class_docstr: Implementation of the Geometric Decision-based Attack (GeoDA), a black-box attack requiring class predictions.
  Based on reference implementation: https://github.com/thisisalirah/GeoDA
  
  | Paper link: https://arxiv.org/abs/2003.06468
class_docstr_tok: ["Implementation","of","the","Geometric","Decision-based","Attack","(","GeoDA",")",",","a","black-box","attack","requiring","class","predictions",".","Based","on","reference","implementation",":","https",":","\/\/github.com\/thisisalirah\/GeoDA","|","Paper","link",":","https",":","\/\/arxiv.org\/abs\/2003.06468"]
docstr: Check if example is adversarial.
  
  :param x_adv: Current example.
  :param y_true: True label of `x`.
  :return: Boolean if `x` is mis-classified.
docstr_tok: ["Check","if","example","is","adversarial",".",":","param","x_adv",":","Current","example",".",":","param","y_true",":","True","label","of","`","x","`",".",":","return",":","Boolean","if","`","x","`","is","mis-classified","."]
code: def _is_adversarial(
      self, x_adv: np.ndarray, y_true: np.ndarray
  ) -> bool:
      """
      Check if example is adversarial.
  
      :param x_adv: Current example.
      :param y_true: True label of `x`.
      :return: Boolean if `x` is mis-classified.
      """
      y_prediction = self.estimator.predict(x=x_adv)
  
      if self.targeted:
          return (
              np.argmax(y_prediction, axis=1)[0]
              == np.argmax(y_true, axis=1)[0]
          )
  
      return (
          np.argmax(y_prediction, axis=1)[0]
          != np.argmax(y_true, axis=1)[0]
      )
  
imports: import os
  import math
  import logging
  from typing import List, Optional, Tuple, Union, TYPE_CHECKING
  import numpy
  from tqdm.auto import trange
  from art.attacks.attack import EvasionAttack
  from art.config import ART_NUMPY_DTYPE
  from art.estimators.estimator import BaseEstimator
  from art.estimators.classification.classifier import ClassifierMixin
  from art.utils import check_and_transform_label_format, get_labels_np_array
label_desc: Use image node_id 4 for calling the GeoDA obj's underlying member method code with example usage: obj._is_adversarial(x_adv, y_true) and returns: unknown, unknown