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)

FileOpener

class torchdata.datapipes.iter.FileOpener(datapipe: Iterable[str], mode: str = 'r', encoding: Optional[str] = None, length: int = - 1)

Given pathnames, opens files and yield pathname and file stream in a tuple (functional name: open_files).

Parameters:

• datapipe – Iterable datapipe that provides pathnames

• mode – An optional string that specifies the mode in which the file is opened by open(). It defaults to r, other options are b for reading in binary mode and t for text mode.

• encoding – An optional string that specifies the encoding of the underlying file. It defaults to None to match the default encoding of open.

• length – Nominal length of the datapipe

Note

The opened file handles will be closed by Python’s GC periodically. Users can choose to close them explicitly.

Example

>>> # xdoctest: +SKIP
>>> from torchdata.datapipes.iter import FileLister, FileOpener, StreamReader
>>> dp = FileLister(root=".").filter(lambda fname: fname.endswith('.txt'))
>>> dp = FileOpener(dp)
>>> dp = StreamReader(dp)
>>> list(dp)
[('./abc.txt', 'abc')]