def METHOD_NAME():
    parser = argparse.ArgumentParser(
        description="Quantize using K-means clustering over acoustic features."
    )
    parser.add_argument(
        "--feature_type",
        type=str,
        choices=["logmel", "hubert", "w2v2", "cpc"],
        default=None,
        required=True,
        help="Acoustic feature type",
    )
    parser.add_argument(
        "--acoustic_model_path",
        type=str,
        help="Pretrained acoustic model checkpoint"
    )
    parser.add_argument(
        "--layer",
        type=int,
        help="The layer of the pretrained model to extract features from",
        default=-1,
    )
    parser.add_argument(
        "--kmeans_model_path",
        type=str,
        required=True,
        help="K-means model file path to use for inference",
    )
    parser.add_argument(
        "--features_path",
        type=str,
        default=None,
        help="Features file path. You don't need to enter acoustic model details if you have dumped features",
    )
    parser.add_argument(
        "--manifest_path",
        type=str,
        default=None,
        help="Manifest file containing the root dir and file names",
    )
    parser.add_argument(
        "--out_quantized_file_path",
        required=True,
        type=str,
        help="File path of quantized output.",
    )
    parser.add_argument(
        "--extension", type=str, default=".flac", help="Features file path"
    )
    parser.add_argument(
        "--channel_id",
        choices=['1', '2'],
        help="The audio channel to extract the units in case of stereo file.",
        default=None,
    )
    parser.add_argument(
        "--hide-fname", action='store_true',
        help="Hide file names in the output file."
    )
    return parser