def METHOD_NAME():
    # parse args and config and redirect to train_sp
    parser = argparse.ArgumentParser(
        description="Synthesize with transformer tts & waveflow.")
    parser.add_argument(
        "--transformer-tts-config",
        type=str,
        help="transformer tts config file.")
    parser.add_argument(
        "--transformer-tts-checkpoint",
        type=str,
        help="transformer tts checkpoint to load.")
    parser.add_argument(
        "--transformer-tts-stat",
        type=str,
        help="mean and standard deviation used to normalize spectrogram when training transformer tts."
    )
    parser.add_argument(
        "--waveflow-config", type=str, help="waveflow config file.")
    # not normalize when training waveflow
    parser.add_argument(
        "--waveflow-checkpoint", type=str, help="waveflow checkpoint to load.")
    parser.add_argument(
        "--phones-dict",
        type=str,
        default="phone_id_map.txt",
        help="phone vocabulary file.")
    parser.add_argument(
        "--text",
        type=str,
        help="text to synthesize, a 'utt_id sentence' pair per line.")
    parser.add_argument("--output-dir", type=str, help="output dir.")
    parser.add_argument(
        "--ngpu", type=int, default=1, help="if ngpu == 0, use cpu.")
    args = parser.parse_args()
    if args.ngpu == 0:
        paddle.set_device("cpu")
    elif args.ngpu > 0:
        paddle.set_device("gpu")
    else:
        print("ngpu should >= 0 !")
    with open(args.transformer_tts_config) as f:
        transformer_tts_config = CfgNode(yaml.safe_load(f))
    with open(args.waveflow_config) as f:
        waveflow_config = CfgNode(yaml.safe_load(f))
    print("========Args========")
    print(yaml.safe_dump(vars(args)))
    print("========Config========")
    print(transformer_tts_config)
    print(waveflow_config)
    evaluate(args, transformer_tts_config, waveflow_config)