docstr: Returns the datasets's ``TaskSet``, which is a mapping <task-id,
  task-dataset>.
docstr_tok: ["Returns","the","datasets","'s","``","TaskSet","``",",","which","is","a","mapping","<","task-id",",","task-dataset",">","."]
code: def task_set(
      self: TClassificationDataset,
  ) -> TaskSet[TClassificationDataset]:
      """Returns the datasets's ``TaskSet``, which is a mapping <task-id,
      task-dataset>."""
      return TaskSet(self)
  
imports: from functools import partial
  import torch
  from torch.utils.data.dataset import Subset, ConcatDataset, TensorDataset
  from avalanche.benchmarks.utils.utils import TaskSet, _count_unique, find_common_transforms_group, _init_task_labels, _init_transform_groups, _split_user_def_targets, _split_user_def_task_label, _traverse_supported_dataset
  from avalanche.benchmarks.utils.data import AvalancheDataset
  from avalanche.benchmarks.utils.transform_groups import TransformGroupDef, DefaultTransformGroups, XTransform, YTransform
  from avalanche.benchmarks.utils.data_attribute import DataAttribute
  from avalanche.benchmarks.utils.dataset_utils import SubSequence
  from avalanche.benchmarks.utils.flat_data import ConstantSequence
  from avalanche.benchmarks.utils.dataset_definitions import ISupportedClassificationDataset, ITensorDataset, IDatasetWithTargets
  from typing import List, Any, Sequence, Union, Optional, TypeVar, Callable, Dict, Tuple, Mapping, overload
label_desc: Use image node_id 2 for calling the TaskAwareClassificationDataset obj's underlying member method code with example usage: obj.task_set() and returns: TaskSet