garage.envs.bullet.bullet_env
¶
Wrappers for py_bullet environments.
- class BulletEnv(env, is_image=False, max_episode_length=None)¶
Bases:
garage.envs.GymEnv
Binding for py_bullet environments.
- property action_space¶
The action space specification.
- Type
akro.Space
- property observation_space¶
The observation space specification.
- Type
akro.Space
- property spec¶
The envionrment specification.
- Type
garage.envs.env_spec.EnvSpec
- close()¶
Close the wrapped env.
- reset()¶
Call reset on wrapped env.
- Returns
- The first observation conforming to
observation_space.
- dict: The episode-level information.
Note that this is not part of env_info provided in step(). It contains information of he entire episode, which could be needed to determine the first action (e.g. in the case of goal-conditioned or MTRL.)
- Return type
numpy.ndarray
- step(action)¶
Call step on wrapped env.
- Parameters
action (np.ndarray) – An action provided by the agent.
- Returns
The environment step resulting from the action.
- Return type
- Raises
RuntimeError – if step() is called after the environment has been constructed and reset() has not been called.
RuntimeError – if underlying environment outputs inconsistent env_info keys.
- render(mode)¶
Renders the environment.
- visualize()¶
Creates a visualization of the environment.