RLEnv class
Reinforcement Learning (RL) environment class which subclasses gym.Env.
Contents
- Reference
This is a wrapper over Env for RL users. To create custom RL environments users should subclass RLEnv and define the following methods: get_reward_range(), get_reward(), get_done(), get_info().
As this is a subclass of gym.Env, it implements reset() and
step().
Methods
- def close(self) -> None
- def get_done(self, observations: simulator.Observations) -> bool
- Returns boolean indicating whether episode is done after performing the last action.
- def get_info(self, observations) -> typing.Dict[typing.Any, typing.Any]
- def get_reward(self, observations: simulator.Observations) -> typing.Any
- Returns reward after action has been performed.
- def get_reward_range(self)
- Get min, max range of reward.
- def render(self, mode: str = 'rgb') -> numpy.ndarray
- def reset(self) -> simulator.Observations
- def seed(self, seed: typing.Optional[int] = None) -> None
- def step(self, *args, **kwargs) -> typing.Tuple[simulator.Observations, typing.Any, bool, dict]
- Perform an action in the environment.
Special methods
- def __enter__(self)
- def __exit__(self, exc_type, exc_val, exc_tb)
- def __init__(self, config: habitat.config.default.Config, dataset: typing.Optional[dataset.Dataset] = None) -> None
- Constructor
- def __str__(self)
Properties
- current_episode: typing.Type[dataset.Episode] get
- episodes: typing.List[typing.Type[dataset.Episode]] get set
- habitat_env: Env get
- unwrapped get
- Completely unwrap this env.
Data
- action_space = None
- metadata = {'render.modes': []}
- observation_space = None
- reward_range = (-inf, inf)
- spec = None
Method documentation
def habitat.
Returns boolean indicating whether episode is done after performing the last action.
| Parameters | |
|---|---|
| observations | observations from simulator and task. |
| Returns | done boolean after performing the last action. |
This method is called inside the step method.
def habitat.
| Parameters | |
|---|---|
| observations | observations from simulator and task. |
| Returns | info after performing the last action. |
def habitat.
Returns reward after action has been performed.
| Parameters | |
|---|---|
| observations | observations from simulator and task. |
| Returns | reward after performing the last action. |
This method is called inside the step() method.
def habitat.
Get min, max range of reward.
| Returns | [min, max] range of reward. |
|---|
def habitat.
Perform an action in the environment.
| Returns | (observations, reward, done, info) |
|---|
def habitat.
Constructor
| Parameters | |
|---|---|
| config | config to construct Env |
| dataset | dataset to construct Env. |
Property documentation
habitat.
Completely unwrap this env.
- Returns:
- gym.Env: The base non-wrapped gym.Env instance