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","."]
code: def __getitem__(
      self: TDataWTransform, idx: Union[int, slice]
  ) -> Union[T_co, TDataWTransform]:
      if isinstance(idx, (int, np.integer)):
          elem = self._getitem_recursive_call(
              idx, self._transform_groups.current_group
          )
          return elem  # type: ignore
      else:
          return super().__getitem__(idx)
  
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 4 for calling the _FlatDataWithTransform obj's underlying member method code with example usage: obj.__getitem__(idx) and returns: elem, super