def mel_filters()

in tensorrtllm/whisper_utils.py [0:0]

• 11 lines of code
• 2 McCabe index (conditional complexity)

def mel_filters(device,
                n_mels: int,
                mel_filters_dir: str = None) -> torch.Tensor:
    """
    load the mel filterbank matrix for projecting STFT into a Mel spectrogram.
    Allows decoupling librosa dependency; saved using:

        np.savez_compressed(
            "mel_filters.npz",
            mel_80=librosa.filters.mel(sr=16000, n_fft=400, n_mels=80),
        )
    """
    assert n_mels in {80, 128}, f"Unsupported n_mels: {n_mels}"
    if mel_filters_dir is None:
        mel_filters_path = os.path.join(os.path.dirname(__file__), "assets",
                                        "mel_filters.npz")
    else:
        mel_filters_path = os.path.join(mel_filters_dir, "mel_filters.npz")
    with np.load(mel_filters_path) as f:
        return torch.from_numpy(f[f"mel_{n_mels}"]).to(device)