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Make canine model exportable by removing unncessary complicated logic (#37124)

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Tugsbayasgalan Manlaibaatar 2025-04-01 07:31:12 -04:00 committed by GitHub
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commit c0bd8048a5
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1 changed files with 2 additions and 2 deletions
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src/transformers/models/canine/modeling_canine.py
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@ -1056,7 +1056,7 @@ class CanineModel(CaninePreTrainedModel):
return molecule_attention_mask
def _repeat_molecules(self, molecules: torch.Tensor, char_seq_length: torch.Tensor) -> torch.Tensor:
def _repeat_molecules(self, molecules: torch.Tensor, char_seq_length: int) -> torch.Tensor:
"""Repeats molecules to make them the same length as the char sequence."""
rate = self.config.downsampling_rate
@ -1070,7 +1070,7 @@ class CanineModel(CaninePreTrainedModel):
# n elements (n < `downsampling_rate`), i.e. the remainder of floor
# division. We do this by repeating the last molecule a few extra times.
last_molecule = molecules[:, -1:, :]
remainder_length = torch.fmod(torch.tensor(char_seq_length), torch.tensor(rate)).item()
remainder_length = char_seq_length % rate
remainder_repeated = torch.repeat_interleave(
last_molecule,
# +1 molecule to compensate for truncation.