from __future__ import absolute_import from __future__ import division from __future__ import print_function import logging import pickle from ray.rllib.utils.annotations import PublicAPI logger = logging.getLogger(__name__) try: import requests # `requests` is not part of stdlib. except ImportError: requests = None logger.warning( "Couldn't import `requests` library. Be sure to install it on" " the client side.") @PublicAPI class PolicyClient(object): """REST client to interact with a RLlib policy server.""" START_EPISODE = "START_EPISODE" GET_ACTION = "GET_ACTION" LOG_ACTION = "LOG_ACTION" LOG_RETURNS = "LOG_RETURNS" END_EPISODE = "END_EPISODE" @PublicAPI def __init__(self, address): self._address = address @PublicAPI def start_episode(self, episode_id=None, training_enabled=True): """Record the start of an episode. Arguments: episode_id (str): Unique string id for the episode or None for it to be auto-assigned. training_enabled (bool): Whether to use experiences for this episode to improve the policy. Returns: episode_id (str): Unique string id for the episode. """ return self._send({ "episode_id": episode_id, "command": PolicyClient.START_EPISODE, "training_enabled": training_enabled, })["episode_id"] @PublicAPI def get_action(self, episode_id, observation): """Record an observation and get the on-policy action. Arguments: episode_id (str): Episode id returned from start_episode(). observation (obj): Current environment observation. Returns: action (obj): Action from the env action space. """ return self._send({ "command": PolicyClient.GET_ACTION, "observation": observation, "episode_id": episode_id, })["action"] @PublicAPI def log_action(self, episode_id, observation, action): """Record an observation and (off-policy) action taken. Arguments: episode_id (str): Episode id returned from start_episode(). observation (obj): Current environment observation. action (obj): Action for the observation. """ self._send({ "command": PolicyClient.LOG_ACTION, "observation": observation, "action": action, "episode_id": episode_id, }) @PublicAPI def log_returns(self, episode_id, reward, info=None): """Record returns from the environment. The reward will be attributed to the previous action taken by the episode. Rewards accumulate until the next action. If no reward is logged before the next action, a reward of 0.0 is assumed. Arguments: episode_id (str): Episode id returned from start_episode(). reward (float): Reward from the environment. """ self._send({ "command": PolicyClient.LOG_RETURNS, "reward": reward, "info": info, "episode_id": episode_id, }) @PublicAPI def end_episode(self, episode_id, observation): """Record the end of an episode. Arguments: episode_id (str): Episode id returned from start_episode(). observation (obj): Current environment observation. """ self._send({ "command": PolicyClient.END_EPISODE, "observation": observation, "episode_id": episode_id, }) def _send(self, data): payload = pickle.dumps(data) response = requests.post(self._address, data=payload) if response.status_code != 200: logger.error("Request failed {}: {}".format(response.text, data)) response.raise_for_status() parsed = pickle.loads(response.content) return parsed