ObservationStackWrapper¶
- class maze.core.wrappers.observation_stack_wrapper.ObservationStackWrapper(env: StructuredEnvSpacesMixin, stack_config: List[Dict[str, Any]], stack_mode: str)¶
An wrapper stacking the observations of multiple subsequent time steps.
Provides functionality for:
selecting which observations to stack
how many past observations should be stacked
stacking deltas with the current step observation (instead of the observations itself)
- Parameters:
env – Environment/wrapper to wrap.
stack_config –
The observation stacking configuration.
observation: The name (key) of the respective observation keep_original: Bool, indicates weather to keep or remove the original observation from the dictionary. tag: Optional[str], tag to add to observation (e.g. stacked) delta: Bool, if true deltas are stacked to the previous observation stack_steps: Int, number of past steps to be stacked
stack_mode – Specifies how to stack observations. ‘group_by_actor_id’: Stacks previous observations by actor ID ‘flatten_history’: Stacks the most recent previous observations from flattened history
- clone_from(env: ObservationStackWrapper) None¶
(overrides
SimulatedEnvMixin)implementation of
SimulatedEnvMixin.
- get_observation_and_action_dicts(maze_state: Any | None, maze_action: Any | None, first_step_in_episode: bool) tuple[Dict[int | str, Any] | None, Dict[int | str, Any] | None]¶
(overrides
Wrapper)If this is the first step in an episode, reset the observation stack.
- get_observation_stack() Dict[str, List[numpy.ndarray]] | Dict[ActorID, Dict[str, List[numpy.ndarray]]]¶
Retrieve the observation stack of the wrapper.
- Returns:
The current observation stack of th wrapper.
- observation(observation: Dict[str, numpy.ndarray]) Dict[str, numpy.ndarray]¶
(overrides
ObservationWrapper)Stack observations.
- param observation:
The observation to be stacked.
- return:
The sacked observation.
- reset() Dict[str, numpy.ndarray]¶
(overrides
ObservationWrapper)Intercept
ObservationWrapper.resetand map observation.