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Load checkpoint on CPU instead of on GPU #6516

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Feb 4, 2022
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2 changes: 1 addition & 1 deletion train.py
Original file line number Diff line number Diff line change
Expand Up @@ -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
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