text: from onehot import onehot
  from util import save_onehot
  from util import load_onehot, save_word2vec
  from word2vec import word2vec
  
  if __name__ == '__main__':
      data = open('./data/part.txt', mode='r', encoding='utf8')
      # sentences = []
      # for line in data.readlines():
      #     line = line.strip('\n')
      #     sentences.append(line.split(' '))
      # voca = onehot(sentences)
      # w = word2vec(100, 1, 3)
      # w.train(sentences)
      w = load_onehot('data/word2vec.model')
      print(w.calc_similarity('实木床', '质量'))
  
  