code: def main():
      
      parser = argparse.ArgumentParser()
      parser.add_argument('--batch_size', type=int, default=64)
      parser.add_argument('--image_path', type=str, default='./data/datasets/')
      parser.add_argument('--align_path', type=str, default='./data/align/')
      parser.add_argument('--num_gpus', type=int, default=1)
      parser.add_argument('--num_workers', type=int, default=0)
      parser.add_argument('--data_type', type=str, default='valid')
      parser.add_argument('--model_path', type=str, default=None)
      config = parser.parse_args()
      trainer = Train(config)
      trainer.build_model(path=config.model_path)
      trainer.load_dataloader()
  
      if config.data_type == 'train':
          data_loader = trainer.train_dataloader
      elif config.data_type == 'valid':
          data_loader = trainer.valid_dataloader
  
      trainer.infer_batch(data_loader)
docs: Description : run lipnet training code using argument info