salohiddin94
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Update README.md
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README.md
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```python
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from stable_baselines3 import
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...
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```
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```python
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from stable_baselines3.common.vec_env import DummyVecEnv, VecNormalize
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# Load the saved statistics
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eval_env = DummyVecEnv([lambda: gym.make("PandaReachDense-v3")])
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eval_env = VecNormalize.load("vec_normalize.pkl", eval_env)
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# We need to override the render_mode
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eval_env.render_mode = "rgb_array"
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# do not update them at test time
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eval_env.training = False
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# reward normalization is not needed at test time
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eval_env.norm_reward = False
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# Load the agent
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model = A2C.load("a2c-PandaReachDense-v3")
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mean_reward, std_reward = evaluate_policy(model, eval_env)
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print(f"Mean reward = {mean_reward:.2f} +/- {std_reward:.2f}")
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...
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```
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