Set param.requires_grad = False

generative/losses/perceptual.py

@@ -137,6 +137,9 @@ def __init__(self, net: str = "medicalnet_resnet10_23datasets", verbose: bool =
         self.model = torch.hub.load("Warvito/MedicalNet-models", model=net, verbose=verbose)
         self.eval()
 
+        for param in self.parameters():
+            param.requires_grad = False
+
     def forward(self, input: torch.Tensor, target: torch.Tensor) -> torch.Tensor:
         """
         Compute perceptual loss using MedicalNet 3D networks. The input and target tensors are inputted in the
@@ -198,6 +201,9 @@ def __init__(self, net: str = "radimagenet_resnet50", verbose: bool = False) ->
         self.model = torch.hub.load("Warvito/radimagenet-models", model=net, verbose=verbose)
         self.eval()
 
+        for param in self.parameters():
+            param.requires_grad = False
+
     def forward(self, input: torch.Tensor, target: torch.Tensor) -> torch.Tensor:
         """
         We expect that the input is normalised between [0, 1]. Given the preprocessing performed during the training at

tests/utils.py

@@ -1,8 +1,6 @@
 # COPIED FROM https://github.com/Project-MONAI/MONAI/blob/fdd07f36ecb91cfcd491533f4792e1a67a9f89fc/tests/utils.py
 # ---------------------------------------------------------------
-
-from __future__ import annotations
-
+#
 # Copyright (c) MONAI Consortium
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.