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: Define the bounds for the image `img` within the limits `limit`.
docstr_tok: ["Define","the","bounds","for","the","image","`","img","`","within","the","limits","`","limit","`","."]
code: def _get_bounds(
      self, img: np.ndarray, limit
  ) -> Tuple[List[list], list]:
      """
      Define the bounds for the image `img` within the limits `limit`.
      """
  
      def bound_limit(value):
          return np.clip(value - limit, 0, 255), np.clip(
              value + limit, 0, 255
          )
  
      minbounds, maxbounds, bounds, initial = [], [], [], []
  
      for i, j, k in product(
          range(img.shape[-3]),
          range(img.shape[-2]),
          range(img.shape[-1]),
      ):
          temp = img[i, j, k]
          initial += [temp]
          bound = bound_limit(temp)
          if self.es == 0:  # pragma: no cover
              minbounds += [bound[0]]
              maxbounds += [bound[1]]
          else:
              bounds += [bound]
      if self.es == 0:
          bounds = [minbounds, maxbounds]
  
      return bounds, initial
  
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 5 for calling the PixelThreshold obj's underlying member method code with example usage: obj._get_bounds(img, limit) and returns: bounds,  initial, np,  np