docstr: Tranform the texts(list) to PaddleTensor
  Args:
       texts(list): texts
  Returns:
       np.array, list, list
docstr_tok: ["Tranform","the","texts","(","list",")","to","PaddleTensor","Args",":","texts","(","list",")",":","texts","Returns",":","np.array",",","list",",","list"]
code: def preprocess(self, texts):
      """
      Tranform the texts(list) to PaddleTensor
      Args:
           texts(list): texts
      Returns:
           np.array, list, list
      """
      lod = [0]
      data = []
      for i, text in enumerate(texts):
          text_inds = word_to_ids(
              text,
              self.word2id_dict,
              self.word_replace_dict,
              oov_id=self.oov_id,
          )
          data += text_inds
          lod.append(len(text_inds) + lod[i])
      return np.array(data).astype("int64"), [lod], [lod[-1], 1]
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import argparse
  import ast
  import io
  import math
  import os
  import numpy
  import six
  from paddle.inference import Config
  from paddle.inference import create_predictor
  from .custom import Customization
  from .processor import load_kv_dict
  from .processor import parse_result
  from .processor import word_to_ids
  from paddlehub.module.module import moduleinfo
  from paddlehub.module.module import runnable
  from paddlehub.module.module import serving
  from paddlehub.utils.parser import txt_parser
  from paddlehub.utils.utils import sys_stdin_encoding
label_desc: Use image node_id 6 for calling the LAC obj's underlying member method code with example usage: obj.preprocess(texts) and returns: np,  list,  list