code: def main(args):
      """
      Train and save the DQN model, for the cartpole problem
  
      :param args: (ArgumentParser) the input arguments
      """
      env = gym.make("CartPole-v0")
      model = DQN(
          env=env,
          policy=MlpPolicy,
          learning_rate=1e-3,
          buffer_size=50000,
          exploration_fraction=0.1,
          exploration_final_eps=0.02,
      )
      model.learn(total_timesteps=args.max_timesteps, callback=callback)
  
      print("Saving model to cartpole_model.zip")
      model.save("cartpole_model.zip")
  
imports: import argparse
  import gym
  import numpy
  from stable_baselines.deepq import DQN, MlpPolicy
label_desc: Use image node_id 2 for calling a global function with example usage: main(args) without return types