code: def decode(self, vectors):
      if self._mode == "concat":
          vec_size = self.cae.output_size
  
          output = []
          for vec in vectors:
              viewed_vec = vec.view(-1, vec_size)
  
              # Find index of first padding vector
              for index, v in enumerate(viewed_vec):
                  if v.abs().sum() == 0:
                      break
              else:
                  index = viewed_vec.size(0)
  
              out = self.cae.decode(viewed_vec[:index])
  
              output.append(out)
  
          return output
  
      elif self._mode == "mean":
          raise ValueError('decode is only defined for mode="concat"')
      else:
          self._unexpected_mode()
  
file_path: lightwood/lightwood/encoder/text/short.py
imports: from typing import List
  import torch
  from lightwood.encoder import BaseEncoder
  from lightwood.encoder.categorical import CategoricalAutoEncoder
  from type_infer.rule_based.helpers import tokenize_text
  from lightwood.helpers.torch import concat_vectors_and_pad, average_vectors
  import pandas
label_desc: Use image node_id 7 for calling the ShortTextEncoder obj's underlying member method code with example usage: obj.decode(vectors) and returns: output