code: def collater(self, samples):
      # TODO For now only supports datasets with same underlying collater implementations
  
      all_keys = set()
      for s in samples:
          all_keys.update(s)
  
      shared_keys = all_keys
      for s in samples:
          shared_keys = shared_keys & set(s.keys())
  
      samples_shared_keys = []
      for s in samples:
          samples_shared_keys.append(
              {k: s[k] for k in s.keys() if k in shared_keys}
          )
  
      return self.datasets[0].collater(samples_shared_keys)
  
file_path: lavis/lavis/datasets/datasets/base_dataset.py
imports: import json
  from typing import Iterable
  import pandas
  import torch
  from torch.utils.data import Dataset, ConcatDataset
  from torch.utils.data.dataloader import default_collate
label_desc: Use image node_id 2 for calling the ConcatDataset obj's underlying member method code with example usage: obj.collater(samples) and returns: self