code: def main():
      """
      Run the atari test
      """
      parser = argparse.ArgumentParser(
          formatter_class=argparse.ArgumentDefaultsHelpFormatter
      )
      parser.add_argument(
          "--env",
          help="environment ID",
          default="BreakoutNoFrameskip-v4",
      )
      parser.add_argument(
          "--seed", help="RNG seed", type=int, default=0
      )
      parser.add_argument("--prioritized", type=int, default=1)
      parser.add_argument("--dueling", type=int, default=1)
      parser.add_argument(
          "--prioritized-replay-alpha", type=float, default=0.6
      )
      parser.add_argument(
          "--num-timesteps", type=int, default=int(10e6)
      )
  
      args = parser.parse_args()
      logger.configure()
      set_global_seeds(args.seed)
      env = make_atari(args.env)
      env = bench.Monitor(env, logger.get_dir())
      env = wrap_atari_dqn(env)
      policy = partial(CnnPolicy, dueling=args.dueling == 1)
  
      model = DQN(
          env=env,
          policy=policy,
          learning_rate=1e-4,
          buffer_size=10000,
          exploration_fraction=0.1,
          exploration_final_eps=0.01,
          train_freq=4,
          learning_starts=10000,
          target_network_update_freq=1000,
          gamma=0.99,
          prioritized_replay=bool(args.prioritized),
          prioritized_replay_alpha=args.prioritized_replay_alpha,
      )
      model.learn(total_timesteps=args.num_timesteps)
  
      env.close()
  
imports: import argparse
  from functools import partial
  from stable_baselines import bench, logger
  from stable_baselines.common import set_global_seeds
  from stable_baselines.common.atari_wrappers import make_atari
  from stable_baselines.deepq import DQN, wrap_atari_dqn, CnnPolicy
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types