你好 about kg-bert HOT 2 OPEN

with open(os.path.join(data_dir, "entity2text.txt"), 'r', encoding='utf') as f:
        ent_lines = f.readlines()
        for line in ent_lines:
            temp = line.strip().split('\t')
            ent2text[temp[0]] = temp[1]

    if data_dir.find("FB15") != -1:
        with open(os.path.join(data_dir, "entity2text.txt"), 'r', encoding='utf') as f:
            ent_lines = f.readlines()
            for line in ent_lines:
                temp = line.strip().split('\t')
                #first_sent_end_position = temp[1].find(".")
                ent2text[temp[0]] = temp[1]#[:first_sent_end_position + 1]              

  tokenizer = BertTokenizer.from_pretrained("D:\\Documents\\code\\pretrained\\bert\\bert-base-cased-vocab.txt", do_lower_case=args.do_lower_case)
  model = BertForSequenceClassification.from_pretrained("D:\\Documents\\code\\pretrained\\bert\\bert-base-cased.tar.gz",
          cache_dir=cache_dir,
          num_labels=num_labels)