allow to use custom norm_layer (#4621)

torchvision/models/regnet.py

@@ -392,7 +392,8 @@ class RegNet(nn.Module):
 
 
 def _regnet(arch: str, block_params: BlockParams, pretrained: bool, progress: bool, **kwargs: Any) -> RegNet:
-    model = RegNet(block_params, norm_layer=partial(nn.BatchNorm2d, eps=1e-05, momentum=0.1), **kwargs)
+    norm_layer = kwargs.pop("norm_layer", partial(nn.BatchNorm2d, eps=1e-05, momentum=0.1))
+    model = RegNet(block_params, norm_layer=norm_layer, **kwargs)
     if pretrained:
         if arch not in model_urls:
             raise ValueError(f"No checkpoint is available for model type {arch}")