code: def encode(self, column_data: List[str]) -> torch.Tensor:
      no_null_sentences = (
          x if x is not None else "" for x in column_data
      )
      output = []
      for sent in no_null_sentences:
          tokens = list(tokenize_text(sent))
          encoded_words = self.cae.encode(tokens)
          encoded_sent = self._combine_fn(encoded_words)
          output.append(torch.Tensor(encoded_sent))
      output = torch.stack(output)
      return output
  
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 6 for calling the ShortTextEncoder obj's underlying member method code with example usage: obj.encode(column_data) and returns: output