    def extract_content_features(self, wavs):
        """extract content features from a batch of dataloader
        Args:
            wavs: tensor (batch_size, T)
        """
        # wavs: (batch, max_len)
        wavs = whisper.pad_or_trim(wavs)
        # batch_mel: (batch, 80, 3000)
        batch_mel = whisper.log_mel_spectrogram(wavs, device=self.model.device)
        with torch.no_grad():
            # (batch, 1500, 1024)
            features = self.model.embed_audio(batch_mel)
        return features
extract content features from a batch of dataloader
Args:
wavs: tensor (batch_size, T)
processors/content_extractor.py