def __weighted_lp_norm(self, perturbations: np.ndarray) -> np.ndarray:
        """
        Lp-norm of perturbation vectors weighted by feature importance.

        :param perturbations: Perturbations of samples towards being adversarial.
        :return: Array with weighted Lp-norm of perturbations.
        """
        order: int | float = np.inf if self.norm == "inf" else float(self.norm)
        return self.lambd * np.linalg.norm(self.importance_vec * perturbations, axis=1, ord=order).reshape(-1, 1)

        Lp-norm of perturbation vectors weighted by feature importance.

        :param perturbations: Perturbations of samples towards being adversarial.
        :return: Array with weighted Lp-norm of perturbations.
        
art/attacks/evasion/lowprofool.py