garage.envs.dm_control
¶
Wrappers for the DeepMind Control Suite.
See https://github.com/deepmind/dm_control
- class DMControlEnv(env, name=None)¶
Bases:
garage.Environment
Binding for dm_control <https://arxiv.org/pdf/1801.00690.pdf>.
- property action_space¶
The action space specification.
- Type
akro.Space
- property observation_space¶
The observation space specification.
- Type
akro.Space
- classmethod from_suite(domain_name, task_name)¶
Create a DmControl task given the domain name and task name.
- reset()¶
Resets the environment.
- 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)¶
Steps the environment with the action and returns a EnvStep.
- Parameters
action (object) – input action
- 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.
- render(mode)¶
Render the environment.
- Parameters
mode (str) – render mode.
- Returns
if mode is ‘rgb_array’, else return None.
- Return type
np.ndarray
- Raises
ValueError – if mode is not supported.
- visualize()¶
Creates a visualization of the environment.
- close()¶
Close the environment.