class_docstr: A helper class that represents a string that can be attacked.
  
  Models that take multiple sentences as input separate them by ``SPLIT_TOKEN``.
  Attacks "see" the entire input, joined into one string, without the split token.
  
  ``AttackedText`` instances that were perturbed from other ``AttackedText``
  objects contain a pointer to the previous text
  (``attack_attrs["previous_attacked_text"]``), so that the full chain of
  perturbations might be reconstructed by using this key to form a linked
  list.
  
  Args:
     text (string): The string that this AttackedText represents
     attack_attrs (dict): Dictionary of various attributes stored
         during the course of an attack.
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code: def newly_swapped_words(self) -> List[str]:
      return [
          self.attack_attrs["prev_attacked_text"].words[i]
          for i in self.attack_attrs["newly_modified_indices"]
      ]
  
imports: from __future__ import annotations
  from collections import OrderedDict
  import math
  from typing import Dict, Iterable, List, Optional, Set, Tuple
  import flair
  from flair.data import Sentence
  import numpy
  import torch
  import textattack
  from .utils import device, words_from_text
label_desc: Use image node_id 32 for calling the AttackedText obj's underlying member method code with example usage: obj.newly_swapped_words() and returns: unknown