Load checkpoint on CPU instead of on GPU (ultralytics#6516)

* Load checkpoint on CPU instead of on GPU

* refactor: simplify code

* Cleanup

* Update train.py

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

train.py

@@ -120,7 +120,7 @@ def train(hyp,  # path/to/hyp.yaml or hyp dictionary
     if pretrained:
         with torch_distributed_zero_first(LOCAL_RANK):
             weights = attempt_download(weights)  # download if not found locally
-        ckpt = torch.load(weights, map_location=device)  # load checkpoint
+        ckpt = torch.load(weights, map_location='cpu')  # load checkpoint to CPU to avoid CUDA memory leak
         model = Model(cfg or ckpt['model'].yaml, ch=3, nc=nc, anchors=hyp.get('anchors')).to(device)  # create
         exclude = ['anchor'] if (cfg or hyp.get('anchors')) and not resume else []  # exclude keys
         csd = ckpt['model'].float().state_dict()  # checkpoint state_dict as FP32