Folder Structure for VicRegL

[ramdhan1989]

Hi I got this error when following ViCRegL tutorial, I think it was coming from dataloader with error as follow? I used my own dataset. I wonder how the correct folder structure for this model?

`Starting Training 0%| | 0/255 [00:27<?, ?it/s]

AttributeError Traceback (most recent call last) Cell In[5], line 5 3 total_loss = 0 4 for views_and_grids in tqdm(dataloader): ----> 5 views_and_grids = [x.to(device) for x in views_and_grids] 6 views = views_and_grids[: len(views_and_grids) // 2] 7 grids = views_and_grids[len(views_and_grids) // 2 :]

Cell In[5], line 5, in (.0) 3 total_loss = 0 4 for views_and_grids in tqdm(dataloader): ----> 5 views_and_grids = [x.to(device) for x in views_and_grids] 6 views = views_and_grids[: len(views_and_grids) // 2] 7 grids = views_and_grids[len(views_and_grids) // 2 :]

AttributeError: 'list' object has no attribute 'to'`

and this is my dataloader

`transform = VICRegLTransform(n_local_views=0) path = 'D:/xxx/images/'

dataset = data.LightlyDataset(path, transform=transform)

dataloader = torch.utils.data.DataLoader( dataset, batch_size=256, shuffle=True, drop_last=True, num_workers=8, )`

inside folder "images" there is another one folder containing images

Thank you

[guarin]

The dataloader should return batches with type tuple[list[Tensor], Tensor]. Tensor are the targets/labels of the images and list[Tensor] contains the different augmented views of the images. Every Tensor in list[Tensor] is one view of the batch.

I believe you have to change the iteration code over the dataloader slightly. This might work:

for batch in tqdm(dataloader):     # batch is a tuple[list[Tensor], Tensor]
    views_and_grids = batch[0].    # views_and_grids is a list[Tensor]
    views_and_grids = [x.to(device) for x in views_and_grids]

[guarin]

I'll close this for now, please reopen if you encounter more issues.