class_docstr: A constraint on BERT-Score difference.
  
  Args:
      min_bert_score (float), minimum threshold value for BERT-Score
      model_name (str), name of model to use for scoring
      num_layers (int), number of hidden layers in the model
      score_type (str), Pick one of following three choices
  
          -(1) ``precision`` : match words from candidate text to reference text
          -(2) ``recall`` :  match words from reference text to candidate text
          -(3) ``f1``: harmonic mean of precision and recall (recommended)
  
      compare_against_original (bool):
          If ``True``, compare new ``x_adv`` against the original ``x``.
          Otherwise, compare it against the previous ``x_adv``.
code: def extra_repr_keys(self):
      return [
          "min_bert_score",
          "model",
          "score_type",
      ] + super().extra_repr_keys()
  
file_path: TextAttack/textattack/constraints/semantics/bert_score.py
imports: import bert_score
  from textattack.constraints import Constraint
  from textattack.shared import utils
label_desc: Use image node_id 4 for calling the BERTScore obj's underlying member method code with example usage: obj.extra_repr_keys() and returns: unknown