add docstrings

class RobertaFeaturizer(RobertaTokenizerFast, MolecularFeaturizer):

  """Roberta Featurizer.

  The Roberta Featurizer is a wrapper class of the Roberta Tokenizer,

  which is used by Huggingface's transformers library for tokenizing large corpuses for Roberta Models.

  Please confirm the details in [1]_.

  Please see https://github.com/huggingface/transformers

  and https://github.com/seyonechithrananda/bert-loves-chemistry for more details.

  Examples

  --------

  >>> from deepchem.feat.molecule_featurizers import RobertaFeaturizer

  >>> smiles = ["Cn1c(=O)c2c(ncn2C)n(C)c1=O", "CC(=O)N1CN(C(C)=O)C(O)C1O"]

  >>> featurizer = RobertaFeaturizer.from_pretrained("seyonec/SMILES_tokenized_PubChem_shard00_160k")

  >>> featurizer.featurize(smiles, add_special_tokens=True, truncation=True)

  References

  ----------

  .. [1] Chithrananda, Seyone, Gabriel Grand, and Bharath Ramsundar (2020): "Chemberta: Large-scale self-supervised 

    pretraining for molecular property prediction." arXiv. preprint. arXiv:2010.09885.

  Note

  -----

  This class requires transformers to be installed.

  RobertaFeaturizer uses dual inheritance with RobertaTokenizerFast in Huggingface for rapid tokenization,

  as well as DeepChem's MolecularFeaturizer class.

  """

  def __init__(self, **kwargs):

    super().__init__(**kwargs)