code: def collate_fn(self, batch):
      tokens = [inst.tokens for inst in batch]
      pieces = [inst.pieces for inst in batch]
      piece_idxs = [inst.piece_idxs for inst in batch]
      token_lens = [inst.token_lens for inst in batch]
      token_start_idxs = [inst.token_start_idxs for inst in batch]
      triggers = [inst.triggers for inst in batch]
      roles = [inst.roles for inst in batch]
      wnd_ids = [inst.wnd_id for inst in batch]
      knowledge = [inst.knowledge for inst in batch]
      retri_event = [inst.event_types for inst in batch]
      return EEBatch(
          tokens=tokens,
          pieces=pieces,
          piece_idxs=piece_idxs,
          token_lens=token_lens,
          token_start_idxs=token_start_idxs,
          triggers=triggers,
          roles=roles,
          wnd_ids=wnd_ids,
          knowledge=knowledge,
          event_types=retri_event,
      )
  
imports: import json, logging, pickle
  from mimetypes import knownfiles
  from unittest.mock import NonCallableMagicMock
  import torch
  from torch.utils.data import Dataset
  from collections import namedtuple
label_desc: Use image node_id 7 for calling the EEDataset obj's underlying member method code with example usage: obj.collate_fn(batch) and returns: EEBatch