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https://github.com/saymrwulf/stable-baselines3.git
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22 lines
625 B
Python
22 lines
625 B
Python
import numpy as np
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def evaluate_policy(model, env, n_eval_episodes=10, deterministic=True, render=False):
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"""
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Runs policy for n episodes and returns average reward
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"""
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mean_reward, n_steps = 0.0, 0
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for _ in range(n_eval_episodes):
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obs = env.reset()
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done = False
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while not done:
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action = model.predict(obs, deterministic=deterministic)
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obs, reward, done, _ = env.step(action)
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mean_reward += reward
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n_steps += 1
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if render:
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env.render()
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mean_reward /= n_eval_episodes
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return mean_reward, n_steps
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