code: def _fixed_size_split(
      online_benchmark: "OnlineCLScenario",  # TODO: Deprecated
      # and unused. Remove.
      experience_size: int,
      access_task_boundaries: bool,
      shuffle: bool,
      s: Iterable[DatasetExperience[TCLDataset]],
  ) -> CLStream[DatasetExperience[TCLDataset]]:
      return split_online_stream(
          original_stream=s,
          experience_size=experience_size,
          access_task_boundaries=access_task_boundaries,
          shuffle=shuffle,
      )
  
imports: from functools import partial
  import random
  from typing import Callable, Generator, Generic, Iterable, List, Optional, TypeVar, Union, Protocol
  from typing_extensions import Literal
  import warnings
  from avalanche.benchmarks.utils.data import AvalancheDataset
  from avalanche.benchmarks.utils.utils import concat_datasets
  import torch
  from torch.distributions.categorical import Categorical
  from torch.utils.data import Sampler
  from .deprecated.benchmark_wrapper_utils import wrap_stream
  from .generic_scenario import CLStream, CLScenario
  from .dataset_scenario import DatasetExperience
label_desc: Use image node_id 3 for calling a global function with example usage: _fixed_size_split(online_benchmark, experience_size, access_task_boundaries, shuffle, s) and returns: split_online_stream