class_docstr: Generic class for attacker steps, under perturbation constraints
  specified by an "origin input" and a perturbation magnitude.
  Must implement project, step, and random_perturb
class_docstr_tok: ["Generic","class","for","attacker","steps",",","under","perturbation","constraints","specified","by","an","``","origin","input","''","and","a","perturbation","magnitude",".","Must","implement","project",",","step",",","and","random_perturb"]
docstr: Given an input (which may be in an alternative parameterization),
  convert it to a valid image (this is implemented as the identity
  function by default as most of the time we use the pixel
  parameterization, but for alternative parameterizations this functino
  must be overriden).
docstr_tok: ["Given","an","input","(","which","may","be","in","an","alternative","parameterization",")",",","convert","it","to","a","valid","image","(","this","is","implemented","as","the","identity","function","by","default","as","most","of","the","time","we","use","the","pixel","parameterization",",","but","for","alternative","parameterizations","this","functino","must","be","overriden",")","."]
code: def to_image(self, x):
      """
      Given an input (which may be in an alternative parameterization),
      convert it to a valid image (this is implemented as the identity
      function by default as most of the time we use the pixel
      parameterization, but for alternative parameterizations this functino
      must be overriden).
      """
      return x
  
imports: import torch
label_desc: Use image node_id 5 for calling the AttackerStep obj's underlying member method code with example usage: obj.to_image(x) and returns: x