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)

StreamReader

class torchdata.datapipes.iter.StreamReader(datapipe, chunk=None)

Given IO streams and their label names, yield bytes with label name as tuple.

(functional name: read_from_stream).

Parameters:

• datapipe – Iterable DataPipe provides label/URL and byte stream

• chunk – Number of bytes to be read from stream per iteration. If None, all bytes will be read until the EOF.

Example

>>> # xdoctest: +SKIP
>>> from torchdata.datapipes.iter import IterableWrapper, StreamReader
>>> from io import StringIO
>>> dp = IterableWrapper([("alphabet", StringIO("abcde"))])
>>> list(StreamReader(dp, chunk=1))
[('alphabet', 'a'), ('alphabet', 'b'), ('alphabet', 'c'), ('alphabet', 'd'), ('alphabet', 'e')]