class_docstr: An object that stores necessary information for saving and loading
  checkpoints.
  
  Args:
      attack_args (textattack.AttackArgs): Arguments of the original attack
      attack_log_manager (textattack.loggers.AttackLogManager): Object for storing attack results
      worklist (deque[int]): List of examples that will be attacked. Examples are represented by their indicies within the dataset.
      worklist_candidates (int): List of other available examples we can attack. Used to get the next dataset element when `attack_n=True`.
      chkpt_time (float): epoch time representing when checkpoint was made
code: def num_maximized_attacks(self):
      return sum(
          isinstance(r, MaximizedAttackResult)
          for r in self.attack_log_manager.results
      )
  
imports: import copy
  import datetime
  import os
  import pickle
  import time
  import textattack
  from textattack.attack_results import FailedAttackResult, MaximizedAttackResult, SkippedAttackResult, SuccessfulAttackResult
  from textattack.shared import logger, utils
label_desc: Use image node_id 7 for calling the AttackCheckpoint obj's underlying member method code with example usage: obj.num_maximized_attacks() and returns: sum