How to use the stable-baselines.stable_baselines.bench.monitor.Monitor function in stable-baselines

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github harvard-edge / quarl / stable-baselines / stable_baselines / bench / monitor.py View on Github external
def get_monitor_files(path: str) -> List[str]:
    """
    get all the monitor files in the given path

    :param path: (str) the logging folder
    :return: ([str]) the log files
    """
    return glob(os.path.join(path, "*" + Monitor.EXT))
github harvard-edge / quarl / stable-baselines / stable_baselines / bench / monitor.py View on Github external
def __init__(self,
                 env: gym.Env,
                 filename: Optional[str],
                 allow_early_resets: bool = True,
                 reset_keywords=(),
                 info_keywords=()):
        """
        A monitor wrapper for Gym environments, it is used to know the episode reward, length, time and other data.

        :param env: (gym.Env) The environment
        :param filename: (Optional[str]) the location to save a log file, can be None for no log
        :param allow_early_resets: (bool) allows the reset of the environment before it is done
        :param reset_keywords: (tuple) extra keywords for the reset call, if extra parameters are needed at reset
        :param info_keywords: (tuple) extra information to log, from the information return of environment.step
        """
        super(Monitor, self).__init__(env=env)
        self.t_start = time.time()
        if filename is None:
            self.file_handler = None
            self.logger = None
        else:
            if not filename.endswith(Monitor.EXT):
                if os.path.isdir(filename):
                    filename = os.path.join(filename, Monitor.EXT)
                else:
                    filename = filename + "." + Monitor.EXT
            self.file_handler = open(filename, "wt")
            self.file_handler.write('#%s\n' % json.dumps({"t_start": self.t_start, 'env_id': env.spec and env.spec.id}))
            self.logger = csv.DictWriter(self.file_handler,
                                         fieldnames=('r', 'l', 't') + reset_keywords + info_keywords)
            self.logger.writeheader()
            self.file_handler.flush()

stable-baselines

A fork of OpenAI Baselines, implementations of reinforcement learning algorithms.

MIT
Latest version published 4 years ago

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60 / 100
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