 43x128x1x1]
%onnx::Conv_830[FLOAT, 43x43x1x1]
%onnx::Conv_833[FLOAT, 43x43x3x3]
%onnx::Conv_836[FLOAT, 42x42x1x1]
%onnx::Conv_839[FLOAT, 128x128x1x1]
%onnx::Conv_842[FLOAT, 43x128x1x1]
%onnx::Conv_845[FLOAT, 43x43x1x1]
%onnx::Conv_848[FLOAT, 43x43x3x3]
%onnx::Conv_851[FLOAT, 42x42x1x1]
%onnx::Conv_854[FLOAT, 128x128x1x1]
%onnx::Conv_857[FLOAT, 86x128x1x1]
%onnx::Conv_858[FLOAT, 86]
%onnx::Conv_860[FLOAT, 85x85x1x1]
%onnx::Conv_861[FLOAT, 85]
%onnx::Conv_863[FLOAT, 85x85x3x3]
%onnx::Conv_866[FLOAT, 85x85x1x1]
%onnx::Conv_869[FLOAT, 256x128x1x1]
%onnx::Conv_870[FLOAT, 256]
%onnx::Conv_872[FLOAT, 86x256x1x1]
%onnx::Conv_875[FLOAT, 85x85x1x1]
%onnx::Conv_878[FLOAT, 85x85x3x3]
%onnx::Conv_881[FLOAT, 85x85x1x1]
%onnx::Conv_884[FLOAT, 256x256x1x1]
%onnx::Conv_887[FLOAT, 86x256x1x1]
%onnx::Conv_890[FLOAT, 85x85x1x1]
%onnx::Conv_893[FLOAT, 85x85x3x3]
%onnx::Conv_896[FLOAT, 85x85x1x1]
%onnx::Conv_899[FLOAT, 256x256x1x1]
%onnx::Conv_902[FLOAT, 171x256x1x1]
%onnx::Conv_903[FLOAT, 171]
%onnx::Conv_905[FLOAT, 171x171x1x1]
%onnx::Conv_908[FLOAT, 171x171x3x3]
%onnx::Conv_911[FLOAT, 170x170x1x1]
%onnx::Conv_912[FLOAT, 170]
%onnx::Conv_914[FLOAT, 512x256x1x1]
%onnx::Conv_915[FLOAT, 512]
%onnx::Conv_917[FLOAT, 171x512x1x1]
%onnx::Conv_920[FLOAT, 171x171x1x1]
%onnx::Conv_923[FLOAT, 171x171x3x3]
%onnx::Conv_926[FLOAT, 170x170x1x1]
%onnx::Conv_929[FLOAT, 512x512x1x1]
%onnx::Conv_932[FLOAT, 171x512x1x1]
%onnx::Conv_935[FLOAT, 171x171x1x1]
%onnx::Conv_938[FLOAT, 171x171x3x3]
%onnx::Conv_941[FLOAT, 170x170x1x1]
%onnx::Conv_944[FLOAT, 512x512x1x1]
) {
%onnx::Conv_945 = Identity(%onnx::Conv_915)
%onnx::Conv_942 = Identity(%onnx::Conv_912)
%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_912)
%onnx::Conv_924 = Identity(%onnx::Conv_903)
%onnx::Conv_921 = Identity(%onnx::Conv_903)
%onnx::Conv_918 = Identity(%onnx::Conv_903)
%onnx::Conv_909 = Identity(%onnx::Conv_903)
%onnx::Conv_906 = Identity(%onnx::Conv_903)
%onnx::Conv_900 = Identity(%onnx::Conv_870)
%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_870)
%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_867 = Identity(%onnx::Conv_861)
%onnx::Conv_864 = Identity(%onnx::Conv_861)
%onnx::Conv_855 = Identity(%onnx::Conv_810)
%onnx::Conv_852 = Identity(%onnx::Conv_822)
%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_810)
%onnx::Conv_837 = Identity(%onnx::Conv_822)
%onnx::Conv_834 = Identity(%onnx::Conv_813)
%onnx::Conv_831 = Identity(%onnx::Conv_813)
%onnx::Conv_828 = Identity(%onnx::Conv_813)
%onnx::Conv_825 = Identity(%onnx::Conv_810)
%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/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.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_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_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/conv3x3/conv_bn_relu/conv_bn_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.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 = <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/conv1x1/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/conv3x3/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_2_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_10_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/Slice_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_3_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/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/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.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_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/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_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/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.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_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_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/conv3x3/conv_bn_relu/conv_bn_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.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 = <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/conv1x1/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/conv3x3/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_2_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_10_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/Slice_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_3_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/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/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.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_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/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_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/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_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_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_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/conv3x3/conv_bn_relu/conv_bn_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.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 = <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/conv1x1/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/conv3x3/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_2_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_10_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/Slice_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_3_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/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/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.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_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/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_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/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.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_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_5_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_5_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_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_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/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_866, %onnx::Conv_867)
%/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/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.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_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/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_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/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.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_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_5_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_5_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_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_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/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_881, %onnx::Conv_882)
%/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/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.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_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/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_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/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_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_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_5_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_5_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_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_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/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_896, %onnx::Conv_897)
%/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/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.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_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/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_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/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.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_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_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/conv3x3/conv_bn_relu/conv_bn_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.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 = <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/conv1x1/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/conv3x3/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_2_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_10_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/Slice_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_3_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/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/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.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_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/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_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/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.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_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_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/conv3x3/conv_bn_relu/conv_bn_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.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 = <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/conv1x1/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/conv3x3/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_2_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_10_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/Slice_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_3_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/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/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.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_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/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_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/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_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_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_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/conv3x3/conv_bn_relu/conv_bn_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.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 = <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/conv1x1/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/conv3x3/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_2_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_10_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/Slice_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_3_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/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/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.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_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/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)
%807 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %807
}
|
val_accuracy
| 92.327726
| 749,334,784
| 2,443,289
|
{'zcp_epe_nas': 97.36434482858066, 'zcp_fisher': 3.746142387390136, 'zcp_flops': 11989356544.0, 'zcp_grad_norm': 45.392208099365234, 'zcp_grasp': -5.594940185546875, 'zcp_jacov': -16.051138405462602, 'zcp_l2_norm': 761.9805908203125, 'zcp_nwot': 220.98457701820374, 'zcp_params': 2443289.0, 'zcp_plain': 0.12054069340229001, 'zcp_snip': 241.37355041503906, 'zcp_synflow': 100.96947900467532, 'zcp_zen': 76.51708984375, 'zcp_val_accuracy': 0.8534655570983881}
|
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