class_docstr: Constraint using similarity between sentence encodings of x and x_adv
  where the text embeddings are created using the Universal Sentence
  Encoder.
code: def encode(self, sentences):
      if not self.model:
          self.model = hub.load(self._tfhub_url)
      encoding = self.model(sentences)
  
      if isinstance(encoding, dict):
          encoding = encoding["outputs"]
  
      return encoding.numpy()
  
file_path: TextAttack/textattack/constraints/semantics/sentence_encoders/universal_sentence_encoder/universal_sentence_encoder.py
imports: from textattack.constraints.semantics.sentence_encoders import SentenceEncoder
  from textattack.shared.utils import LazyLoader
label_desc: Use image node_id 2 for calling the UniversalSentenceEncoder obj's underlying member method code with example usage: obj.encode(sentences) and returns: encoding