(
      self,
      walker: Callable[..., 'legacy_base.Walker'],
      arena: composer.Arena,
      ref_path: Text,
      ref_steps: Sequence[int],
      dataset: Union[Text, Sequence[Any]],
      termination_error_threshold: float = 0.3,
      prop_termination_error_threshold: float = 0.1,
      min_steps: int = 10,
      reward_type: Text = 'termination_reward',
      physics_timestep: float = DEFAULT_PHYSICS_TIMESTEP,
      always_init_at_clip_start: bool = False,
      proto_modifier: Optional[Any] = None,
      prop_factory: Optional[Any] = None,
      disable_props: bool = True,
      ghost_offset: Optional[Sequence[Union[int, float]]] = None,
      body_error_multiplier: Union[int, float] = 1.0,
      actuator_force_coeff: float = 0.015,
      enabled_reference_observables: Optional[Sequence[Text]] = None,
  )
Mocap tracking task.

    Args:
      walker: Walker constructor to be used.
      arena: Arena to be used.
      ref_path: Path to the dataset containing reference poses.
      ref_steps: tuples of indices of reference observation. E.g if
        ref_steps=(1, 2, 3) the walker/reference observation at time t will
        contain information from t+1, t+2, t+3.
      dataset: dataset: A ClipCollection instance or a named dataset that
        appears as a key in DATASETS in datasets.py
      termination_error_threshold: Error threshold for episode terminations for
        hand body position and joint error only.
      prop_termination_error_threshold: Error threshold for episode terminations
        for prop position.
      min_steps: minimum number of steps within an episode. This argument
        determines the latest allowable starting point within a given reference
        trajectory.
      reward_type: type of reward to use, must be a string that appears as a key
        in the REWARD_FN dict in rewards.py.
      physics_timestep: Physics timestep to use for simulation.
      always_init_at_clip_start: only initialize epsidodes at the start of a
        reference trajectory.
      proto_modifier: Optional proto modifier to modify reference trajectories,
        e.g. adding a vertical offset.
      prop_factory: Optional function that takes the mocap proto and returns
        the corresponding props for the trajectory.
      disable_props: If prop_factory is specified but disable_props is True,
        no props will be created.
      ghost_offset: if not None, include a ghost rendering of the walker with
        the reference pose at the specified position offset.
      body_error_multiplier: A multiplier that is applied to the body error term
        when determining failure termination condition.
      actuator_force_coeff: A coefficient for the actuator force reward channel.
      enabled_reference_observables: Optional iterable of enabled observables.
        If not specified, a reasonable default set will be enabled.
Mocap tracking task.
Mocap tracking task .
def __init__(
      self,
      walker: Callable[..., 'legacy_base.Walker'],
      arena: composer.Arena,
      ref_path: Text,
      ref_steps: Sequence[int],
      dataset: Union[Text, Sequence[Any]],
      termination_error_threshold: float = 0.3,
      prop_termination_error_threshold: float = 0.1,
      min_steps: int = 10,
      reward_type: Text = 'termination_reward',
      physics_timestep: float = DEFAULT_PHYSICS_TIMESTEP,
      always_init_at_clip_start: bool = False,
      proto_modifier: Optional[Any] = None,
      prop_factory: Optional[Any] = None,
      disable_props: bool = True,
      ghost_offset: Optional[Sequence[Union[int, float]]] = None,
      body_error_multiplier: Union[int, float] = 1.0,
      actuator_force_coeff: float = 0.015,
      enabled_reference_observables: Optional[Sequence[Text]] = None,
  ):
    """Mocap tracking task.

    Args:
      walker: Walker constructor to be used.
      arena: Arena to be used.
      ref_path: Path to the dataset containing reference poses.
      ref_steps: tuples of indices of reference observation. E.g if
        ref_steps=(1, 2, 3) the walker/reference observation at time t will
        contain information from t+1, t+2, t+3.
      dataset: dataset: A ClipCollection instance or a named dataset that
        appears as a key in DATASETS in datasets.py
      termination_error_threshold: Error threshold for episode terminations for
        hand body position and joint error only.
      prop_termination_error_threshold: Error threshold for episode terminations
        for prop position.
      min_steps: minimum number of steps within an episode. This argument
        determines the latest allowable starting point within a given reference
        trajectory.
      reward_type: type of reward to use, must be a string that appears as a key
        in the REWARD_FN dict in rewards.py.
      physics_timestep: Physics timestep to use for simulation.
      always_init_at_clip_start: only initialize epsidodes at the start of a
        reference trajectory.
      proto_modifier: Optional proto modifier to modify reference trajectories,
        e.g. adding a vertical offset.
      prop_factory: Optional function that takes the mocap proto and returns
        the corresponding props for the trajectory.
      disable_props: If prop_factory is specified but disable_props is True,
        no props will be created.
      ghost_offset: if not None, include a ghost rendering of the walker with
        the reference pose at the specified position offset.
      body_error_multiplier: A multiplier that is applied to the body error term
        when determining failure termination condition.
      actuator_force_coeff: A coefficient for the actuator force reward channel.
      enabled_reference_observables: Optional iterable of enabled observables.
        If not specified, a reasonable default set will be enabled.
    """
    super().__init__(
        walker=walker,
        arena=arena,
        ref_path=ref_path,
        ref_steps=ref_steps,
        termination_error_threshold=termination_error_threshold,
        prop_termination_error_threshold=prop_termination_error_threshold,
        min_steps=min_steps,
        dataset=dataset,
        reward_type=reward_type,
        physics_timestep=physics_timestep,
        always_init_at_clip_start=always_init_at_clip_start,
        proto_modifier=proto_modifier,
        prop_factory=prop_factory,
        disable_props=disable_props,
        ghost_offset=ghost_offset,
        body_error_multiplier=body_error_multiplier,
        actuator_force_coeff=actuator_force_coeff,
        enabled_reference_observables=enabled_reference_observables)
    self._walker.observables.add_observable(
        'time_in_clip',
        base_observable.Generic(self.get_normalized_time_in_clip))
def __init__ ( self , walker : Callable [ ... , 'legacy_base.Walker' ] , arena : composer . Arena , ref_path : Text , ref_steps : Sequence [ int ] , dataset : Union [ Text , Sequence [ Any ] ] , termination_error_threshold : float = 0.3 , prop_termination_error_threshold : float = 0.1 , min_steps : int = 10 , reward_type : Text = 'termination_reward' , physics_timestep : float = DEFAULT_PHYSICS_TIMESTEP , always_init_at_clip_start : bool = False , proto_modifier : Optional [ Any ] = None , prop_factory : Optional [ Any ] = None , disable_props : bool = True , ghost_offset : Optional [ Sequence [ Union [ int , float ] ] ] = None , body_error_multiplier : Union [ int , float ] = 1.0 , actuator_force_coeff : float = 0.015 , enabled_reference_observables : Optional [ Sequence [ Text ] ] = None , ) : super ( ) . __init__ ( walker = walker , arena = arena , ref_path = ref_path , ref_steps = ref_steps , termination_error_threshold = termination_error_threshold , prop_termination_error_threshold = prop_termination_error_threshold , min_steps = min_steps , dataset = dataset , reward_type = reward_type , physics_timestep = physics_timestep , always_init_at_clip_start = always_init_at_clip_start , proto_modifier = proto_modifier , prop_factory = prop_factory , disable_props = disable_props , ghost_offset = ghost_offset , body_error_multiplier = body_error_multiplier , actuator_force_coeff = actuator_force_coeff , enabled_reference_observables = enabled_reference_observables ) self . _walker . observables . add_observable ( 'time_in_clip' , base_observable . Generic ( self . get_normalized_time_in_clip ) )