class_docstr: Private class used to wrap a dataset with a transformation group.
  
  Do not use outside of this file.
class_docstr_tok: ["Private","class","used","to","wrap","a","dataset","with","a","transformation","group",".","Do","not","use","outside","of","this","file","."]
docstr: Clone dataset.
  This is a shallow copy, i.e. the data attributes are not copied.
docstr_tok: ["Clone","dataset",".","This","is","a","shallow","copy",",","i.e",".","the","data","attributes","are","not","copied","."]
code: def _shallow_clone_dataset(self: TDataWTransform) -> TDataWTransform:
      """Clone dataset.
      This is a shallow copy, i.e. the data attributes are not copied.
      """
      dataset_copy = copy.copy(self)
      dataset_copy._transform_groups = copy.copy(
          dataset_copy._transform_groups
      )
      dataset_copy._frozen_transform_groups = copy.copy(
          dataset_copy._frozen_transform_groups
      )
      return dataset_copy
  
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 9 for calling the _FlatDataWithTransform obj's underlying member method code with example usage: obj._shallow_clone_dataset() and returns: dataset_copy