code: def vectorize(self, tokens, remove_oov=False, norm=False):
          
          if not tokens:
              raise ValueError("You supplied an empty list.")
          index = list(self.bow(tokens, remove_oov=remove_oov))
          if not index:
              raise ValueError("You supplied a list with only OOV tokens: {}, "
                               "which then got removed. Set remove_oov to False,"
                               " or filter your sentences to remove any in which"
                               " all items are OOV.")
          if norm:
              return np.stack([self.norm_vectors[x] for x in index])
          else:
              return np.stack([self.vectors[x] for x in index])
docs: Vectorize a sentence by replacing all items with their vectors.
  
          Parameters
          ----------
          tokens : object or list of objects
              The tokens to vectorize.
          remove_oov : bool, optional, default False
              Whether to remove OOV items. If False, OOV items are replaced by
              the UNK glyph. If this is True, the returned sequence might
              have a different length than the original sequence.
          norm : bool, optional, default False
              Whether to return the unit vectors, or the regular vectors.
  
          Returns
          -------
          s : numpy array
              An M * N matrix, where every item has been replaced by
              its vector. OOV items are either removed, or replaced
              by the value of the UNK glyph.