class_docstr: Storage Structure of Topic model, including vocabulary and word topic count.
      
code: def load_model(self, word_topic_path, vocab_path):
      # Loading vocabulary
      self.__vocab.load(vocab_path)
  
      self.__beta_sum = self.__beta * self.__vocab.size()
      self.__word_topic = [
          {} for _ in range(self.__vocab.size())
      ]  # 字典列表
      self.__load_word_dict(word_topic_path)
      logger.info(
          "Model Info: #num_topics=%d #vocab_size=%d alpha=%f beta=%f"
          % (
              self.num_topics(),
              self.vocab_size(),
              self.alpha(),
              self.beta(),
          )
      )
  
imports: import os
  from collections import OrderedDict
  import numpy
  from tqdm import tqdm
  from paddlehub.common.logger import logger
  from lda_novel.vocab import Vocab, WordCount
label_desc: Use image node_id 3 for calling the TopicModel obj's underlying member method code with example usage: obj.load_model(word_topic_path, vocab_path) without return types