examples/research_projects/mlm_wwm/run_chinese_ref.py/main
def main(args):
    # For Chinese (Ro)Bert, the best result is from : RoBERTa-wwm-ext (https://github.com/ymcui/Chinese-BERT-wwm)
    # If we want to fine-tune these model, we have to use same tokenizer : LTP (https://github.com/HIT-SCIR/ltp)
    with open(args.file_name, "r", encoding="utf-8") as f:
        data = f.readlines()
    data = [line.strip() for line in data if len(line) > 0 and not line.isspace()]  # avoid delimiter like '\u2029'
    ltp_tokenizer = LTP(args.ltp)  # faster in GPU device
    bert_tokenizer = BertTokenizer.from_pretrained(args.bert)

    ref_ids = prepare_ref(data, ltp_tokenizer, bert_tokenizer)

    with open(args.save_path, "w", encoding="utf-8") as f:
        data = [json.dumps(ref) + "\n" for ref in ref_ids]
        f.writelines(data)