我们从Python开源项目中，提取了以下22个代码示例，用于说明如何使用gym.envs()。
def make_env(env_id, seed, rank, log_dir): def _thunk(): env = gym.make(env_id) is_atari = hasattr(gym.envs, 'atari') and isinstance(env.unwrapped, gym.envs.atari.atari_env.AtariEnv) if is_atari: env = make_atari(env_id) env.seed(seed + rank) if log_dir is not None: env = bench.Monitor(env, os.path.join(log_dir, str(rank))) if is_atari: env = wrap_deepmind(env) # If the input has shape (W,H,3), wrap for PyTorch convolutions obs_shape = env.observation_space.shape if len(obs_shape) == 3 and obs_shape[2] in [1, 3]: env = WrapPyTorch(env) return env return _thunk
def test_default_time_limit(): # We need an env without a default limit register( id='test.NoLimitDummyVNCEnv-v0', entry_point='universe.envs:DummyVNCEnv', tags={ 'vnc': True, }, ) env = gym.make('test.NoLimitDummyVNCEnv-v0') env.configure(_n=1) env = wrappers.TimeLimit(env) env.reset() assert env._max_episode_seconds == wrappers.time_limit.DEFAULT_MAX_EPISODE_SECONDS assert env._max_episode_steps == None
def add_new_rollouts(spec_ids, overwrite): environments = [spec for spec in envs.registry.all() if spec._entry_point is not None] if spec_ids: environments = [spec for spec in environments if spec.id in spec_ids] assert len(environments) == len(spec_ids), "Some specs not found" with open(ROLLOUT_FILE) as data_file: rollout_dict = json.load(data_file) modified = False for spec in environments: if not overwrite and spec.id in rollout_dict: logger.debug("Rollout already exists for {}. Skipping.".format(spec.id)) else: modified = update_rollout_dict(spec, rollout_dict) or modified if modified: logger.info("Writing new rollout file to {}".format(ROLLOUT_FILE)) with open(ROLLOUT_FILE, "w") as outfile: json.dump(rollout_dict, outfile, indent=2, sort_keys=True) else: logger.info("No modifications needed.")
def should_skip_env_spec_for_tests(spec): # We skip tests for envs that require dependencies or are otherwise # troublesome to run frequently ep = spec._entry_point # Skip mujoco tests for pull request CI skip_mujoco = not (os.environ.get('MUJOCO_KEY_BUNDLE') or os.path.exists(os.path.expanduser('~/.mujoco'))) if skip_mujoco and ep.startswith('gym.envs.mujoco:'): return True if ( 'GoEnv' in ep or 'HexEnv' in ep or ep.startswith('gym.envs.box2d:') or ep.startswith('gym.envs.box2d:') or ep.startswith('gym.envs.parameter_tuning:') or ep.startswith('gym.envs.safety:Semisuper') or (ep.startswith("gym.envs.atari") and not spec.id.startswith("Pong") and not spec.id.startswith("Seaquest")) ): logger.warning("Skipping tests for env {}".format(ep)) return True return False
def __init__(self, env_name, record_video=True, video_schedule=None, log_dir=None, record_log=True): if log_dir is None: if logger.get_snapshot_dir() is None: logger.log("Warning: skipping Gym environment monitoring since snapshot_dir not configured.") else: log_dir = os.path.join(logger.get_snapshot_dir(), "gym_log") Serializable.quick_init(self, locals()) env = gym.envs.make(env_name) self.env = env self.env_id = env.spec.id monitor.logger.setLevel(logging.WARNING) assert not (not record_log and record_video) if log_dir is None or record_log is False: self.monitoring = False else: if not record_video: video_schedule = NoVideoSchedule() else: if video_schedule is None: video_schedule = CappedCubicVideoSchedule() self.env.monitor.start(log_dir, video_schedule, force=True) # add 'force=True' if want overwrite dirs self.monitoring = True self._observation_space = convert_gym_space(env.observation_space) self._action_space = convert_gym_space(env.action_space) self._horizon = env.spec.timestep_limit self._log_dir = log_dir
def __init__(self, env_name, record_video=True, video_schedule=None, log_dir=None, record_log=True, force_reset=False): if log_dir is None: if logger.get_snapshot_dir() is None: logger.log("Warning: skipping Gym environment monitoring since snapshot_dir not configured.") else: log_dir = os.path.join(logger.get_snapshot_dir(), "gym_log") Serializable.quick_init(self, locals()) env = gym.envs.make(env_name) self.env = env self.env_id = env.spec.id assert not (not record_log and record_video) if log_dir is None or record_log is False: self.monitoring = False else: if not record_video: video_schedule = NoVideoSchedule() else: if video_schedule is None: video_schedule = CappedCubicVideoSchedule() self.env = gym.wrappers.Monitor(self.env, log_dir, video_callable=video_schedule, force=True) self.monitoring = True self._observation_space = convert_gym_space(env.observation_space) logger.log("observation space: {}".format(self._observation_space)) self._action_space = convert_gym_space(env.action_space) logger.log("action space: {}".format(self._action_space)) self._horizon = env.spec.tags['wrapper_config.TimeLimit.max_episode_steps'] self._log_dir = log_dir self._force_reset = force_reset
def test_env_semantics(spec): with open(ROLLOUT_FILE) as data_file: rollout_dict = json.load(data_file) if spec.id not in rollout_dict: if not spec.nondeterministic: logger.warn("Rollout does not exist for {}, run generate_json.py to generate rollouts for new envs".format(spec.id)) return logger.info("Testing rollout for {} environment...".format(spec.id)) observations_now, actions_now, rewards_now, dones_now = generate_rollout_hash(spec) errors = [] if rollout_dict[spec.id]['observations'] != observations_now: errors.append('Observations not equal for {} -- expected {} but got {}'.format(spec.id, rollout_dict[spec.id]['observations'], observations_now)) if rollout_dict[spec.id]['actions'] != actions_now: errors.append('Actions not equal for {} -- expected {} but got {}'.format(spec.id, rollout_dict[spec.id]['actions'], actions_now)) if rollout_dict[spec.id]['rewards'] != rewards_now: errors.append('Rewards not equal for {} -- expected {} but got {}'.format(spec.id, rollout_dict[spec.id]['rewards'], rewards_now)) if rollout_dict[spec.id]['dones'] != dones_now: errors.append('Dones not equal for {} -- expected {} but got {}'.format(spec.id, rollout_dict[spec.id]['dones'], dones_now)) if len(errors): for error in errors: logger.warn(error) raise ValueError(errors)
def __init__(self): self.groups = collections.OrderedDict() self.envs = collections.OrderedDict() self.benchmarks = collections.OrderedDict()
def env(self, id): return self.envs[id]
def add_group(self, id, name, description, universe=False): self.groups[id] = { 'id': id, 'name': name, 'description': description, 'envs': [], 'universe': universe, }
def add_task(self, id, group, summary=None, description=None, background=None, deprecated=False, experimental=False, contributor=None): self.envs[id] = { 'group': group, 'id': id, 'summary': summary, 'description': description, 'background': background, 'deprecated': deprecated, 'experimental': experimental, 'contributor': contributor, } if not deprecated: self.groups[group]['envs'].append(id)
def __init__(self, env_name, record_video=True, video_schedule=None, log_dir=None, record_log=True, force_reset=False): if log_dir is None: if logger.get_snapshot_dir() is None: logger.log( "Warning: skipping Gym environment monitoring since snapshot_dir not configured.") else: log_dir = os.path.join(logger.get_snapshot_dir(), "gym_log") Serializable.quick_init(self, locals()) env = gym.envs.make(env_name) self.env = env self.env_id = env.spec.id assert not (not record_log and record_video) if log_dir is None or record_log is False: self.monitoring = False else: if not record_video: video_schedule = NoVideoSchedule() else: if video_schedule is None: video_schedule = CappedCubicVideoSchedule() self.env = gym.wrappers.Monitor( self.env, log_dir, video_callable=video_schedule, force=True) self.monitoring = True self._observation_space = convert_gym_space(env.observation_space) logger.log("observation space: {}".format(self._observation_space)) self._action_space = convert_gym_space(env.action_space) logger.log("action space: {}".format(self._action_space)) self._horizon = env.spec.tags['wrapper_config.TimeLimit.max_episode_steps'] self._log_dir = log_dir self._force_reset = force_reset
def wrap_dqn(env, history_len=4, action_repeat=4, no_op_max=30): """ DQN??????????? Parameters ---------- env: gym.envs gym??? history_len: int ???????????????????? action_repeat: int 1???????????????????????? no_op_max: int ????????????????????????????? ?????????? Returns ---------- env: gym.wrappers.time_limit.TimeLimit gym.env???????? """ env = EpisodicLifeEnv(env) env = NoOpResetEnv(env, no_op_max) env = MaxAndSkipEnv(env, action_repeat) if 'FIRE' in env.unwrapped.get_action_meanings(): env = FireResetEnv(env) env = ProcessFrame84(env) env = FrameStack(env, history_len) env = ClippedRewardsWrapper(env) env = ScaledFloatFrame(env) return env
def add_group(self, id, name, description): self.groups[id] = { 'id': id, 'name': name, 'description': description, 'envs': [] }
def __init__(self, env_name, record_video=True, video_schedule=None, log_dir=None, record_log=True, force_reset=False): if log_dir is None: if logger.get_snapshot_dir() is None: logger.log("Warning: skipping Gym environment monitoring since snapshot_dir not configured.") else: log_dir = os.path.join(logger.get_snapshot_dir(), "gym_log") Serializable.quick_init(self, locals()) env = gym.envs.make(env_name) self.env = env self.env_id = env.spec.id monitor_manager.logger.setLevel(logging.WARNING) assert not (not record_log and record_video) if log_dir is None or record_log is False: self.monitoring = False else: if not record_video: video_schedule = NoVideoSchedule() else: if video_schedule is None: video_schedule = CappedCubicVideoSchedule() self.env = gym.wrappers.Monitor(self.env, log_dir, video_callable=video_schedule, force=True) self.monitoring = True self._observation_space = convert_gym_space(env.observation_space) self._action_space = convert_gym_space(env.action_space) self._horizon = env.spec.timestep_limit self._log_dir = log_dir self._force_reset = force_reset
