🔥 [Remove] layer_helper, same func as module_helper

yolo/model/yolo.py

@@ -5,8 +5,8 @@ from loguru import logger
 from omegaconf import ListConfig, OmegaConf
 
 from yolo.config.config import Config, Model, YOLOLayer
-from yolo.tools.layer_helper import get_layer_map
 from yolo.tools.log_helper import log_model
+from yolo.tools.module_helper import get_layer_map
 from yolo.utils.drawer import draw_model
 
 

yolo/tools/layer_helper.py

@@ -3,20 +3,3 @@ import inspect
 import torch.nn as nn
 
 from yolo.model import module
-
-
-def auto_pad():
-    raise NotImplementedError
-
-
-def get_layer_map():
-    """
-    Dynamically generates a dictionary mapping class names to classes,
-    filtering to include only those that are subclasses of nn.Module,
-    ensuring they are relevant neural network layers.
-    """
-    layer_map = {}
-    for name, obj in inspect.getmembers(module, inspect.isclass):
-        if issubclass(obj, nn.Module) and obj is not nn.Module:
-            layer_map[name] = obj
-    return layer_map

yolo/tools/module_helper.py

@@ -1,3 +1,4 @@
+import inspect
 from typing import Tuple, Union
 
 from torch import Tensor, nn
@@ -18,6 +19,21 @@ def auto_pad(kernel_size: _size_2_t, dilation: _size_2_t = 1, **kwargs) -> Tuple
     return (pad_h, pad_w)
 
 
+def get_layer_map():
+    """
+    Dynamically generates a dictionary mapping class names to classes,
+    filtering to include only those that are subclasses of nn.Module,
+    ensuring they are relevant neural network layers.
+    """
+    layer_map = {}
+    from yolo.model import module
+
+    for name, obj in inspect.getmembers(module, inspect.isclass):
+        if issubclass(obj, nn.Module) and obj is not nn.Module:
+            layer_map[name] = obj
+    return layer_map
+
+
 def get_activation(activation: str) -> nn.Module:
     """
     Retrieves an activation function from the PyTorch nn module based on its name, case-insensitively.