Base class for embodied task.
EmbodiedTask holds definition of
a task that agent needs to solve: action space, observation space,
measures, simulator usage.
EmbodiedTask has reset() and
step() methods that are called by
EmbodiedTask is the
one of main dimensions for the framework extension. Once new embodied task
is introduced implementation of
EmbodiedTask is a formal definition of
the task that opens opportunity for others to propose solutions and
include it into benchmark results.
- config: config for the task. sim: reference to the simulator for calculating task observations. dataset: reference to dataset for task instance level information.
- data measurements:
- set of task measures.
- data sensor_suite:
- suite of task sensors.
- def get_action_name(self, action_index: typing.Union[int, numpy.integer])
- def overwrite_sim_config(self, sim_config: DictConfig, episode: dataset.Episode) -> DictConfig
- Update config merging information from
- def reset(self, episode: dataset.Episode)
- def seed(self, seed: int) -> None
- def step(self, action: typing.Dict[str, typing.Any], episode: dataset.Episode)
- def __init__(self, config: DictConfig, sim: simulator.Simulator, dataset: typing.Optional[dataset.Dataset] = None)
- action_space: gym.spaces.space.Space get
- is_episode_active get
- measurements: Measurements = None
- sensor_suite: simulator.SensorSuite = None
core. embodied_task. EmbodiedTask. overwrite_sim_config(self,
episode: dataset.Episode) -> DictConfig
Update config merging information from
|sim_config||config for simulator.|