from copy import deepcopy from typing import Optional, TypeVar from stable_baselines3.common.vec_env.base_vec_env import CloudpickleWrapper, VecEnv, VecEnvWrapper from stable_baselines3.common.vec_env.dummy_vec_env import DummyVecEnv from stable_baselines3.common.vec_env.stacked_observations import StackedObservations from stable_baselines3.common.vec_env.subproc_vec_env import SubprocVecEnv from stable_baselines3.common.vec_env.vec_check_nan import VecCheckNan from stable_baselines3.common.vec_env.vec_extract_dict_obs import VecExtractDictObs from stable_baselines3.common.vec_env.vec_frame_stack import VecFrameStack from stable_baselines3.common.vec_env.vec_monitor import VecMonitor from stable_baselines3.common.vec_env.vec_normalize import VecNormalize from stable_baselines3.common.vec_env.vec_transpose import VecTransposeImage from stable_baselines3.common.vec_env.vec_video_recorder import VecVideoRecorder VecEnvWrapperT = TypeVar("VecEnvWrapperT", bound=VecEnvWrapper) def unwrap_vec_wrapper(env: VecEnv, vec_wrapper_class: type[VecEnvWrapperT]) -> Optional[VecEnvWrapperT]: """ Retrieve a ``VecEnvWrapper`` object by recursively searching. :param env: The ``VecEnv`` that is going to be unwrapped :param vec_wrapper_class: The desired ``VecEnvWrapper`` class. :return: The ``VecEnvWrapper`` object if the ``VecEnv`` is wrapped with the desired wrapper, None otherwise """ env_tmp = env while isinstance(env_tmp, VecEnvWrapper): if isinstance(env_tmp, vec_wrapper_class): return env_tmp env_tmp = env_tmp.venv return None def unwrap_vec_normalize(env: VecEnv) -> Optional[VecNormalize]: """ Retrieve a ``VecNormalize`` object by recursively searching. :param env: The VecEnv that is going to be unwrapped :return: The ``VecNormalize`` object if the ``VecEnv`` is wrapped with ``VecNormalize``, None otherwise """ return unwrap_vec_wrapper(env, VecNormalize) def is_vecenv_wrapped(env: VecEnv, vec_wrapper_class: type[VecEnvWrapper]) -> bool: """ Check if an environment is already wrapped in a given ``VecEnvWrapper``. :param env: The VecEnv that is going to be checked :param vec_wrapper_class: The desired ``VecEnvWrapper`` class. :return: True if the ``VecEnv`` is wrapped with the desired wrapper, False otherwise """ return unwrap_vec_wrapper(env, vec_wrapper_class) is not None def sync_envs_normalization(env: VecEnv, eval_env: VecEnv) -> None: """ Synchronize the normalization statistics of an eval environment and train environment when they are both wrapped in a ``VecNormalize`` wrapper. :param env: Training env :param eval_env: Environment used for evaluation. """ env_tmp, eval_env_tmp = env, eval_env while isinstance(env_tmp, VecEnvWrapper): assert isinstance(eval_env_tmp, VecEnvWrapper), ( "Error while synchronizing normalization stats: expected the eval env to be " f"a VecEnvWrapper but got {eval_env_tmp} instead. " "This is probably due to the training env not being wrapped the same way as the evaluation env. " f"Training env type: {env_tmp}." ) if isinstance(env_tmp, VecNormalize): assert isinstance(eval_env_tmp, VecNormalize), ( "Error while synchronizing normalization stats: expected the eval env to be " f"a VecNormalize but got {eval_env_tmp} instead. " "This is probably due to the training env not being wrapped the same way as the evaluation env. " f"Training env type: {env_tmp}." ) # Only synchronize if observation normalization exists if hasattr(env_tmp, "obs_rms"): eval_env_tmp.obs_rms = deepcopy(env_tmp.obs_rms) eval_env_tmp.ret_rms = deepcopy(env_tmp.ret_rms) env_tmp = env_tmp.venv eval_env_tmp = eval_env_tmp.venv __all__ = [ "CloudpickleWrapper", "DummyVecEnv", "StackedObservations", "SubprocVecEnv", "VecCheckNan", "VecEnv", "VecEnvWrapper", "VecExtractDictObs", "VecFrameStack", "VecMonitor", "VecNormalize", "VecTransposeImage", "VecVideoRecorder", "is_vecenv_wrapped", "sync_envs_normalization", "unwrap_vec_normalize", "unwrap_vec_wrapper", ]