The scenario: Training SWINIR for classical Super resolution.
- Using Available DIV2K (900 image pairs, using Ground truth and bicubic x2). It works
- Using combination of DIV2K and Flickr total 3550 images, facing above issue. Now Flickr pair was not available, therefore I down sized bicubic x2 and create the pairs.
To give an idea: ground truth image: 2040 pixels. X2 bicubic: 1020 pixels
I am giving the code github here:
Also full error:
Traceback (most recent call last):
File “/data1/aradhana/KAIR/main_train_psnr.py”, line 253, in
main()
File “/data1/aradhana/KAIR/main_train_psnr.py”, line 173, in main
for i, train_data in enumerate(train_loader):
File “/home/aradhana/PycharmProjects/pythonProject/venv/lib/python3.8/site-packages/torch/utils/data/dataloader.py”, line 633, in next
data = self._next_data()
File “/home/aradhana/PycharmProjects/pythonProject/venv/lib/python3.8/site-packages/torch/utils/data/dataloader.py”, line 1345, in _next_data
return self._process_data(data)
File “/home/aradhana/PycharmProjects/pythonProject/venv/lib/python3.8/site-packages/torch/utils/data/dataloader.py”, line 1371, in _process_data
data.reraise()
File “/home/aradhana/PycharmProjects/pythonProject/venv/lib/python3.8/site-packages/torch/_utils.py”, line 644, in reraise
raise exception
RuntimeError: Caught RuntimeError in DataLoader worker process 0.
Original Traceback (most recent call last):
File “/home/aradhana/PycharmProjects/pythonProject/venv/lib/python3.8/site-packages/torch/utils/data/_utils/worker.py”, line 308, in _worker_loop
data = fetcher.fetch(index)
File “/home/aradhana/PycharmProjects/pythonProject/venv/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py”, line 54, in fetch
return self.collate_fn(data)
File “/home/aradhana/PycharmProjects/pythonProject/venv/lib/python3.8/site-packages/torch/utils/data/_utils/collate.py”, line 265, in default_collate
return collate(batch, collate_fn_map=default_collate_fn_map)
File “/home/aradhana/PycharmProjects/pythonProject/venv/lib/python3.8/site-packages/torch/utils/data/_utils/collate.py”, line 127, in collate
return elem_type({key: collate([d[key] for d in batch], collate_fn_map=collate_fn_map) for key in elem})
File “/home/aradhana/PycharmProjects/pythonProject/venv/lib/python3.8/site-packages/torch/utils/data/_utils/collate.py”, line 127, in
return elem_type({key: collate([d[key] for d in batch], collate_fn_map=collate_fn_map) for key in elem})
File “/home/aradhana/PycharmProjects/pythonProject/venv/lib/python3.8/site-packages/torch/utils/data/_utils/collate.py”, line 119, in collate
return collate_fn_map[elem_type](batch, collate_fn_map=collate_fn_map)
File "/home/aradhana/PycharmProjects/pythonProject/venv/lib/python3.8/site-packages/torch/utils/data/utils/collate.py", line 161, in collate_tensor_fn
out = elem.new(storage).resize(len(batch), *list(elem.size()))
RuntimeError: Trying to resize storage that is not resizable