updates
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train.py
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train.py
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@ -235,7 +235,7 @@ def train(cfg,
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# Print batch results
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mloss = (mloss * i + loss_items) / (i + 1) # update mean losses
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mem = torch.cuda.memory_cached() if torch.cuda.is_available() else 0
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mem = torch.cuda.memory_cached() / 1E6 if torch.cuda.is_available() else 0
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s = ('%8s' + '%10.3g' * 8) % ('%g/%g' % (epoch, epochs - 1), *mloss, len(targets), img_size, mem)
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pbar.set_description(s) # print(s)
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