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)

ZipperLongest

class torchdata.datapipes.iter.ZipperLongest(*datapipes: IterDataPipe, fill_value: Optional[Any] = None)

Aggregates elements into a tuple from each of the input DataPipes (functional name: zip_longest). The output is stopped until all input DataPipes are exhausted. If any input DataPipe is exhausted, missing values are filled-in with fill_value (default value is None).

Parameters:

• *datapipes – Iterable DataPipes being aggregated

• *fill_value – Value that user input to fill in the missing values from DataPipe. Default value is None.

Example

>>> from torchdata.datapipes.iter import IterableWrapper
>>> dp1, dp2, dp3 = IterableWrapper(range(3)), IterableWrapper(range(10, 15)), IterableWrapper(range(20, 25))
>>> list(dp1.zip_longest(dp2, dp3))
[(0, 10, 20), (1, 11, 21), (2, 12, 22), (None, 13, 23), (None, 14, 24)]
>>> list(dp1.zip_longest(dp2, dp3, -1))
[(0, 10, 20), (1, 11, 21), (2, 12, 22), (-1, 13, 23), (-1, 14, 24)]