def create_args()

in community-content/pytorch_efficient_training/resnet_ddp_wds.py [0:0]

• 50 lines of code
• 1 McCabe index (conditional complexity)

def create_args():
  """Create main args."""
  parser = argparse.ArgumentParser(
      formatter_class=argparse.ArgumentDefaultsHelpFormatter)
  parser.add_argument(
      '--gpus',
      default=4,
      type=int,
      help='number of gpus to use')
  parser.add_argument(
      '--epochs',
      default=1,
      type=int,
      help='number of total epochs to run')
  parser.add_argument(
      '--dataloader_num_workers',
      default=2,
      type=int,
      help='number of workders for dataloader')
  parser.add_argument(
      '--train_data_path',
      default='',
      type=str,
      help='path to training data')
  parser.add_argument(
      '--train_batch_size',
      default=32,
      type=int,
      help='batch size for training per gpu')
  parser.add_argument(
      '--train_data_size',
      default=50000,
      type=int,
      help='data size for training')
  parser.add_argument(
      '--eval_data_path',
      default='',
      type=str,
      help='path to evaluation data')
  parser.add_argument(
      '--eval_batch_size',
      default=32,
      type=int,
      help='batch size for evaluation per gpu')
  parser.add_argument(
      '--eval_data_size',
      default=50000,
      type=int,
      help='data size for evaluation')
  args = parser.parse_args()
  return args