code: def main():
      parser = argparse.ArgumentParser()
      parser.add_argument(
          "--num_episodes",
          type=int,
          default=10,
          help="num episodes to evaluate",
      )
      parser.add_argument(
          "--env_dir",
          default=None,
          help="directory path of the environment",
      )
  
      args = parser.parse_args()
      if args.env_dir:
          grid2op.change_local_dir(args.env_dir)
  
      evaluator = Evaluator()
      mean_steps, mean_rewards = evaluator.run(args.num_episodes)
      print(
          "num_episodes: {}, mean_reward: {:.1f}, mean_steps: {:.1f}".format(
              args.num_episodes, mean_rewards, mean_steps
          )
      )
  
file_path: PARL/examples/NeurIPS2020-Learning-to-Run-a-Power-Network-Challenge/track1/evaluate.py
imports: import grid2op
  import lightsim2grid
  from lightsim2grid.LightSimBackend import LightSimBackend
  import numpy
  from agent import Track1PowerNetAgent
  import argparse
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types