updates
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train.py
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train.py
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@ -283,9 +283,6 @@ def train():
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s = ('%10s' * 2 + '%10.3g' * 6) % (
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'%g/%g' % (epoch, epochs - 1), '%.3gG' % mem, *mloss, len(targets), img_size)
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pbar.set_description(s)
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if torch.isnan(loss):
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print('WARNING: nan loss detected, ending training', loss_items)
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return results
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# end batch ------------------------------------------------------------------------------------------------
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