@call_decorator<EOL><INDENT>def __call__(self, input_or_adv, label=None, unpack=True,<EOL>epsilons=<NUM_LIT:1000>, max_epsilon=<NUM_LIT:1>):<DEDENT>
a = input_or_adv<EOL>del input_or_adv<EOL>del label<EOL>del unpack<EOL>return self._run(a, epsilons=epsilons, max_epsilon=max_epsilon)<EOL>
Adds the sign of the gradient to the image, gradually increasing
        the magnitude until the image is misclassified.

        Parameters
        ----------
        input_or_adv : `numpy.ndarray` or :class:`Adversarial`
            The original, unperturbed input as a `numpy.ndarray` or
            an :class:`Adversarial` instance.
        label : int
            The reference label of the original input. Must be passed
            if `a` is a `numpy.ndarray`, must not be passed if `a` is
            an :class:`Adversarial` instance.
        unpack : bool
            If true, returns the adversarial input, otherwise returns
            the Adversarial object.
        epsilons : int or Iterable[float]
            Either Iterable of step sizes in the direction of the sign of
            the gradient or number of step sizes between 0 and max_epsilon
            that should be tried.
        max_epsilon : float
            Largest step size if epsilons is not an iterable.