docstr: Calculate the score
  
  :param str transformed_texts: transformed sentence
  :param str reference_text: origin sentence
  :return float: the score of two sentence
code: def validate(self, transformed_texts, reference_text):
      r"""
      Calculate the score
  
      :param str transformed_texts: transformed sentence
      :param str reference_text: origin sentence
      :return float: the score of two sentence
  
      """
      transformed_embeddings = self.encode(transformed_texts)
      reference_embeddings = self.encode(reference_text).expand(
          transformed_embeddings.size(0), -1
      )
      scores = self.sim_metric(
          transformed_embeddings, reference_embeddings
      )
  
      return float(scores.numpy())
  
file_path: textflint/textflint/generation/validator/sentence_encoding.py
imports: import torch
  from transformers import AutoModel, AutoTokenizer
  from .validator import Validator
label_desc: Use image node_id 3 for calling the SentenceEncoding obj's underlying member method code with example usage: obj.validate(transformed_texts, reference_text) and returns: float