CartPole_ppo.py

from stable_baselines3 import PPO                                                       
import gym                                                                              
                                                                                        
env = gym.make("CartPole-v1")                                                           
                                                                                        
model = PPO(policy = "MlpPolicy",env =  env, verbose=1)                                 
model.learn(total_timesteps=25000)                                                      
                                                                                        
model.save("ppo_cartpole")  # saving the model to ppo_cartpole.zip                      
model = PPO.load("ppo_cartpole")  # loading the model from ppo_cartpole.zip             
                                                                                        
obs = env.reset()                                                                       
for i in range(1000):                                                                   
    action, _state = model.predict(obs, deterministic=True)                             
    obs, reward, done, info = env.step(action)                                          
    env.render()                                                                        
    if done:                                                                            
      obs = env.reset()