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Fix UnboundLocalError in invert_attention_mask by adding proper shape… #45247

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Fix UnboundLocalError in invert_attention_mask by adding proper shape… #45247

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Fix UnboundLocalError in invert_attention_mask by adding proper shape…
Apr 5, 2026
f7d9c23
code formatting and linting
Apr 5, 2026
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4 changes: 3 additions & 1 deletion src/transformers/modeling_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -867,8 +867,10 @@ def invert_attention_mask(self, encoder_attention_mask: Tensor) -> Tensor:
"""
if encoder_attention_mask.dim() == 3:
encoder_extended_attention_mask = encoder_attention_mask[:, None, :, :]
if encoder_attention_mask.dim() == 2:
elif encoder_attention_mask.dim() == 2:
encoder_extended_attention_mask = encoder_attention_mask[:, None, None, :]
else:
raise ValueError(f"Wrong shape for encoder_attention_mask (shape {encoder_attention_mask.shape})")
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@vasqu vasqu Apr 9, 2026

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Yea. we try to remove these tbh - see #43924 (I really should get back to that PR). So I honestly don't want to add extra logic that may result in other issues

# T5 has a mask that can compare sequence ids, we can simulate this here with this transposition
# encoder_extended_attention_mask = (encoder_extended_attention_mask ==
# encoder_extended_attention_mask.transpose(-1, -2))
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