class_docstr: Experience decorator that provides info about classes occurrence over time.
class_docstr_tok: ["Experience","decorator","that","provides","info","about","classes","occurrence","over","time","."]
docstr: List of classes of current and previous experiences.
docstr_tok: ["List","of","classes","of","current","and","previous","experiences","."]
code: def classes_seen_so_far(self) -> List[int]:
      """List of classes of current and previous experiences."""
      ...
  
imports: import warnings
  from copy import copy
  from typing import Iterable, Sequence, Optional, Dict, List, Protocol
  import torch
  from avalanche.benchmarks.utils.classification_dataset import ClassificationDataset, _as_taskaware_supervised_classification_dataset, TaskAwareSupervisedClassificationDataset
  from avalanche.benchmarks.utils.data import AvalancheDataset
  from avalanche.benchmarks.utils.data_attribute import DataAttribute
  from .dataset_scenario import _split_dataset_by_attribute, DatasetExperience
  from ..None import CLScenario, CLStream, EagerCLStream
label_desc: Use image node_id 3 for calling the ClassesTimeline obj's underlying member method code with example usage: obj.classes_seen_so_far() without return types