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@ -118,8 +118,9 @@ def train(hyp):
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if model.state_dict()[k].shape == v.shape} # to FP32, filter
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model.load_state_dict(ckpt['model'], strict=False)
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except KeyError as e:
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s = "%s is not compatible with %s. Specify --weights '' or specify a --cfg compatible with %s." \
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% (opt.weights, opt.cfg, opt.weights)
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s = "%s is not compatible with %s. This may be due to model differences or %s may be out of date. " \
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"Please delete or update %s and try again, or use --weights '' to train from scatch." \
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% (opt.weights, opt.cfg, opt.weights, opt.weights)
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raise KeyError(s) from e
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# load optimizer
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