Загрузка sendex модели

import gymnasium as gym
from stable_baselines3 import PPO

models_dir = "models/PPO"

from stable_baselines3.common.evaluation import evaluate_policy

env = gym.make("CartPole-v1")
env.reset()
model_path = f"{models_dir}/120000.zip"
model = PPO.load(model_path, env=env)

#model = PPO.load(model_path, env=env)

# Evaluate the trained agent
mean_reward, std_reward = evaluate_policy(model, env, n_eval_episodes=10, deterministic=True)

print(f"mean_reward={mean_reward:.2f} +/- {std_reward}")