def _parse_args()

in tensorflow_2_managed_spot_training_checkpointing/mnist.py [0:0]

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

def _parse_args():
    parser = argparse.ArgumentParser()

    # Data, model, and output directories
    # model_dir is always passed in from SageMaker. By default this is a S3 path under the default bucket.
    parser.add_argument('--model_dir', type=str)
    parser.add_argument('--sm-model-dir', type=str, default=os.environ.get('SM_MODEL_DIR'))
    parser.add_argument('--train', type=str, default=os.environ.get('SM_CHANNEL_TRAINING'))
    parser.add_argument('--hosts', type=list, default=json.loads(os.environ.get('SM_HOSTS')))
    parser.add_argument('--current-host', type=str, default=os.environ.get('SM_CURRENT_HOST'))
    parser.add_argument('--epochs',type=int,default=10,help='The number of steps to use for training.')
    parser.add_argument("--checkpoint-path",type=str,default="/opt/ml/checkpoints",help="Path where checkpoints will be saved.")

    return parser.parse_known_args()