[BugFix][Torchvision] update optimizer state dict before transfer learning (#1358)

* Add: an `_update_checkpoint_optimizer(...)` for deleting mismatching params from saved optimizer(s) state_dict

* Remove: _update_checkpoint_optimizer in favor of loading in the optim state_dict only when `args.resume` is set

* Remove: un-needed imports

* Address review comments

* Style

Author: rahul-tuli

src/sparseml/pytorch/torchvision/train.py

@@ -533,7 +533,14 @@ def collate_fn(batch):
     # load params
     if checkpoint is not None:
         if "optimizer" in checkpoint and not args.test_only:
-            optimizer.load_state_dict(checkpoint["optimizer"])
+            if args.resume:
+                optimizer.load_state_dict(checkpoint["optimizer"])
+            else:
+                warnings.warn(
+                    "Optimizer state dict not loaded from checkpoint. Unless run is "
+                    "resumed with the --resume arg, the optimizer will start from a "
+                    "fresh state"
+                )
         if model_ema and "model_ema" in checkpoint:
             model_ema.load_state_dict(checkpoint["model_ema"])
         if scaler and "scaler" in checkpoint: