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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def bundle_attacks_with_goal(sess, model, x, y, adv_x, attack_configs, run_counts, goal, report, report_path, attack_batch_size=BATCH_SIZE, eval_batch_size=BATCH_SIZE):
 """ Runs attack bundling, working on one specific AttackGoal. This function is mostly intended to be called by `bundle_attacks`. Reference: https://openreview.net/forum?id=H1g0piA9tQ :param sess: tf.session.Session :param model: cleverhans.model.Model :param x: numpy array containing clean example inputs to attack :param y: numpy array containing true labels :param adv_x: numpy array containing the adversarial examples made so far by earlier work in the bundling process :param attack_configs: list of AttackConfigs to run :param run_counts: dict mapping AttackConfigs to numpy arrays specifying how many times they have been run on each example :param goal: AttackGoal to run :param report: ConfidenceReport :param report_path: str, the path the report will be saved to :param attack_batch_size: int, batch size for generating adversarial examples :param eval_batch_size: int, batch size for evaluating the model on adversarial examples """

  goal.start(run_counts)
  _logger.info("Running criteria for new goal...")
  criteria = goal.get_criteria(sess, model, adv_x, y, batch_size=eval_batch_size)
  assert 'correctness' in criteria
  _logger.info("Accuracy: " + str(criteria['correctness'].mean()))
  assert 'confidence' in criteria
  while not goal.is_satisfied(criteria, run_counts):
    run_batch_with_goal(sess, model, x, y, adv_x, criteria, attack_configs,
                        run_counts,
                        goal, report, report_path,
                        attack_batch_size=attack_batch_size)
  # Save after finishing all goals.
  # The incremental saves run on a timer. This save is needed so that the last
  # few attacks after the timer don't get discarded
  report.completed = True
  save(criteria, report, report_path, adv_x)