Use tqdm reporting with validation
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@ -246,12 +246,12 @@ def main():
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model.force_restore_swapout()
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val_batch_sz = 1 if 'batch_size' not in opt['datasets']['val'].keys() else opt['datasets']['val']['batch_size']
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# does not support multi-GPU validation
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pbar = util.ProgressBar(len(val_loader) * val_batch_sz)
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avg_psnr = 0.
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avg_fea_loss = 0.
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idx = 0
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colab_imgs_to_copy = []
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for val_data in val_loader:
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val_tqdm = tqdm(val_loader)
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for val_data in val_tqdm:
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idx += 1
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for b in range(len(val_data['LQ_path'])):
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img_name = os.path.splitext(os.path.basename(val_data['LQ_path'][b]))[0]
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