stable-baselines3/torchy_baselines/common/evaluation.py
2019-09-06 10:44:55 +02:00

21 lines
589 B
Python

import numpy as np
def evaluate_policy(model, env, n_eval_episodes=10, deterministic=True, render=False):
"""
Runs policy for n episodes and returns average reward
"""
mean_reward = 0.0
for _ in range(n_eval_episodes):
obs = env.reset()
done = False
while not done:
action = model.predict(np.array(obs), deterministic=deterministic)
obs, reward, done, _ = env.step(action)
mean_reward += reward
if render:
env.render()
mean_reward /= n_eval_episodes
return mean_reward