    def extract_content_features(self, wavs):
        """extract content features from a batch of dataloader
        Args:
            wavs: tensor (batch, T)
        """
        device = next(self.model.parameters()).device
        wavs = wavs.to(device)  # (batch, max_len)
        padding_mask = torch.eq(wavs, torch.zeros_like(wavs)).to(device)
        with torch.no_grad():
            logits = self.model.extract_features(
                source=wavs, padding_mask=padding_mask, output_layer=12
            )
            # feats: (batch, T, 256)
            feats = self.model.final_proj(logits[0])
        return feats
extract content features from a batch of dataloader
Args:
wavs: tensor (batch, T)
processors/content_extractor.py