code: def _default_online_split(
      shuffle: bool,
      drop_last: bool,
      access_task_boundaries: bool,
      exp: DatasetExperience,
      size: int,
  ):
      return FixedSizeExperienceSplitter(
          experience=exp,
          experience_size=size,
          shuffle=shuffle,
          drop_last=drop_last,
          access_task_boundaries=access_task_boundaries,
      )
  
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 1 for calling a global function with example usage: _default_online_split(shuffle, drop_last, access_task_boundaries, exp, size) and returns: FixedSizeExperienceSplitter