def _gripper_visualization(self):
        """
        Do any needed visualization here. Overrides superclass implementations.
        """
        # color the gripper site appropriately based on distance to nearest object
        if self.gripper_visualization:
            # find closest object
            square_dist = lambda x: np.sum(
                np.square(x - self.sim.data.get_site_xpos("grip_site"))
            )
            dists = np.array(list(map(square_dist, self.sim.data.site_xpos)))
            dists[self.eef_site_id] = np.inf  # make sure we don't pick the same site
            dists[self.eef_cylinder_id] = np.inf
            ob_dists = dists[
                self.object_site_ids
            ]  # filter out object sites we care about
            min_dist = np.min(ob_dists)
            ob_id = np.argmin(ob_dists)
            ob_name = self.object_names[ob_id]

            # set RGBA for the EEF site here
            max_dist = 0.1
            scaled = (1.0 - min(min_dist / max_dist, 1.)) ** 15
            rgba = np.zeros(4)
            rgba[0] = 1 - scaled
            rgba[1] = scaled
            rgba[3] = 0.5

            self.sim.model.site_rgba[self.eef_site_id] = rgba
Do any needed visualization here. Overrides superclass implementations.