code: def get_args():
      parser = argparse.ArgumentParser()
  
      parser.add_argument(
          "--cluster_address",
          default="localhost:8010",
          type=str,
          help="cluster address of xparl.",
      )
      parser.add_argument(
          "--actor_num",
          type=int,
          required=True,
          help="number of actors.",
      )
      parser.add_argument(
          "--logdir",
          type=str,
          default="logdir",
          help="directory to save model/tensorboard data",
      )
  
      parser.add_argument(
          "--difficulty",
          type=int,
          required=True,
          help="difficulty of L2M2019Env. difficulty=1 means Round 1 environment but target theta is always 0; difficulty=2 menas Round 1 environment; difficulty=3 means Round 2 environment.",
      )
      parser.add_argument(
          "--vel_penalty_coeff",
          type=float,
          default=1.0,
          help="coefficient of velocity penalty in reward shaping.",
      )
      parser.add_argument(
          "--muscle_penalty_coeff",
          type=float,
          default=1.0,
          help="coefficient of muscle penalty in reward shaping.",
      )
      parser.add_argument(
          "--penalty_coeff",
          type=float,
          default=1.0,
          help="coefficient of all penalty in reward shaping.",
      )
      parser.add_argument(
          "--only_first_target",
          action="store_true",
          help="if set, will terminate the environment run after the first target finished.",
      )
  
      parser.add_argument(
          "--rpm_size",
          type=lambda x: int(float(x)),
          default=int(2e6),
          help="size of replay memory.",
      )
      parser.add_argument(
          "--train_times",
          type=int,
          default=100,
          help="training times (batches) when finishing an episode.",
      )
      parser.add_argument(
          "--restore_model_path",
          type=str,
          help="restore model path for warm start",
      )
      parser.add_argument(
          "--restore_rpm_path",
          type=str,
          help="restore rpm path for warm start",
      )
      parser.add_argument(
          "--warm_start_batchs",
          type=int,
          default=2000,
          help="collect how many batch data to warm start",
      )
  
      args = parser.parse_args()
  
      return args
  
label_desc: Use image node_id 1 for calling a global function with example usage: get_args() and returns: args