my code is
class dogloader(Dataset):
def __init__(self, img, label, transform = None):
self.img = img; self.label = label
self.transform = transform
def __len__(self):
return len(self.label)
def __getitem__(self, idx):
img = Image.open(self.img[idx]).convert('RGB')
print(img.size)
if self.transform is not None:
img = self.transform(img)
label = torch.from_numpy(np.array(self.label[idx]))
# print(idx)
return img, label
and error is
Traceback (most recent call last):
File "torch_test.py", line 31, in <module>
for batch_idx, (data, target) in enumerate(dataloader):
File "/usr/local/lib/python2.7/dist-packages/torch/utils/data/dataloader.py", line 212, in __next__
return self._process_next_batch(batch)
File "/usr/local/lib/python2.7/dist-packages/torch/utils/data/dataloader.py", line 239, in _process_next_batch
raise batch.exc_type(batch.exc_msg)
RuntimeError: Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/torch/utils/data/dataloader.py", line 41, in _worker_loop
samples = collate_fn([dataset[i] for i in batch_indices])
File "/usr/local/lib/python2.7/dist-packages/torch/utils/data/dataloader.py", line 110, in default_collate
return [default_collate(samples) for samples in transposed]
File "/usr/local/lib/python2.7/dist-packages/torch/utils/data/dataloader.py", line 90, in default_collate
storage = batch[0].storage()._new_shared(numel)
File "/usr/local/lib/python2.7/dist-packages/torch/storage.py", line 113, in _new_shared
return cls._new_using_fd(size)
RuntimeError: $ Torch: unable to mmap memory: you tried to mmap 0GB. at /b/wheel/pytorch-src/torch/lib/TH/THAllocator.c:317