class_docstr: Constraint that uses the Google 1 Billion Words Language Model to
  determine the difference in perplexity between x and x_adv.
  
  Args:
      top_n (int):
      top_n_per_index (int):
      compare_against_original (bool):  If `True`, compare new `x_adv` against the original `x`.
          Otherwise, compare it against the previous `x_adv`.
code: def __init__(
      self,
      top_n=None,
      top_n_per_index=None,
      compare_against_original=True,
  ):
      if not (top_n or top_n_per_index):
          raise ValueError(
              "Cannot instantiate GoogleLanguageModel without top_n or top_n_per_index"
          )
      self.lm = GoogLMHelper()
      self.top_n = top_n
      self.top_n_per_index = top_n_per_index
      super().__init__(compare_against_original)
  
file_path: TextAttack/textattack/constraints/grammaticality/language_models/google_language_model/google_language_model.py
imports: from collections import defaultdict
  import numpy
  from textattack.constraints import Constraint
  from textattack.transformations import WordSwap
  from .alzantot_goog_lm import GoogLMHelper
label_desc: Use image node_id 1 to create a new GoogleLanguageModel object from inherited base classes: Constraint with example: obj = GoogleLanguageModel(top_n, top_n_per_index, compare_against_original)