def _check_box_observation_space()

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

• 28 lines of code
• 9 McCabe index (conditional complexity)

def _check_box_observation_space(observation_space: spaces.Box):
    """Checks that a :class:`Box` observation space is defined in a sensible way.

    Args:
        observation_space: A box observation space
    """
    # Check if the box is an image
    if len(observation_space.shape) == 3:
        if observation_space.dtype != np.uint8:
            logger.warn(
                f"It seems a Box observation space is an image but the `dtype` is not `np.uint8`, actual type: {observation_space.dtype}. "
                "If the Box observation space is not an image, we recommend flattening the observation to have only a 1D vector."
            )
        if np.any(observation_space.low != 0) or np.any(observation_space.high != 255):
            logger.warn(
                "It seems a Box observation space is an image but the upper and lower bounds are not in [0, 255]. "
                "Generally, CNN policies assume observations are within that range, so you may encounter an issue if the observation values are not."
            )

    if len(observation_space.shape) not in [1, 3]:
        logger.warn(
            "A Box observation space has an unconventional shape (neither an image, nor a 1D vector). "
            "We recommend flattening the observation to have only a 1D vector or use a custom policy to properly process the data. "
            f"Actual observation shape: {observation_space.shape}"
        )

    assert (
        observation_space.low.shape == observation_space.shape
    ), f"The Box observation space shape and low shape have different shapes, low shape: {observation_space.low.shape}, box shape: {observation_space.shape}"
    assert (
        observation_space.high.shape == observation_space.shape
    ), f"The Box observation space shape and high shape have have different shapes, high shape: {observation_space.high.shape}, box shape: {observation_space.shape}"

    if np.any(observation_space.low == observation_space.high):
        logger.warn("A Box observation space maximum and minimum values are equal.")
    elif np.any(observation_space.high < observation_space.low):
        logger.warn("A Box observation space low value is greater than a high value.")