🔨 [Add] helper function - auto padding & act func

yolo/tools/module_helper.py

@@ -0,0 +1,36 @@
+from typing import Tuple
+
+from torch import nn
+from torch.nn.common_types import _size_2_t
+
+
+def auto_pad(kernel_size: _size_2_t, dilation: _size_2_t = 1, **kwargs) -> Tuple[int, int]:
+    """
+    Auto Padding for the convolution blocks
+    """
+    if isinstance(kernel_size, int):
+        kernel_size = (kernel_size, kernel_size)
+    if isinstance(dilation, int):
+        dilation = (dilation, dilation)
+
+    pad_h = ((kernel_size[0] - 1) * dilation[0]) // 2
+    pad_w = ((kernel_size[1] - 1) * dilation[1]) // 2
+    return (pad_h, pad_w)
+
+
+def get_activation(activation: str) -> nn.Module:
+    """
+    Retrieves an activation function from the PyTorch nn module based on its name, case-insensitively.
+    """
+    if not activation or activation.lower() in ["false", "none"]:
+        return nn.Identity()
+
+    activation_map = {
+        name.lower(): obj
+        for name, obj in nn.modules.activation.__dict__.items()
+        if isinstance(obj, type) and issubclass(obj, nn.Module)
+    }
+    if activation.lower() in activation_map:
+        return activation_map[activation.lower()]()
+    else:
+        raise ValueError(f"Activation function '{activation}' is not found in torch.nn")