Env class
Fundamental environment class for habitat.
All the information needed for working on embodied task with simulator
is abstracted inside Env. Acts as a base for other derived
environment classes. Env consists of three major components:
dataset (episodes), simulator (sim) and task and
connects all the three components together.
Methods
- def close(self) -> None
- def get_metrics(self) -> embodied_task.Metrics
- def reconfigure(self, config: DictConfig)
- def render(self, mode = 'rgb') -> numpy.ndarray
- def reset(self) -> simulator.Observations
- Resets the environments and returns the initial observations.
- def seed(self, seed: int) -> None
- def step(self, action: typing.Union[int, str, typing.Dict[str, typing.Any]], **kwargs) -> simulator.Observations
- Perform an action in the environment and return observations.
Special methods
Properties
- current_episode: dataset.Episode get set
- episode_iterator: typing.Iterator[dataset.Episode] get set
- episode_over: bool get
- episode_start_time: typing.Optional[float] get
- episodes: typing.List[dataset.Episode] get set
- sim: simulator.Simulator get
- task: embodied_task.EmbodiedTask get
Data
- observation_space: gym.spaces.dict.Dict = None
SpaceDictobject corresponding to sensor in sim and task.- action_space: gym.spaces.dict.Dict = None
gym.spaceobject corresponding to valid actions.- number_of_episodes: typing.Optional[int] = None
Method documentation
def habitat. core. env. Env. reset(self) -> simulator.Observations
Resets the environments and returns the initial observations.
| Returns | initial observations from the environment. |
|---|
def habitat. core. env. Env. step(self,
action: typing.Union[int, str, typing.Dict[str, typing.Any]],
**kwargs) -> simulator.Observations
Perform an action in the environment and return observations.
| Parameters | |
|---|---|
| action | action (belonging to action_space) to be performed inside the environment. Action is a name or index of allowed task’s action and action arguments (belonging to action’s action_space) to support parametrized and continuous actions. |
| kwargs | |
| Returns | observations after taking action in environment. |
def habitat. core. env. Env. __init__(self,
config: DictConfig,
dataset = None)
Constructor
| Parameters | |
|---|---|
| config | config for the environment. Should contain id for
simulator and task_name which are passed into make_sim and
make_task. |
| dataset | reference to dataset for task instance level
information. Can be defined as None in which case
_episodes should be populated from outside. |