code: def __init__(
      self,
      name: str,
      benchmark: DatasetScenario,
      *,
      slice_ids: Optional[List[int]] = None,
      set_stream_info: bool = True,
  ):
      super().__init__(
          name=name,
          benchmark=benchmark,
          slice_ids=slice_ids,
          set_stream_info=set_stream_info,
      )
  
imports: from abc import ABC, abstractmethod
  from dataclasses import dataclass
  import re
  from typing import Generic, TypeVar, Union, Sequence, Callable, Optional, Dict, Any, Iterable, List, Set, Tuple, Mapping, TYPE_CHECKING
  from .None import DatasetExperience
  from ..generic_scenario import CLScenario, CLExperience, CLStream, SequenceCLStream
  from .lazy_dataset_sequence import LazyDatasetSequence
  from avalanche.benchmarks.utils import AvalancheDataset
  from torch.utils.data.dataset import Dataset
label_desc: Use image node_id 1 to create a new FactoryBasedStream object from inherited base classes: DatasetStream with example: obj = FactoryBasedStream(name, benchmark)