4fed0beca64a52aa718371dc3b2cf1fd979197a4,fairseq/models/wav2vec/wav2vec2.py,Wav2Vec2Model,forward,#Wav2Vec2Model#Any#Any#Any#Any#,446

Before Change

        unmasked_features = features.clone()

        if padding_mask is not None:
            extra = padding_mask.size(1) % features.size(1)
            if extra > 0:
                padding_mask = padding_mask[:, :-extra]
            padding_mask = padding_mask.view(padding_mask.size(0), features.size(1), -1)
            padding_mask = padding_mask.all(-1)

After Change

        unmasked_features = features.clone()

        if padding_mask is not None:
            input_lengths = (1 - padding_mask.long()).sum(-1)
            // apply conv formula to get real output_lengths
            output_lengths = self._get_feat_extract_output_lengths(input_lengths)

            padding_mask = torch.zeros(
                features.shape[:2], dtype=features.dtype, device=features.device
            )

Instances