def METHOD_NAME():
    parser = argparse.ArgumentParser()
    parser.add_argument(
        "--perf_type",
        default="pd",
        type=str,
        choices=["pd", "pd_faster_fp32", "pd_faster_fp16", "hf"],
        help="The type of perf.  ",
    )
    parser.add_argument(
        "--model_name_or_path",
        default="Salesforce/codegen-350M-mono",
        type=str,
        choices=[
            "Salesforce/codegen-350M-mono",
            "Salesforce/codegen-2B-mono",
            "Salesforce/codegen-6B-mono",
            "Salesforce/codegen-16B-mono",
        ],
        help="The model name to specify the bart to use.  ",
    )
    parser.add_argument("--top_k", default=4, type=int, help="The number of candidate to procedure topk sampling. ")
    parser.add_argument(
        "--top_p", default=1.0, type=float, help="The probability threshold to procedure topp sampling. "
    )
    parser.add_argument("--batch_size", default=1, type=int, help="The size of input batch. ")
    parser.add_argument("--input_len", default=60, type=int, help="The size of model input. ")
    parser.add_argument("--generate_len", default=20, type=int, help="Length of output . ")
    parser.add_argument("--gpu_id", default=2, type=int, help="The id of GPU . ")
    parser.add_argument(
        "--use_faster", action="store_true", help="Whether to process inference using faster codegen. "
    )
    parser.add_argument("--use_fp16_decoding", action="store_true", help="Whether to use fp16 decoding to predict. ")
    args = parser.METHOD_NAME()
    return args