docstr: initialize with the necessary elements
docstr_tok: ["initialize","with","the","necessary","elements"]
code: def __init__(self, user_dict=None):
      """
      initialize with the necessary elements
      """
      self.default_pretrained_model_path = os.path.join(
          self.directory, "infer_model", "model"
      )
      self.word2id_dict = load_kv_dict(
          os.path.join(self.directory, "assets/word.dic"),
          reverse=True,
          value_func=int,
      )
      self.id2word_dict = load_kv_dict(
          os.path.join(self.directory, "assets/word.dic")
      )
      self.label2id_dict = load_kv_dict(
          os.path.join(self.directory, "assets/tag.dic"),
          reverse=True,
          value_func=int,
      )
      self.id2label_dict = load_kv_dict(
          os.path.join(self.directory, "assets/tag.dic")
      )
      self.word_replace_dict = load_kv_dict(
          os.path.join(self.directory, "assets/q2b.dic")
      )
      self.oov_id = self.word2id_dict["OOV"]
      self.word_dict_len = max(map(int, self.word2id_dict.values())) + 1
      self.label_dict_len = (
          max(map(int, self.label2id_dict.values())) + 1
      )
      self.tag_file = os.path.join(
          self.directory, "assets/tag_file.txt"
      )
  
      if user_dict:
          self.set_user_dict(dict_path=user_dict)
      else:
          self.custom = None
  
      self._set_config()
  
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 1 to create a new LAC object  with example: obj = LAC(user_dict)