class_docstr: Helper class to store data about images generated by attacks.
docstr: Initializes instance of AttacksOutput class.
  
  Args:
    dataset_dir: location of the dataset.
    attacks_output_dir: where to write results of attacks.
    targeted_attacks_output_dir: where to write results of targeted attacks.
    all_adv_examples_dir: directory to copy all adversarial examples from
      all attacks.
    epsilon: maximum allowed size of adversarial perturbation.
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code: def __init__(
      self,
      dataset_dir,
      attacks_output_dir,
      targeted_attacks_output_dir,
      all_adv_examples_dir,
      epsilon,
  ):
      """Initializes instance of AttacksOutput class.
  
      Args:
        dataset_dir: location of the dataset.
        attacks_output_dir: where to write results of attacks.
        targeted_attacks_output_dir: where to write results of targeted attacks.
        all_adv_examples_dir: directory to copy all adversarial examples from
          all attacks.
        epsilon: maximum allowed size of adversarial perturbation.
      """
      self.attacks_output_dir = attacks_output_dir
      self.targeted_attacks_output_dir = targeted_attacks_output_dir
      self.all_adv_examples_dir = all_adv_examples_dir
      self._load_dataset_clipping(dataset_dir, epsilon)
      self._output_image_idx = 0
      self._output_to_attack_mapping = {}
      self._attack_image_count = 0
      self._targeted_attack_image_count = 0
      self._attack_names = set()
      self._targeted_attack_names = set()
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import argparse
  import csv
  import json
  import os
  import subprocess
  import numpy
  from PIL import Image
label_desc: Use image node_id 1 to create a new AttacksOutput object from inherited base classes: object with example: obj = AttacksOutput(dataset_dir, attacks_output_dir, targeted_attacks_output_dir, all_adv_examples_dir, epsilon)