code: def __getitem__(self, indices):
      elements_from_attributes = []
      for idx in indices:
          reversed_idx = self.reversed_indices[int(idx)]
          values = []
          for da in self.get_item_data_attributes:
              values.append(da[reversed_idx])
          elements_from_attributes.append(tuple(values))
  
      return tuple(self.collate_fn(elements_from_attributes))
  
imports: from dataclasses import dataclass
  from pathlib import Path
  from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Union
  from collections import OrderedDict
  import warnings
  import numpy
  import torch
  from torch.utils.data.sampler import Sampler
  from avalanche.benchmarks.scenarios.generic_scenario import CLScenario
  from avalanche.benchmarks.utils.data import AvalancheDataset
  from avalanche.benchmarks.utils.dataset_traversal_utils import flat_datasets_from_benchmark, single_flat_dataset
  from avalanche.benchmarks.utils.utils import concat_datasets
label_desc: Use image node_id 2 for calling the _GetItemDataset obj's underlying member method code with example usage: obj.__getitem__(indices) and returns: tuple