DCO Remediation Commit for Mohammad Amanour Rahman <[email protected]>

I, Mohammad Amanour Rahman <[email protected]>, hereby add my Signed-off-by to this commit.

Signed-off-by: Mohammad Amanour Rahman <[email protected]>

Author: aman0311x

monai/losses/perceptual.py

@@ -23,7 +23,7 @@
 torchvision, _ = optional_import("torchvision")
 
 
-class PercetualNetworkType(StrEnum):
+class PerceptualNetworkType(StrEnum):
     alex = "alex"
     vgg = "vgg"
     squeeze = "squeeze"
@@ -49,11 +49,15 @@ class PerceptualLoss(nn.Module):
 
     Args:
         spatial_dims: number of spatial dimensions.
-        network_type: str or PercetualNetworkType Specifies the network architecture to use. Supported values are defined in
-            ``PercetualNetworkType`` (e.g., ``"alex"``, ``"vgg"``, ``"squeeze"``,
-            ``"radimagenet_resnet50"``, ``"medicalnet_resnet10_23datasets"``,
-            ``"medicalnet_resnet50_23datasets"``, ``"resnet50"``).
-            Defaults to ``PercetualNetworkType.alex``.
+        network_type : str
+            One of:
+            - "alex"
+            - "vgg"
+            - "squeeze"
+            - "radimagenet_resnet50"
+            - "medicalnet_resnet10_23datasets"
+            - "medicalnet_resnet50_23datasets"
+            - "resnet50"
         is_fake_3d: if True use 2.5D approach for a 3D perceptual loss.
         fake_3d_ratio: ratio of how many slices per axis are used in the 2.5D approach.
         cache_dir: path to cache directory to save the pretrained network weights.