class_docstr: A memory-efficient constant sequence.
docstr: Constructor
  
  :param constant_value: the fixed value
  :param size: length of the sequence
docstr_tok: ["Constructor",":","param","constant_value",":","the","fixed","value",":","param","size",":","length","of","the","sequence"]
code: def __init__(self, constant_value: DataT, size: int):
      """Constructor
  
      :param constant_value: the fixed value
      :param size: length of the sequence
      """
      self._constant_value = constant_value
      self._size = size
      self._can_flatten = False
      self._indices = None
  
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 1 to create a new ConstantSequence object from inherited base classes: IDataset, Sequence with example: obj = ConstantSequence(constant_value, size)