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transformers - ✅(Solved) Fix Wrong docstring for position_ids [2 pull requests, 3 comments, 4 participants]

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huggingface/transformers#44373•Fetched 2026-04-08 00:28:53
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Fix Action

Fixed

PR fix notes

PR #44547: Fix position_ids docstring in modeling_flash_attention_utils.py

Description (problem / solution / changelog)

Fixes #44373

Summary

  • Corrected the docstring for position_ids parameter in prepare_fa_kwargs_from_position_ids and _prepare_from_posids which incorrectly described attention mask semantics ("Boolean or int tensor... 1 means valid and 0 means not valid")
  • The docstring now accurately describes position indices behavior

Testing

  • Docstring-only change, no code behavior affected

This contribution was developed with AI assistance (Claude Code).

Changed files

  • src/transformers/modeling_flash_attention_utils.py (modified, +2/-2)

PR #44590: Fix incorrect docstring for position_ids

Description (problem / solution / changelog)

Fixes incorrect documentation for position_ids in masking_utils.py.

The docstring previously described position_ids as torch.Tensor.
This PR updates it to torch.LongTensor and aligns the description with the standard wording used across the Transformers codebase.

Fixes #44373

What does this PR do?

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Fixes # (issue)

Before submitting

  • This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
  • Did you read the contributor guideline, Pull Request section?
  • Was this discussed/approved via a Github issue or the forum? Please add a link to it if that's the case.
  • Did you make sure to update the documentation with your changes? Here are the documentation guidelines, and here are tips on formatting docstrings.
  • Did you write any new necessary tests?

Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR.

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Changed files

  • src/transformers/masking_utils.py (modified, +2/-2)
RAW_BUFFERClick to expand / collapse

System Info

latest commit, see link below

Who can help?

@stevhliu

Information

  • The official example scripts
  • My own modified scripts

Tasks

  • An officially supported task in the examples folder (such as GLUE/SQuAD, ...)
  • My own task or dataset (give details below)

Reproduction

Wrong docstring:

https://github.com/huggingface/transformers/blob/11b1906d5c0dae39c13270e47cc02c4cde70e548/src/transformers/modeling_flash_attention_utils.py#L359-L360

https://github.com/huggingface/transformers/blob/11b1906d5c0dae39c13270e47cc02c4cde70e548/src/transformers/modeling_flash_attention_utils.py#L412-L413

The docstring is for attention_mask, not position_ids

https://github.com/huggingface/transformers/blob/11b1906d5c0dae39c13270e47cc02c4cde70e548/src/transformers/modeling_flash_attention_utils.py#L201

Expected behavior

Expected docstring:

https://github.com/huggingface/transformers/blob/11b1906d5c0dae39c13270e47cc02c4cde70e548/src/transformers/models/layoutlmv2/modeling_layoutlmv2.py#L897-L901

or

https://github.com/huggingface/transformers/blob/11b1906d5c0dae39c13270e47cc02c4cde70e548/src/transformers/masking_utils.py#L715-L716

extent analysis

Fix Plan

Fix Name

Update docstring for attention_mask and position_ids in modeling_flash_attention_utils.py

Steps

1. Update docstring for attention_mask

def attention_mask(input_ids: torch.Tensor, attention_mask: torch.Tensor) -> torch.Tensor:
    """
    Compute the masked attention weights.

    Args:
        input_ids (torch.Tensor): The input token ids.
        attention_mask (torch.Tensor): The attention mask.

    Returns:
        torch.Tensor: The masked attention weights.
    """

2. Update docstring for position_ids

def position_ids_from_input_ids(input_ids: torch.Tensor) -> torch.Tensor:
    """
    Create position ids from input ids.

    Args:
        input_ids (torch.Tensor): The input token ids.

    Returns:
        torch.Tensor: The position ids.
    """

3. Update the docstring for the attention_mask parameter in the attention_mask function

def attention_mask(input_ids: torch.Tensor, attention_mask: torch.Tensor) -> torch.Tensor:
    """
    Compute the masked attention weights.

    Args:
        input_ids (torch.Tensor): The input token ids.
        attention_mask (torch.Tensor): The attention mask to be used in the attention mechanism.

    Returns:
        torch.Tensor: The masked attention weights.
    """

4. Update the docstring for the position_ids parameter in the position_ids_from_input_ids function

def position_ids_from_input_ids(input_ids: torch.Tensor) -> torch.Tensor:
    """
    Create position ids from input ids.

    Args:
        input_ids (torch.Tensor): The input token ids.

    Returns:
        torch.Tensor: The position ids.
    """

Verification

  • Run python setup.py to rebuild the documentation.
  • Verify that the updated docstrings are

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