code: def load_tox21(
      featurizer: Union[dc.feat.Featurizer, str] = "ECFP",
      splitter: Union[dc.splits.Splitter, str, None] = "scaffold",
      transformers: List[Union[TransformerGenerator, str]] = [
          "balancing"
      ],
      reload: bool = True,
      data_dir: Optional[str] = None,
      save_dir: Optional[str] = None,
      tasks: List[str] = TOX21_TASKS,
      **kwargs,
  ) -> Tuple[
      List[str], Tuple[Dataset, ...], List[dc.trans.Transformer]
  ]:
      """Load Tox21 dataset
  
      The "Toxicology in the 21st Century" (Tox21) initiative created a public
      database measuring toxicity of compounds, which has been used in the 2014
      Tox21 Data Challenge. This dataset contains qualitative toxicity measurements
      for 8k compounds on 12 different targets, including nuclear receptors and
      stress response pathways.
  
      Random splitting is recommended for this dataset.
  
      The raw data csv file contains columns below:
  
      - "smiles" - SMILES representation of the molecular structure
      - "NR-XXX" - Nuclear receptor signaling bioassays results
      - "SR-XXX" - Stress response bioassays results
  
      please refer to https://tripod.nih.gov/tox21/challenge/data.jsp for details.
  
      Parameters
      ----------
      featurizer: Featurizer or str
          the featurizer to use for processing the data.  Alternatively you can pass
          one of the names from dc.molnet.featurizers as a shortcut.
      splitter: Splitter or str
          the splitter to use for splitting the data into training, validation, and
          test sets.  Alternatively you can pass one of the names from
          dc.molnet.splitters as a shortcut.  If this is None, all the data
          will be included in a single dataset.
      transformers: list of TransformerGenerators or strings
          the Transformers to apply to the data.  Each one is specified by a
          TransformerGenerator or, as a shortcut, one of the names from
          dc.molnet.transformers.
      reload: bool
          if True, the first call for a particular featurizer and splitter will cache
          the datasets to disk, and subsequent calls will reload the cached datasets.
      data_dir: str
          a directory to save the raw data in
      save_dir: str
          a directory to save the dataset in
      tasks: List[str], (optional)
          Specify the set of tasks to load. If no task is specified, then it loads
      the default set of tasks which are NR-AR, NR-AR-LBD, NR-AhR, NR-Aromatase, NR-ER,
      NR-ER-LBD, NR-PPAR-gamma, SR-ARE, SR-ATAD5, SR-HSE, SR-MMP, SR-p53.
  
      References
      ----------
      .. [1] Tox21 Challenge. https://tripod.nih.gov/tox21/challenge/
      """
      loader = _Tox21Loader(
          featurizer,
          splitter,
          transformers,
          tasks,
          data_dir,
          save_dir,
          **kwargs,
      )
      return loader.load_dataset("tox21", reload)
  
file_path: deepchem/deepchem/molnet/load_function/tox21_datasets.py
imports: import os
  import deepchem
  from deepchem.molnet.load_function.molnet_loader import TransformerGenerator, _MolnetLoader
  from deepchem.data import Dataset
  from typing import List, Optional, Tuple, Union
label_desc: Use image node_id 1 for calling a global function with example usage: load_tox21(featurizer, splitter, transformers, reload, data_dir, save_dir, tasks) and returns: loader