class_docstr: Abstract class for defining CLStreams whose size
  (number of experiences) is known.
class_docstr_tok: ["Abstract","class","for","defining","CLStreams","whose","size","(","number","of","experiences",")","is","known","."]
code: def __init__(
      self: TCLStream,
      name: str,
      exps_iter: Iterable[TCLExperience],
      benchmark: "Optional[CLScenario[TCLStream]]" = None,
      set_stream_info: bool = True,
  ):
      super().__init__(
          name=name,
          exps_iter=exps_iter,
          benchmark=benchmark,
          set_stream_info=set_stream_info,
      )
  
imports: from abc import abstractmethod, ABC
  from contextlib import contextmanager
  from copy import copy
  from enum import Enum
  from types import GeneratorType
  from typing import Any, Dict, Generator, Iterator, List, Iterable, Optional, Sequence, Tuple, TypeVar, Union, Generic, overload
  from typing_extensions import final
  import numpy
  from avalanche.benchmarks.utils.dataset_utils import slice_alike_object_to_indices
label_desc: Use image node_id 1 to create a new SizedCLStream object from inherited base classes: CLStream, ABC with example: obj = SizedCLStream(name, exps_iter, benchmark, set_stream_info)