#!/usr/bin/env python # # Run all the tasks on a benchmark using a random agent. # # This script assumes you have set an OPENAI_GYM_API_KEY environment # variable. You can find your API key in the web interface: # https://gym.openai.com/settings/profile. # import argparse import logging import os import sys import gym # In modules, use `logger = logging.getLogger(__name__)` from gym import wrappers logger = logging.getLogger() def main(): parser = argparse.ArgumentParser(description=None) parser.add_argument('-b', '--benchmark-id', help='id of benchmark to run e.g. Atari7Ram-v0') parser.add_argument('-v', '--verbose', action='count', dest='verbosity', default=0, help='Set verbosity.') parser.add_argument('-t', '--training-dir', default="/tmp/gym-results/", help='What directory to upload.') args = parser.parse_args() if args.verbosity == 0: logger.setLevel(logging.INFO) elif args.verbosity >= 1: logger.setLevel(logging.DEBUG) benchmark_id = args.benchmark_id if benchmark_id is None: logger.info("Must supply a valid benchmark") return 1 try: benchmark = gym.benchmark_spec(benchmark_id) except Exception: logger.info("Invalid benchmark") return 1 # run benchmark tasks for task in benchmark.tasks: logger.info("Running on env: {}".format(task.env_id)) for trial in range(task.trials): env = gym.make(task.env_id) training_dir_name = "{}/{}-{}".format(args.training_dir, task.env_id, trial) env = wrappers.Monitor(training_dir_name)(env) env.reset() for _ in range(task.max_timesteps): o, r, done, _ = env.step(env.action_space.sample()) if done: env.reset() env.close() logger.info("""Done running, upload results using the following command: python -c "import gym; gym.upload('{}', benchmark_id='{}', algorithm_id='(unknown)')" """.rstrip().format(args.training_dir, benchmark_id)) return 0 if __name__ == '__main__': sys.exit(main())