Solve format issue of loading pre-trained model weights

baselines/fedvssl/fedvssl/finetune_preprocess.py

@@ -43,17 +43,17 @@ def args_parser():
 
 # Conversion of the format of pre-trained SSL model from .npz files to .pth format.
 params = np.load(args.pretrained_model_path, allow_pickle=True)
-try:
+
+if params["arr_0"].shape == ():
+    # For the cases where weights are stored as Parameters
     params = params["arr_0"].item()
-except:
-    # For the cases where the weights are stored as NumPy arrays instead of parameters
+    params = parameters_to_ndarrays(params)
+else:
+    # For the cases where weights are stored as NumPy arrays
     params = [
         np.array(v) for v in list(params["arr_0"])
     ]
-try:
-    params = parameters_to_ndarrays(params)
-except:
-    pass
+
 params_dict = zip(model.state_dict().keys(), params)
 state_dict = {
     "state_dict": OrderedDict({k: torch.from_numpy(v) for k, v in params_dict})