Attention

June 2024 Status Update: Removing DataPipes and DataLoader V2

We are re-focusing the torchdata repo to be an iterative enhancement of torch.utils.data.DataLoader. We do not plan on continuing development or maintaining the [DataPipes] and [DataLoaderV2] solutions, and they will be removed from the torchdata repo. We’ll also be revisiting the DataPipes references in pytorch/pytorch. In release torchdata==0.8.0 (July 2024) they will be marked as deprecated, and in 0.9.0 (Oct 2024) they will be deleted. Existing users are advised to pin to torchdata==0.8.0 or an older version until they are able to migrate away. Subsequent releases will not include DataPipes or DataLoaderV2. Please reach out if you suggestions or comments (please use this issue for feedback)

IndexAdder

class torchdata.datapipes.iter.IndexAdder(source_datapipe: IterDataPipe[Dict], index_name: str = 'index')

Adds an index to an existing Iterable DataPipe with (functional name: add_index). The row or batch within the DataPipe must have the type Dict; otherwise, a NotImplementedError will be thrown. The index of the data is set to the provided index_name.

Parameters:

• source_datapipe – Iterable DataPipe being indexed, its row/batch must be of type Dict

• index_name – Name of the key to store data index

Example

>>> from torchdata.datapipes.iter import IterableWrapper
>>> dp = IterableWrapper([{'a': 1, 'b': 2}, {'c': 3, 'a': 1}])
>>> index_dp = dp.add_index("order")
>>> list(index_dp)
[{'a': 1, 'b': 2, 'order': 0}, {'c': 3, 'a': 1, 'order': 1}]