garage.envs.bullet.bullet_env

Wrappers for py_bullet environments.

class BulletEnv(env, is_image=False, max_episode_length=None)

Bases: garage.envs.GymEnv

Inheritance diagram of garage.envs.bullet.bullet_env.BulletEnv

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

property render_modes

A list of string representing the supported render modes.

Type

list

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

EnvStep

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.

Parameters

mode (str) – the mode to render with. The string must be present in self.render_modes.

Returns

the return value for render, depending on each env.

Return type

object

visualize()

Creates a visualization of the environment.