code: def __getitem__(self, index):
      specific_class_name = self.labels[index % self.num_classes]
      data = self.data[specific_class_name]
      general_class_name = data.attrs["label_general"]
      transform = self.get_transform(index, self.transform)
      target_transform = self.get_target_transform(index)
  
      return TieredImagenetDataset(
          index,
          data,
          general_class_name,
          specific_class_name,
          transform=transform,
          target_transform=target_transform,
      )
  
imports: import numpy
  from PIL import Image
  import h5py
  import json
  import os
  import io
  import pickle
  from torchmeta.utils.data import Dataset, ClassDataset, CombinationMetaDataset
  from torchmeta.datasets.utils import download_file_from_google_drive
label_desc: Use image node_id 4 for calling the TieredImagenetClassDataset obj's underlying member method code with example usage: obj.__getitem__(index) and returns: TieredImagenetDataset