garage.envs.bullet
¶
Wrappers for the py_bullet based gym environments.
See https://github.com/bulletphysics/bullet3/tree/master/examples/pybullet
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class
BulletEnv
(env, is_image=False, max_episode_length=None)¶ Bases:
garage.envs.GymEnv
Binding for py_bullet environments.
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close
(self)¶ Close the wrapped env.
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property
action_space
(self)¶ akro.Space: The action space specification.
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property
observation_space
(self)¶ akro.Space: The observation space specification.
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property
spec
(self)¶ garage.envs.env_spec.EnvSpec: The envionrment specification.
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property
render_modes
(self)¶ list: A list of string representing the supported render modes.
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reset
(self)¶ 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
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step
(self, 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.
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render
(self, mode)¶ Renders the environment.
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visualize
(self)¶ Creates a visualization of the environment.
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