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@@ -50,8 +50,6 @@ def do_train(start_epoch, args, model, train_loader, evaluator, optimizer,
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ret = model(batch)
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ret = model(batch)
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total_loss = sum([v for k, v in ret.items() if "loss" in k])
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total_loss = sum([v for k, v in ret.items() if "loss" in k])
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- total_loss = sum([v for k, v in ret.items() if "loss" in k])
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-
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batch_size = batch['images'].shape[0]
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batch_size = batch['images'].shape[0]
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meters['loss'].update(total_loss.item(), batch_size)
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meters['loss'].update(total_loss.item(), batch_size)
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meters['sdm_loss'].update(ret.get('sdm_loss', 0), batch_size)
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meters['sdm_loss'].update(ret.get('sdm_loss', 0), batch_size)
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