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[Parakeet] add output_attention_mask #41694

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Merged
eustlb merged 2 commits into from
Oct 23, 2025
Merged

[Parakeet] add output_attention_mask #41694

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2a691c3
add output_attention_mask
eustlb Oct 17, 2025
9838b35
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eustlb Oct 23, 2025
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22 changes: 19 additions & 3 deletions src/transformers/models/parakeet/modeling_parakeet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -37,6 +37,16 @@
from .configuration_parakeet import ParakeetCTCConfig, ParakeetEncoderConfig


@dataclass
@auto_docstring(
custom_intro="""
Extends [~modeling_outputs.BaseModelOutput] to include the output attention mask since sequence length is not preserved in the model's forward.
"""
)
class ParakeetEncoderModelOutput(BaseModelOutput):
attention_mask: Optional[torch.Tensor] = None


class ParakeetEncoderRelPositionalEncoding(nn.Module):
"""Relative positional encoding for Parakeet."""

Expand Down Expand Up @@ -513,9 +523,13 @@ def forward(
self,
input_features: torch.Tensor,
attention_mask: Optional[torch.Tensor] = None,
output_attention_mask: Optional[bool] = None,
**kwargs: Unpack[TransformersKwargs],
) -> BaseModelOutput:
r"""
output_attention_mask (`bool`, *optional*):
Whether to return the output attention mask.

Example:

```python
Expand Down Expand Up @@ -546,8 +560,8 @@ def forward(
)

if attention_mask is not None:
attention_mask = self._get_output_attention_mask(attention_mask, target_length=hidden_states.shape[1])
attention_mask = attention_mask.unsqueeze(1).expand(-1, hidden_states.shape[1], -1)
output_mask = self._get_output_attention_mask(attention_mask, target_length=hidden_states.shape[1])
attention_mask = output_mask.unsqueeze(1).expand(-1, hidden_states.shape[1], -1)
attention_mask = attention_mask & attention_mask.transpose(1, 2)
attention_mask = attention_mask.unsqueeze(1)

Expand All @@ -567,7 +581,9 @@ def forward(
**kwargs,
)

return BaseModelOutput(last_hidden_state=hidden_states)
return ParakeetEncoderModelOutput(
last_hidden_state=hidden_states, attention_mask=output_mask.int() if output_attention_mask else None
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@nithinraok nithinraok Oct 17, 2025

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can we return lengths directly instead or along with attention_mask

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@eustlb eustlb Oct 20, 2025

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I'd rather keep an explicit approach here for potiential future usage of the same with left padding, you can retreive lengths by doing attention_mask.sum(-1)

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@nithinraok nithinraok Oct 21, 2025

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sounds good.

)


@dataclass
Expand Down
22 changes: 19 additions & 3 deletions src/transformers/models/parakeet/modular_parakeet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -34,6 +34,16 @@
from .configuration_parakeet import ParakeetCTCConfig, ParakeetEncoderConfig


@dataclass
@auto_docstring(
custom_intro="""
Extends [~modeling_outputs.BaseModelOutput] to include the output attention mask since sequence length is not preserved in the model's forward.
"""
)
class ParakeetEncoderModelOutput(BaseModelOutput):
attention_mask: Optional[torch.Tensor] = None


class ParakeetEncoderRelPositionalEncoding(nn.Module):
"""Relative positional encoding for Parakeet."""

Expand Down Expand Up @@ -399,9 +409,13 @@ def forward(
self,
input_features: torch.Tensor,
attention_mask: Optional[torch.Tensor] = None,
output_attention_mask: Optional[bool] = None,
**kwargs: Unpack[TransformersKwargs],
) -> BaseModelOutput:
r"""
output_attention_mask (`bool`, *optional*):
Whether to return the output attention mask.

Example:

```python
Expand Down Expand Up @@ -432,8 +446,8 @@ def forward(
)

if attention_mask is not None:
attention_mask = self._get_output_attention_mask(attention_mask, target_length=hidden_states.shape[1])
attention_mask = attention_mask.unsqueeze(1).expand(-1, hidden_states.shape[1], -1)
output_mask = self._get_output_attention_mask(attention_mask, target_length=hidden_states.shape[1])
attention_mask = output_mask.unsqueeze(1).expand(-1, hidden_states.shape[1], -1)
attention_mask = attention_mask & attention_mask.transpose(1, 2)
attention_mask = attention_mask.unsqueeze(1)

Expand All @@ -453,7 +467,9 @@ def forward(
**kwargs,
)

return BaseModelOutput(last_hidden_state=hidden_states)
return ParakeetEncoderModelOutput(
last_hidden_state=hidden_states, attention_mask=output_mask.int() if output_attention_mask else None
)


@dataclass
Expand Down