class_docstr: Implementation of the NewtonFool Attack. [#Jang17]_
  
  Args:
      steps : Number of update steps to perform.
      step_size : Size of each update step.
  
  References:
      .. [#Jang17] Uyeong Jang et al., "Objective Metrics and Gradient Descent
          Algorithms for Adversarial Examples in Machine Learning",
          https://dl.acm.org/citation.cfm?id=3134635
class_docstr_tok: ["Implementation","of","the","NewtonFool","Attack",".","[","#","Jang17","]","_","Args",":","steps",":","Number","of","update","steps","to","perform",".","step_size",":","Size","of","each","update","step",".","References",":","..","[","#","Jang17","]","Uyeong","Jang","et","al.",",","``","Objective","Metrics","and","Gradient","Descent","Algorithms","for","Adversarial","Examples","in","Machine","Learning","''",",","https",":","\/\/dl.acm.org\/citation.cfm","?","id=3134635"]
code: def __init__(self, steps: int = 100, stepsize: float = 0.01):
      self.steps = steps
      self.stepsize = stepsize
  
file_path: foolbox/foolbox/attacks/newtonfool.py
imports: from typing import Union, Tuple, Any, Optional
  import eagerpy
  from ..models import Model
  from ..criteria import Misclassification
  from ..distances import l2
  from ..devutils import atleast_kd, flatten
  from .base import MinimizationAttack
  from .base import get_criterion
  from .base import T
  from .base import raise_if_kwargs
  from .base import verify_input_bounds
label_desc: Use image node_id 1 to create a new NewtonFoolAttack object from inherited base classes: MinimizationAttack with example: obj = NewtonFoolAttack(steps, stepsize)