class_docstr: A memory-efficient constant sequence.
code: def __getitem__(
      self, index: Union[int, slice]
  ) -> "Union[DataT, ConstantSequence[DataT]]":
      if isinstance(index, (int, np.integer)):
          index = int(index)
  
          if index >= len(self):
              raise IndexError()
          return self._constant_value
      else:
          slice_indices = slice_alike_object_to_indices(
              slice_alike_object=index, max_length=len(self)
          )
          return ConstantSequence(
              constant_value=self._constant_value,
              size=sum(1 for _ in slice_indices),
          )
  
imports: import bisect
  import sys
  import numpy
  from avalanche.benchmarks.utils.dataset_utils import slice_alike_object_to_indices
  from typing import Iterable, List, Optional, Sequence, Tuple, TypeVar, Union, overload
  from torch.utils.data import ConcatDataset
  import itertools
  from avalanche.benchmarks.utils.dataset_definitions import IDataset
label_desc: Use image node_id 5 for calling the ConstantSequence obj's underlying member method code with example usage: obj.__getitem__(index) and returns: self, ConstantSequence