def check_space_limit()

in gym/utils/env_checker.py [0:0]

• 32 lines of code
• 14 McCabe index (conditional complexity)

def check_space_limit(space, space_type: str):
    """Check the space limit for only the Box space as a test that only runs as part of `check_env`."""
    if isinstance(space, spaces.Box):
        if np.any(np.equal(space.low, -np.inf)):
            logger.warn(
                f"A Box {space_type} space minimum value is -infinity. This is probably too low."
            )
        if np.any(np.equal(space.high, np.inf)):
            logger.warn(
                f"A Box {space_type} space maximum value is -infinity. This is probably too high."
            )

        # Check that the Box space is normalized
        if space_type == "action":
            if len(space.shape) == 1:  # for vector boxes
                if (
                    np.any(
                        np.logical_and(
                            space.low != np.zeros_like(space.low),
                            np.abs(space.low) != np.abs(space.high),
                        )
                    )
                    or np.any(space.low < -1)
                    or np.any(space.high > 1)
                ):
                    # todo - Add to gymlibrary.ml?
                    logger.warn(
                        "For Box action spaces, we recommend using a symmetric and normalized space (range=[-1, 1] or [0, 1]). "
                        "See https://stable-baselines3.readthedocs.io/en/master/guide/rl_tips.html for more information."
                    )
    elif isinstance(space, spaces.Tuple):
        for subspace in space.spaces:
            check_space_limit(subspace, space_type)
    elif isinstance(space, spaces.Dict):
        for subspace in space.values():
            check_space_limit(subspace, space_type)