I have 2 datasets, in which each has a different sequence of transforms applied e.g., the first transform differs in whether the data needs to be converted to a PILImage. Transforms are applied in their getitem function definitions.
I am able to construct a data loader on each data separately and train properly.
I am trying to construct a single data loader with the 2 datasets merged and interleaved randomly.
I used a ConcatDataset to combine the 2 datasets, and passed this into the dataset loader (where the instances get shuffled), but get the following error after 1 epoch appears to complete successfully. I’m not sure why this error is occurring since the dataloader works when constructed using each dataset separately.
AttributeError: Caught AttributeError in DataLoader worker process 0.
Original Traceback (most recent call last):
File “/home/.conda/envs/di_env/lib/python3.6/site-packages/torch/utils/data/_utils/worker.py”, line 178, in _worker_loop
data = fetcher.fetch(index)
File “/home//.conda/envs/di_env/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py”, line 47, in fetch
return self.collate_fn(data)
File “/home//.conda/envs/di_env/lib/python3.6/site-packages/torch/utils/data/_utils/collate.py”, line 79, in default_collate
return [default_collate(samples) for samples in transposed]
File “/home//.conda/envs/di_env/lib/python3.6/site-packages/torch/utils/data/_utils/collate.py”, line 79, in 
return [default_collate(samples) for samples in transposed]
File “/home//.conda/envs/di_env/lib/python3.6/site-packages/torch/utils/data/_utils/collate.py”, line 52, in default_collate
numel = sum([x.numel() for x in batch])
File “/home//.conda/envs/di_env/lib/python3.6/site-packages/torch/utils/data/_utils/collate.py”, line 52, in 
numel = sum([x.numel() for x in batch])
AttributeError: ‘int’ object has no attribute ‘numel’