remove load checkpoint

mmlearn/modules/encoders/vision.py

@@ -310,41 +310,6 @@ def _init_weights(self, m: nn.Module) -> None:
             if m.bias is not None:
                 nn.init.constant_(m.bias, 0)
 
-    def load_checkpoint(
-        self,
-        device: str,
-        checkpoint_path: str,
-        encoder: nn.Module,
-        predictor: nn.Module,
-        target_encoder: nn.Module,
-    ) -> Tuple[nn.Module, nn.Module, nn.Module]:
-        """Load a pre-trained model from a checkpoint."""
-        try:
-            checkpoint = torch.load(checkpoint_path, map_location=torch.device(device))
-            epoch = checkpoint["epoch"]
-
-            # loading encoder
-            pretrained_dict = checkpoint["encoder"]
-            msg = encoder.load_state_dict(pretrained_dict)
-            print(f"loaded pretrained encoder from epoch {epoch} with msg: {msg}")
-
-            # loading predictor
-            pretrained_dict = checkpoint["predictor"]
-            msg = predictor.load_state_dict(pretrained_dict)
-            print(f"loaded pretrained encoder from epoch {epoch} with msg: {msg}")
-
-            # loading target_encoder
-            if target_encoder is not None:
-                print(list(checkpoint.keys()))
-                pretrained_dict = checkpoint["target_encoder"]
-                msg = target_encoder.load_state_dict(pretrained_dict)
-                print(f"loaded pretrained encoder from epoch {epoch} with msg: {msg}")
-
-        except Exception as e:
-            print(f"Encountered exception when loading checkpoint {e}")
-
-        return encoder, predictor, target_encoder
-
     def forward(
         self,
         x: torch.Tensor,