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cartpole_test.py
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cartpole_test.py
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import gym
import numpy as np
from models import load_model
from model_path import best_path
steps = 200
env = gym.make("CartPole-v0")
model = load_model(best_path)
print("ランダムに行動させる確立を入力してください。(0~100)")
while True:
epsilon = input()
if epsilon.isdecimal():
print("{}%の確率でランダムに行動します。".format(int(epsilon)))
epsilon = min(100, max(0, int(epsilon)))
epsilon /= 100
break
else:
print("入力が正しくありません。")
episode = 0
while True:
obs = env.reset()
for t in range(steps):
env.render()
if np.random.rand() < epsilon:
action = env.action_space.sample()
else:
bs = obs.reshape((1, *obs.shape))
action = np.argmax(model.predict(obs))
obs, reward, done, info = env.step(action)
if done:
print("Episode-{}: {}steps".format(episode, t))
break
episode += 1