code: def make_avalanche_dataset(
      dataset: IDataset[T_co],
      *,
      data_attributes: Optional[List[DataAttribute]] = None,
      transform_groups: Optional[TransformGroups] = None,
      frozen_transform_groups: Optional[TransformGroups] = None,
      collate_fn: Optional[Callable[[List], Any]] = None,
  ) -> AvalancheDataset[T_co]:
      """Avalanche Dataset.
  
      Creates a ``AvalancheDataset`` instance.
      See ``AvalancheDataset`` for more details.
  
      :param dataset: Original dataset. Beware that
          AvalancheDataset will not overwrite transformations already
          applied by this dataset.
      :param transform_groups: Avalanche transform groups.
      """
      return AvalancheDataset(
          [dataset],
          data_attributes=data_attributes,
          transform_groups=transform_groups,
          frozen_transform_groups=frozen_transform_groups,
          collate_fn=collate_fn,
      )
  
imports: import copy
  import warnings
  import numpy
  from torch.utils.data.dataloader import default_collate
  from avalanche.benchmarks.utils.dataset_definitions import IDataset
  from .data_attribute import DataAttribute
  from typing import Dict, List, Any, Optional, Sequence, TypeVar, Callable, Union, overload
  from .flat_data import FlatData
  from .transform_groups import TransformGroups, EmptyTransformGroups
  from torch.utils.data import Dataset
  from collections import OrderedDict
label_desc: Use image node_id 1 for calling a global function with example usage: make_avalanche_dataset(dataset) and returns: AvalancheDataset