code: def __next__(self):
      if self.i >= self.len:
          raise StopIteration
      batch = {
          k: v[self.i : self.i + self.batch_size]
          if isinstance(v, Iterable)
          else v
          for k, v in self.data_dict.items()
      }
  
      self.i += self.batch_size
      return batch
  
imports: from typing import Callable, Dict
  import torch
  from torch.utils.data import Dataset
  import torchvision.transforms.functional
  from torchvision import transforms
  import pytorch_lightning
  from collections.abc import Iterable
  from pathlib import Path
  from PIL import Image
  from typing import Tuple
label_desc: Use image node_id 3 for calling the DataDictLoader obj's underlying member method code with example usage: obj.__next__() and returns: batch