code: def __init__(
      self, data_path, mapping, bart_name, learn_weights
  ) -> None:
      self.data_path = data_path
      self.bart_name = bart_name
      self.tokenizer = (
          BertTokenizer.from_pretrained(self.bart_name)
          if "chinese" in self.bart_name
          else BartTokenizer.from_pretrained(self.bart_name)
      )
      self.mapping = mapping  # 记录的是原始tag与转换后的tag的str的匹配关系
      self.original_token_nums = self.tokenizer.vocab_size
      self.learn_weights = learn_weights
      self._add_tags_to_tokens()
  
file_path: DeepKE/src/deepke/name_entity_re/few_shot/module/datasets.py
imports: import torch
  from tqdm import tqdm
  import numpy
  from itertools import chain
  from torch.utils.data import Dataset, DataLoader
  from torch.nn.utils.rnn import pad_sequence
  from transformers import BartTokenizer, BertTokenizer
  import logging
label_desc: Use image node_id 1 to create a new ConllNERProcessor object from inherited base classes: object with example: obj = ConllNERProcessor(data_path, mapping, bart_name, learn_weights)