Reduce sync loss weight
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@ -251,7 +251,7 @@ def train(device, model, train_data_loader, test_data_loader, optimizer,
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average_sync_loss = eval_model(test_data_loader, global_step, device, model, checkpoint_dir)
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if average_sync_loss < .75:
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hparams.set_hparam('syncnet_wt', 0.03)
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hparams.set_hparam('syncnet_wt', 0.01) # without image GAN a lesser weight is sufficient
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prog_bar.set_description('L1: {}, Sync Loss: {}'.format(running_l1_loss / (step + 1),
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running_sync_loss / (step + 1)))
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