code: def main():
      logger.configure()
      env = make_atari("PongNoFrameskip-v4")
      env = bench.Monitor(env, logger.get_dir())
      env = deepq.wrap_atari_dqn(env)
  
      model = deepq.learn(
          env,
          "conv_only",
          convs=[(32, 8, 4), (64, 4, 2), (64, 3, 1)],
          hiddens=[256],
          dueling=True,
          lr=1e-4,
          total_timesteps=int(1e7),
          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,
      )
  
      model.save("pong_model.pkl")
      env.close()
  
imports: from baselines import deepq
  from baselines import bench
  from baselines import logger
  from baselines.common.atari_wrappers import make_atari
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types