class_docstr: "Fast Gradient Sign Method" is extended to support targeted attack.
  "Fast Gradient Sign Method" was originally implemented by Goodfellow et
  al. (2015) with the infinity norm.
  
  Paper link: https://arxiv.org/abs/1412.6572
class_docstr_tok: ["``","Fast","Gradient","Sign","Method","''","is","extended","to","support","targeted","attack",".","``","Fast","Gradient","Sign","Method","''","was","originally","implemented","by","Goodfellow","et","al",".","(","2015",")","with","the","infinity","norm",".","Paper","link",":","https",":","\/\/arxiv.org\/abs\/1412.6572"]
code: def _apply(
      self,
      adversary,
      epsilons=0.01,
      epsilons_max=0.5,
      epsilon_steps=100,
      steps=10,
  ):
      return GradientMethodAttack._apply(
          self,
          adversary=adversary,
          norm_ord=np.inf,
          epsilons=epsilons,
          epsilons_max=epsilons_max,
          steps=steps,
          epsilon_steps=epsilon_steps,
      )
  
imports: from __future__ import division
  from builtins import range
  import logging
  from collections import Iterable
  import numpy
  from .base import Attack
  from functools import reduce
label_desc: Use image node_id 1 for calling the FastGradientSignMethodTargetedAttack obj's underlying member method code with example usage: obj._apply(adversary, epsilons, epsilons_max, epsilon_steps, steps) and returns: GradientMethodAttack