code: def _make_plain_experience(
      stream: DatasetStream[DatasetExperience[TCLDataset]],
      experience_idx: int,
  ) -> DatasetExperience[TCLDataset]:
      dataset = stream.benchmark.stream_definitions[
          stream.name
      ].exps_data[experience_idx]
  
      return DatasetExperience(
          current_experience=experience_idx,
          origin_stream=stream,
          benchmark=stream.benchmark,
          dataset=dataset,
      )
  
file_path: avalanche/avalanche/benchmarks/scenarios/deprecated/generators.py
imports: from typing import TYPE_CHECKING, Sequence, Optional, Dict, TypeVar, Union, Any, List, Callable, Set, Tuple
  import torch
  from avalanche.benchmarks.scenarios.dataset_scenario import split_validation_random
  from avalanche.benchmarks.scenarios.deprecated.classification_scenario import ClassificationScenario
  from avalanche.benchmarks.scenarios.deprecated.dataset_scenario import DatasetScenario, DatasetStream, FactoryBasedStream, StreamDef, TStreamsUserDict
  from avalanche.benchmarks.scenarios.detection_scenario import DetectionScenario
  from avalanche.benchmarks.scenarios.deprecated.generic_benchmark_creation import *
  from avalanche.benchmarks.scenarios.deprecated import DatasetExperience
  from avalanche.benchmarks.scenarios.deprecated.lazy_dataset_sequence import LazyDatasetSequence
  from avalanche.benchmarks.scenarios.deprecated.new_classes.nc_scenario import NCScenario
  from avalanche.benchmarks.scenarios.deprecated.new_instances.ni_scenario import NIScenario
  from avalanche.benchmarks.scenarios.online import FixedSizeExperienceSplitter
  from avalanche.benchmarks.utils.classification_dataset import SupportedDataset, _as_taskaware_supervised_classification_dataset, _make_taskaware_classification_dataset, _concat_taskaware_classification_datasets_sequentially
label_desc: Use image node_id 4 for calling a global function with example usage: _make_plain_experience(stream, experience_idx) and returns: DatasetExperience