def METHOD_NAME():
    parser = argparse.ArgumentParser()
    parser.add_argument("--msmarco_train_input_filepath", default=None, type=str, required=True)
    parser.add_argument("--msmarco_dev_input_filepath", default=None, type=str, required=True)
    parser.add_argument("--converted_train_save_path", default=None, type=str, required=True)
    parser.add_argument("--converted_dev_save_path", default=None, type=str, required=True)
    parser.add_argument(
        "--exclude_negative_samples",
        default=False,
        type=bool,
        help="whether to keep No Answer samples in the dataset",
        required=False,
    )
    parser.add_argument(
        "--keep_only_relevant_passages",
        default=False,
        type=bool,
        help="if True, will only use passages with is_selected=True for context",
        required=False,
    )
    args = parser.parse_args()
    print("converting MS-MARCO train dataset...")
    msmarco_train_data = load_json(args.msmarco_train_input_filepath)
    squad_train_data = convert_msmarco_to_squad_format(msmarco_train_data, args)
    dump_json(args.converted_train_save_path, squad_train_data)
    print("converting MS-MARCO dev dataset...")
    msmarco_dev_data = load_json(args.msmarco_dev_input_filepath)
    squad_dev_data = convert_msmarco_to_squad_format(msmarco_dev_data, args)
    dump_json(args.converted_dev_save_path, squad_dev_data)