Hi @ptrblck, pytorch users,
I noticed that this behaviour is related to using nn.DataParallel() (multi-GPUs) and num_workers > 1 in torch.utils.data.DataLoader()
After a few epochs, the training crashes with errors like:
" ERROR: Unexpected bus error encountered in worker. This might be caused by insufficient shared memory (shm)"
Are there any conflicts / problems  when using multiple workers in DataLoader() and nn.DataParallel() ?
Thanks