This problem occurs when training deraining dataset. Why is that?

[lonely6628]

Hello,I'm sorry to bother you. I encountered a problem when training the deraining dataset. My friends didn't encountered this case, so I'd like to ask you to help me see the reason for this error. I only changed the values of BATCH_SIZE and TRAIN_PS in the train. yml file, it occurred during the training of epochs 9, 22, 31 and 60. The error code is as follows:

Traceback (most recent call last):
  File "train.py", line 109, in <module>
    for i, data in enumerate(tqdm(train_loader), 0):
  File "/home/min1/anaconda3/envs/bwq/lib/python3.7/site-packages/tqdm/std.py", line 1185, in __iter__
    for obj in iterable:
  File "/home/min1/anaconda3/envs/bwq/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 582, in __next__
    return self._process_next_batch(batch)
  File "/home/min1/anaconda3/envs/bwq/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 608, in _process_next_batch
    raise batch.exc_type(batch.exc_msg)
RuntimeError: Traceback (most recent call last):
  File "/home/min1/anaconda3/envs/bwq/lib/python3.7/site-packages/torch/utils/data/_utils/worker.py", line 99, in _worker_loop
    samples = collate_fn([dataset[i] for i in batch_indices])
  File "/home/min1/anaconda3/envs/bwq/lib/python3.7/site-packages/torch/utils/data/_utils/collate.py", line 68, in default_collate
    return [default_collate(samples) for samples in transposed]
  File "/home/min1/anaconda3/envs/bwq/lib/python3.7/site-packages/torch/utils/data/_utils/collate.py", line 68, in <listcomp>
    return [default_collate(samples) for samples in transposed]
  File "/home/min1/anaconda3/envs/bwq/lib/python3.7/site-packages/torch/utils/data/_utils/collate.py", line 43, in default_collate
    return torch.stack(batch, 0, out=out)
RuntimeError: invalid argument 0: Sizes of tensors must match except in dimension 0. Got 128 and 126 in dimension 3 at /opt/conda/conda-bld/pytorch_1556653114079/work/aten/src/TH/generic/THTensor.cpp:711

[adityac8]

Hi,

Which TRAIN_PS are you using. Also, are you using the MPRNet model.

Thanks

[lonely6628]

Hello,thank you very much for your reply!
Yes, I use the MPRNet Model.
I changed the value of TRAIN_PS to 128 and the value of BATCH_SIZE to 2. Nothing else has changed.

[adityac8]

Hi

Make sure you do not turn off reflection padding in dataset_RGB.py

There are certain images whose height and width are smaller than 128. For those particular cases, we reflect pad it to TRAIN_PS.

Thanks

[lonely6628]

Hi,I didn't modify the code in dataset_RGB.py, the code of reflection padding should be effective.

Thanks for your reply!

[lonely6628]

Hi, I really appreciate your guidance！
I have solved this problem. This is because there is a different size of the input picture and the target picture in the dataset.

[adityac8]

Hi @lonely6628

I am glad that your issue is solved.
I checked the dataset we uploaded and there does not seem to be such problem with the data.

Thanks