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Use tqdm reporting with validation

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This commit is contained in:
James Betker 2020-10-03 11:16:39 -06:00
parent 6c9718ad64
commit 21d3bb83b2
1 changed files with 2 additions and 2 deletions
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codes/train.py
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@ -246,12 +246,12 @@ def main():
model.force_restore_swapout() model.force_restore_swapout()
val_batch_sz = 1 if 'batch_size' not in opt['datasets']['val'].keys() else opt['datasets']['val']['batch_size'] val_batch_sz = 1 if 'batch_size' not in opt['datasets']['val'].keys() else opt['datasets']['val']['batch_size']
# does not support multi-GPU validation # does not support multi-GPU validation
pbar = util.ProgressBar(len(val_loader) * val_batch_sz)
avg_psnr = 0. avg_psnr = 0.
avg_fea_loss = 0. avg_fea_loss = 0.
idx = 0 idx = 0
colab_imgs_to_copy = [] colab_imgs_to_copy = []
for val_data in val_loader: val_tqdm = tqdm(val_loader)
for val_data in val_tqdm:
idx += 1 idx += 1
for b in range(len(val_data['LQ_path'])): for b in range(len(val_data['LQ_path'])):
img_name = os.path.splitext(os.path.basename(val_data['LQ_path'][b]))[0] img_name = os.path.splitext(os.path.basename(val_data['LQ_path'][b]))[0]