class_docstr: A constraint on the distance between two sentences' thought vectors.
  
  Args:
      word_embedding (textattack.shared.AbstractWordEmbedding): The word embedding to use
class_docstr_tok: ["A","constraint","on","the","distance","between","two","sentences","'","thought","vectors",".","Args",":","word_embedding","(","textattack.shared.AbstractWordEmbedding",")",":","The","word","embedding","to","use"]
code: def encode(self, raw_text_list):
      return torch.stack(
          [self._get_thought_vector(text) for text in raw_text_list]
      )
  
file_path: TextAttack/textattack/constraints/semantics/sentence_encoders/thought_vector.py
imports: import functools
  import torch
  from textattack.shared import AbstractWordEmbedding, WordEmbedding, utils
  from .sentence_encoder import SentenceEncoder
label_desc: Use image node_id 4 for calling the ThoughtVector obj's underlying member method code with example usage: obj.encode(raw_text_list) and returns: torch