code: def fgsm(x, predictions, eps=0.3, clip_min=None, clip_max=None):
      warnings.warn(
          "This function is deprecated and will be removed on or after "
          "2019-04-09. Switch to cleverhans.attacks.FastGradientMethod."
      )
      return fgm(
          x,
          predictions,
          y=None,
          eps=eps,
          ord=np.inf,
          clip_min=clip_min,
          clip_max=clip_max,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import warnings
  import numpy
  from cleverhans.attacks.carlini_wagner_l2 import CWL2
  from cleverhans.attacks.deep_fool import deepfool_batch, deepfool_attack
  from cleverhans.attacks.elastic_net_method import EAD
  from cleverhans.attacks.lbfgs import LBFGS_impl
  from cleverhans.attacks.saliency_map_method import jsma_symbolic
  from cleverhans.attacks.spsa import TensorOptimizer, TensorGradientDescent, TensorAdam
  from cleverhans.attacks.spsa import SPSAAdam, margin_logit_loss, _apply_black_border
  from cleverhans.attacks.spsa import _apply_transformation, spm, parallel_apply_transformations
  from cleverhans.attacks.virtual_adversarial_method import vatm
  from cleverhans.utils_tf import jacobian_graph, jacobian_augmentation
  from cleverhans import utils
label_desc: Use image node_id 1 for calling a global function with example usage: fgsm(x, predictions, eps, clip_min, clip_max) and returns: fgm