code: def collate_fn(self, batch):
      src_tokens, src_seq_len, first = [], [], []
      tgt_tokens, tgt_seq_len, target_span = [], [], []
      if self.mode == "test":
          raw_words = []
          for tup in batch:
              src_tokens.append(tup[0])
              src_seq_len.append(tup[1])
              first.append(tup[2])
              raw_words.append(tup[3])
          src_tokens = pad_sequence(
              src_tokens,
              batch_first=True,
              padding_value=self.data_processor.tokenizer.pad_token_id,
          )
          first = pad_sequence(first, batch_first=True, padding_value=0)
          return (
              src_tokens,
              torch.stack(src_seq_len, 0),
              first,
              raw_words,
          )
  
      for tup in batch:
          src_tokens.append(tup[0])
          tgt_tokens.append(tup[1])
          src_seq_len.append(tup[2])
          tgt_seq_len.append(tup[3])
          first.append(tup[4])
          target_span.append(tup[5])
      src_tokens = pad_sequence(
          src_tokens,
          batch_first=True,
          padding_value=self.data_processor.tokenizer.pad_token_id,
      )
      tgt_tokens = pad_sequence(
          tgt_tokens, batch_first=True, padding_value=1
      )
      first = pad_sequence(first, batch_first=True, padding_value=0)
      return (
          src_tokens,
          tgt_tokens,
          torch.stack(src_seq_len, 0),
          torch.stack(tgt_seq_len, 0),
          first,
          target_span,
      )
  
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 4 for calling the ConllNERDataset obj's underlying member method code with example usage: obj.collate_fn(batch) and returns: src_tokens,  tgt_tokens,  torch,  torch,  first,  target_span, src_tokens,  torch,  first,  raw_words