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Fix flash_attention.py: wrong argument passing for attn_implementation #41347

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Merged
merged 4 commits into from
Oct 6, 2025
Merged

Fix flash_attention.py: wrong argument passing for attn_implementation #41347

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c272d01
Fix flash_attention.py: wrong argument passing for attn_implementation
TKONIY Oct 4, 2025
c9071b7
modify the kwargs inside _flash_attention_forward
TKONIY Oct 6, 2025
849acdd
fix the doc
TKONIY Oct 6, 2025
2af089d
fix typo
Cyrilvallez Oct 6, 2025
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6 changes: 3 additions & 3 deletions src/transformers/modeling_flash_attention_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -545,7 +545,7 @@ def _flash_attention_forward(
max_length_q: Optional[int] = None,
max_length_k: Optional[int] = None,
target_dtype: Optional[torch.dtype] = None,
implementation: Optional[str] = None,
attn_implementation: Optional[str] = None,
**kwargs,
):
"""
Expand All @@ -564,11 +564,11 @@ def _flash_attention_forward(
attention_mask (`torch.Tensor`, *optional*):
The padding mask - corresponds to a tensor of size `(batch_size, seq_len)` where 0 stands for the
position of padding tokens and 1 for the position of non-padding tokens.
implementation (`str`, *optional*):
attn_implementation (`str`, *optional*):
The attention implementation to use. If None, will default to the one based on the environment.
"""
(flash_fn, flash_varlen_fn, pad_fn, unpad_fn), process_flash_kwargs_fn = lazy_import_flash_attention(
implementation
attn_implementation
)

# PEFT possibly silently casts tensors to fp32, this potentially reconverts to correct dtype or is a no op
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