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53 lines
2.2 KiB
Python
53 lines
2.2 KiB
Python
#######################################################################
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# Copyright (C) 2017 Shangtong Zhang(zhangshangtong.cpp@gmail.com) #
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# Permission given to modify the code as long as you keep this #
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# declaration at the top #
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#######################################################################
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import numpy as np
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import pickle
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def run_episodes(agent):
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config = agent.config
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window_size = 100
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ep = 0
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rewards = []
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steps = []
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avg_test_rewards = []
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agent_type = agent.__class__.__name__
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while True:
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ep += 1
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reward, step = agent.episode()
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rewards.append(reward)
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steps.append(step)
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avg_reward = np.mean(rewards[-window_size:])
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config.logger.info('episode %d, reward %f, avg reward %f, total steps %d, episode step %d' % (
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ep, reward, avg_reward, agent.total_steps, step))
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if config.save_interval and ep % config.save_interval == 0:
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with open('data/%s-%s-online-stats-%s.bin' % (
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agent_type, config.tag, agent.task.name), 'wb') as f:
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pickle.dump([steps, rewards], f)
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if config.episode_limit and ep > config.episode_limit:
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break
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if config.test_interval and ep % config.test_interval == 0:
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config.logger.info('Testing...')
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agent.save('data/%s-%s-model-%s.bin' % (agent_type, config.tag, agent.task.name))
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test_rewards = []
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for _ in range(config.test_repetitions):
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test_rewards.append(agent.episode(True)[0])
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avg_reward = np.mean(test_rewards)
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avg_test_rewards.append(avg_reward)
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config.logger.info('Avg reward %f(%f)' % (
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avg_reward, np.std(test_rewards) / np.sqrt(config.test_repetitions)))
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with open('data/%s-%s-all-stats-%s.bin' % (agent_type, config.tag, agent.task.name), 'wb') as f:
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pickle.dump({'rewards': rewards,
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'steps': steps,
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'test_rewards': avg_test_rewards}, f)
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if avg_reward > agent.task.success_threshold:
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break
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return steps, rewards, avg_test_rewards |