Update models/common.py

models/common.py

@@ -35,15 +35,15 @@ from utils.plots import Annotator, colors, save_one_box
 from utils.torch_utils import copy_attr, smart_inference_mode
 
 
-
-def autopad(k, p, d):
+def autopad(k, p=None, d=1):  # kernel, padding, dilation
+    # Pad to 'same' shape outputs
+    if d > 1:
+        k = d * (k - 1) + 1 if isinstance(k, int) else [d * (x - 1) + 1 for x in k]  # actual kernel-size
     if p is None:
-        if d != 1:
-            p = d * (k - 1) // 2
-        else:
-            p = k // 2
+        p = k // 2 if isinstance(k, int) else [x // 2 for x in k]  # auto-pad
     return p
 
+
 class Conv(nn.Module):
     # Standard convolution with args(ch_in, ch_out, kernel, stride, padding, groups, dilation, activation)
     default_act = nn.SiLU()  # default activation
@@ -55,15 +55,10 @@ class Conv(nn.Module):
         self.act = self.default_act if act is True else act if isinstance(act, nn.Module) else nn.Identity()
 
     def forward(self, x):
-        out = self.conv(x)
-        out = self.bn(out)
-        out = self.act(out)
-        return out
+        return self.act(self.bn(self.conv(x)))
 
     def forward_fuse(self, x):
-        out = self.conv(x)
-        out = self.act(out)
-        return out
+        return self.act(self.conv(x))
 
 
 class DWConv(Conv):