def METHOD_NAME():
    parser = argparse.ArgumentParser(description='Train a model')
    parser.add_argument('config', help='Train config file path')
    parser.add_argument('--work-dir', help='The dir to save logs and models')
    parser.add_argument(
        '--resume', action='store_true', help='Whether to resume checkpoint.')
    parser.add_argument(
        '--amp',
        action='store_true',
        default=False,
        help='Enable automatic-mixed-precision training')
    parser.add_argument(
        '--auto-scale-lr',
        action='store_true',
        help='Whether to scale the learning rate automatically. It requires '
        '`auto_scale_lr` in config, and `base_batch_size` in `auto_scale_lr`')
    parser.add_argument(
        '--cfg-options',
        nargs='+',
        action=DictAction,
        help='Override some settings in the used config, the key-value pair '
        'in xxx=yyy format will be merged into config file. If the value to '
        'be overwritten is a list, it should be like key="[a,b]" or key=a,b '
        'It also allows nested list/tuple values, e.g. key="[(a,b),(c,d)]" '
        'Note that the quotation marks are necessary and that no white space '
        'is allowed.')
    parser.add_argument(
        '--launcher',
        choices=['none', 'pytorch', 'slurm', 'mpi'],
        default='none',
        help='Job launcher')
    # When using PyTorch version >= 2.0.0, the `torch.distributed.launch`
    # will pass the `--local-rank` parameter to `tools/train.py` instead
    # of `--local_rank`.
    parser.add_argument('--local_rank', '--local-rank', type=int, default=0)
    args = parser.METHOD_NAME()
    if 'LOCAL_RANK' not in os.environ:
        os.environ['LOCAL_RANK'] = str(args.local_rank)
    return args