text: 
  import warnings
  warnings.filterwarnings("ignore")
  import os
  os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
  
  import gym
  from stable_baselines.deepq import DQN
  
  env_id = "CartPole-v1"
  env = gym.make(env_id)
  model = DQN('MlpPolicy', env, learning_rate=1e-4, verbose=1)#, tensorboard_log="MLP/")
  #model.learn(int(2e5))
  #model.save('../result/model/dqn_cartpole_2e5.pkl')
  model = model.load('../result/model/dqn_cartpole_10e5.pkl')
  
  env = gym.make(env_id)
  obs = env.reset()
  
  for _ in range(10000):
      env.render()
      action, _states = model.predict(obs)
      obs, rewards, dones, info = env.step(action)
  env.close()
  
  