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ada730a5b1
Python doesn't make it easy for libraries to take responsibility for logging configuration (which we do to make simple usage much easier), and as we see more Gym plugins, we want their loggers to have an appropriate log level too. So we may as well configure the root logger level.
73 lines
2.5 KiB
Python
73 lines
2.5 KiB
Python
import argparse
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import logging
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import os
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import sys
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import gym
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# The world's simplest agent!
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class RandomAgent(object):
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def __init__(self, action_space):
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self.action_space = action_space
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def act(self, observation, reward, done):
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return self.action_space.sample()
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(description=None)
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parser.add_argument('env_id', nargs='?', default='CartPole-v0', help='Select the environment to run')
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args = parser.parse_args()
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# Call `undo_logger_setup` if you want to undo Gym's logger setup
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# and configure things manually. (The default should be fine most
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# of the time.)
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gym.undo_logger_setup()
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logger = logging.getLogger()
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formatter = logging.Formatter('[%(asctime)s] %(message)s')
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handler = logging.StreamHandler(sys.stderr)
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handler.setFormatter(formatter)
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logger.addHandler(handler)
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# You can set the level to logging.DEBUG or logging.WARN if you
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# want to change the amount of output.
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logger.setLevel(logging.INFO)
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env = gym.make(args.env_id)
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# You provide the directory to write to (can be an existing
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# directory, including one with existing data -- all monitor files
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# will be namespaced). You can also dump to a tempdir if you'd
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# like: tempfile.mkdtemp().
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outdir = '/tmp/random-agent-results'
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env.monitor.start(outdir, force=True, seed=0)
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# This declaration must go *after* the monitor call, since the
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# monitor's seeding creates a new action_space instance with the
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# appropriate pseudorandom number generator.
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agent = RandomAgent(env.action_space)
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episode_count = 100
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max_steps = 200
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reward = 0
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done = False
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for i in range(episode_count):
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ob = env.reset()
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for j in range(max_steps):
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action = agent.act(ob, reward, done)
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ob, reward, done, _ = env.step(action)
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if done:
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break
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# Note there's no env.render() here. But the environment still can open window and
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# render if asked by env.monitor: it calls env.render('rgb_array') to record video.
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# Video is not recorded every episode, see capped_cubic_video_schedule for details.
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# Dump result info to disk
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env.monitor.close()
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# Upload to the scoreboard. We could also do this from another
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# process if we wanted.
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logger.info("Successfully ran RandomAgent. Now trying to upload results to the scoreboard. If it breaks, you can always just try re-uploading the same results.")
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gym.upload(outdir)
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