code: def __iter__(self):
      batch_len = len(self.batch["input"])
      for i in range(batch_len):
          single_sample = {k: v[i] for k, v in self.batch.items()}
          single_sample["index"] = i
          yield single_sample
      raise StopIteration
  
imports: import os
  import re
  import collections
  from medicaltorch import transforms
  from tqdm import tqdm
  import numpy
  import nibabel
  from torch.utils.data import Dataset
  import torch
  from torch._six import string_classes, int_classes
  from PIL import Image
label_desc: Use image node_id 2 for calling the BatchSplit obj's underlying member method code with example usage: obj.__iter__() without return types