class_docstr: These attacks were originally implemented by Vargas et al. (2019) & Su et al.(2019).
  
  | One Pixel Attack Paper link: https://arxiv.org/abs/1710.08864
  | Pixel and Threshold Attack Paper link: https://arxiv.org/abs/1906.06026
docstr: Rescale inputs
docstr_tok: ["Rescale","inputs"]
code: def rescale_input(self, x):
      """Rescale inputs"""
      x = x.astype(ART_NUMPY_DTYPE) / 255.0
      x = (
          x
          * (
              self.estimator.clip_values[1]
              - self.estimator.clip_values[0]
          )
      ) + self.estimator.clip_values[0]
      return x
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  from itertools import product
  from typing import List, Optional, Tuple, TYPE_CHECKING
  import numpy
  from six import string_types
  import scipy
  from scipy._lib._util import check_random_state
  from scipy.optimize import OptimizeResult, minimize
  from tqdm.auto import tqdm
  from art.config import ART_NUMPY_DTYPE
  from art.attacks.attack import EvasionAttack
  from art.estimators.estimator import BaseEstimator, NeuralNetworkMixin
  from art.estimators.classification.classifier import ClassifierMixin
  from art.utils import check_and_transform_label_format
label_desc: Use image node_id 3 for calling the PixelThreshold obj's underlying member method code with example usage: obj.rescale_input(x) and returns: x