Dataloader对象无法读取

[lx935484038]

`def train():
decom_net.train()
relight_net.train()

for epoch in range(args.epoch):
    times_per_epoch, sum_loss = 0, 0.

    dataloader = torch.utils.data.DataLoader(train_set, batch_size=args.batch_size, shuffle=True,
                                             num_workers=args.workers, pin_memory=True)
    decom_optim.param_groups[0]['lr'] = lr[epoch]
    
    for data in tqdm.tqdm(dataloader):
        print(data)`

无法从dataloader获取到data，报错如下：
Traceback (most recent call last): File "train.py", line 119, in <module> train() File "train.py", line 69, in train for data in tqdm.tqdm(dataloader): File "/usr/local/lib/python3.5/dist-packages/tqdm/_tqdm.py", line 1022, in __iter__ for obj in iterable: File "/usr/local/lib/python3.5/dist-packages/torch/utils/data/dataloader.py", line 336, in __next__ return self._process_next_batch(batch) File "/usr/local/lib/python3.5/dist-packages/torch/utils/data/dataloader.py", line 357, in _process_next_batch raise batch.exc_type(batch.exc_msg) ValueError: Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/torch/utils/data/dataloader.py", line 106, in _worker_loop samples = collate_fn([dataset[i] for i in batch_indices]) File "/usr/local/lib/python3.5/dist-packages/torch/utils/data/dataloader.py", line 187, in default_collate return [default_collate(samples) for samples in transposed] File "/usr/local/lib/python3.5/dist-packages/torch/utils/data/dataloader.py", line 187, in <listcomp> return [default_collate(samples) for samples in transposed] File "/usr/local/lib/python3.5/dist-packages/torch/utils/data/dataloader.py", line 173, in default_collate return torch.stack([torch.from_numpy(b) for b in batch], 0) File "/usr/local/lib/python3.5/dist-packages/torch/utils/data/dataloader.py", line 173, in <listcomp> return torch.stack([torch.from_numpy(b) for b in batch], 0) ValueError: some of the strides of a given numpy array are negative. This is currently not supported, but will be added in future releases.

[JiaqianLi]

I got the same problem with you and how do you solve it?

[x752155]

在utils.py中data_augmentation(image, mode)函数下面所有的
return np.(XX)
改成
return np.(XX).copy()

[weixinxu666]

在utils.py中data_augmentation(image, mode)函数下面所有的
return np.(XX)
改成
return np.(XX).copy()

This is the correct solution!