code: def __init__(
      self,
      dataset: AvalancheDataset,
      reversed_indices: Dict[int, int],
      collate_fn=None,
  ):
      self.dataset: AvalancheDataset = dataset
      self.reversed_indices: Dict[int, int] = reversed_indices
  
      all_data_attributes = self.dataset._data_attributes.values()
      self.get_item_data_attributes = list(
          filter(lambda x: x.use_in_getitem, all_data_attributes)
      )
  
      self.collate_fn = (
          collate_fn
          if collate_fn is not None
          else self.dataset.collate_fn
      )
  
      if self.collate_fn is None:
          raise RuntimeError("Undefined collate function")
  
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 1 to create a new _GetItemDataset object  with example: obj = _GetItemDataset(dataset, reversed_indices, collate_fn)