def parse_args()

in test.py [0:0]

• 25 lines of code
• 2 McCabe index (conditional complexity)

def parse_args():
    parser = argparse.ArgumentParser(
        description='test/eval a model')
    parser.add_argument('--config', type=str, help='test config file path')
    parser.add_argument('--checkpoint', help='checkpoint file')
    parser.add_argument('--aug-test', action='store_true', help='Use Flip and Multi scale aug')
    parser.add_argument('--out', help='output result file in pickle format')
    parser.add_argument('--format-only', action='store_true', help='Format the output results without perform evaluation. It is'
                                                                        'useful when you want to format the result to a specific format and '
                                                                        'submit it to the test server')
    parser.add_argument('--eval', type=str, nargs='+', help='evaluation metrics, which depends on the dataset, e.g., "mIoU"'
                                                                ' for generic datasets, and "cityscapes" for Cityscapes')
    parser.add_argument('--show', action='store_true', help='show results')
    parser.add_argument('--show-dir', help='directory where painted images will be saved')
    parser.add_argument('--gpu-collect', action='store_true', help='whether to use gpu to collect results.')
    parser.add_argument('--tmpdir', help='tmp directory used for collecting results from multiple '
                                            'workers, available when gpu_collect is not specified')
    parser.add_argument('--options', nargs='+', action=DictAction, help='custom options')
    parser.add_argument('--eval-options', nargs='+', action=DictAction, help='custom options for evaluation')
    parser.add_argument('--launcher', choices=['none', 'pytorch', 'slurm', 'mpi'], default='none', help='job launcher')
    parser.add_argument('--local_rank', type=int, default=0)
    args = parser.parse_args()
    if 'LOCAL_RANK' not in os.environ:
        os.environ['LOCAL_RANK'] = str(args.local_rank)
    return args