Indexing over DataLoader

Hi there,

I would like to access the batches created by DataLoader with their indices. Is there an easy function in PyTorch for this?

More precisely, I’d like to say something like:

 val_data        = torchvision.datasets.ImageFolder(root='./imagenet2012',transform=transform);
 val_loader     =, batch_size=batchSize)

 for i in range(len(val_loader)):
      inputs, _        = val_loader.__getbatch__(i);

Any comment is much appreciated.


There isn’t a way to do this directly.

However, if you modify this file slightly, it’ll be possible:

Particularly, see the next function of the DataLoaderIter, you could enumerate self.sample_iter fully before hand (the indices of each mini-batch), and then you can have a function on that iterator that just returns a particular index.


@hatef Have you successfully implemented that and would you mind sharing your code please? I’m still have difficulty despite @smth 's hint :frowning:

hey @smth,

I’d like to use num_workers > 1 and be able to receive the indices. I’m not so familiar with multiprocessing. Is it sufficient to return indices from _put_indices() , ?


you can you can use tqdm_notebook pakage to do that:

for i, (train_inputs, train_labels) in tqdm_notebook(enumerate(dl), total=n):
train_inputs, train_labels = to_var(train_inputs), to_var(train_labels)