code: def __call__(self, data):
      batch = {}
      batch["input_ids"] = torch.cat(
          [f[0] for f in data] + [f[2] for f in data], dim=0
      )
      batch["attention_mask"] = torch.cat(
          [f[1] for f in data] + [f[3] for f in data], dim=0
      )
      return batch
  
imports: import torch
  from torch.utils.data import Dataset, Subset, ConcatDataset
  from torch.nn.utils.rnn import pad_sequence
  import torch.nn.functional
  from datasets import load_dataset
  import numpy
  import os
  import hashlib
  from itertools import chain
  from dschat.utils.data import raw_datasets
  from deepspeed.accelerator import get_accelerator
label_desc: Use image node_id 1 for calling the DataCollatorReward obj's underlying member method code with example usage: obj.__call__(data) and returns: batch