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
(self)¶ akro.Space: The action space specification.
-
property
observation_space
(self)¶ akro.Space: The observation space specification.
-
property
spec
(self)¶ EnvSpec: The environment specification.
-
property
render_modes
(self)¶ list: A list of string representing the supported render modes.
-
classmethod
from_suite
(cls, domain_name, task_name)¶ Create a DmControl task given the domain name and task name.
-
reset
(self)¶ 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
(self, 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
(self, 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
(self)¶ Creates a visualization of the environment.
-
close
(self)¶ Close the environment.
-
property