Source code for embodichain_tasks.locomotion.velocity.contracts.anymal_c.config

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"""Load the ANYmal-C flat velocity task configuration."""

from __future__ import annotations

from dataclasses import MISSING

from embodichain.utils import configclass

from .._config import load_task_data

__all__ = ["ANYmalCVelocityConfig", "load_config"]




@configclass
class ANYmalCVelocityConfig:
    """Dimensions, control parameters, and timing for ANYmal-C."""

    data: dict = MISSING
    joint_names: tuple[str, ...] = MISSING
    default_joint_position: tuple[float, ...] = MISSING
    action_scale: tuple[float, ...] = MISSING
    actor_observation_dim: int = MISSING
    critic_observation_dim: int = MISSING
    action_dim: int = MISSING
    physics_dt: float = MISSING
    control_dt: float = MISSING
    max_episode_steps: int = MISSING





def load_config() -> ANYmalCVelocityConfig:
    """Load ANYmal-C settings from its packaged task definition.

    Returns:
        Joint order, default pose, action scale, observation dimensions and timing.

    Raises:
        ValueError: Joint, default-pose and action dimensions differ.
    """
    data = load_task_data("anymal_c_flat")
    robot = data["robot"]
    joint_names = tuple(robot["joint_names"])
    default_position = tuple(float(value) for value in robot["default_joint_position"])
    scale = robot["action_scale"]
    action_scale = (
        (float(scale),) * len(joint_names)
        if isinstance(scale, (int, float))
        else tuple(float(value) for value in scale)
    )
    physics = data["physics"]
    control_dt = float(physics["control_dt"])
    if not len(joint_names) == len(default_position) == len(action_scale):
        raise ValueError("ANYmal-C joint, default pose, and action dimensions differ")
    return ANYmalCVelocityConfig(
        data=data,
        joint_names=joint_names,
        default_joint_position=default_position,
        action_scale=action_scale,
        actor_observation_dim=int(data["observations"]["actor_dimension"]),
        critic_observation_dim=int(data["observations"]["critic_dimension"]),
        action_dim=len(joint_names),
        physics_dt=float(physics["physics_dt"]),
        control_dt=control_dt,
        max_episode_steps=round(float(physics["episode_length_s"]) / control_dt),
    )