old_contents: from deepchem.feat import MolecularFeaturizer
  from transformers import RobertaTokenizerFast
  from deepchem.utils.typing import RDKitMol
  
  
  class RobertaFeaturizer(RobertaTokenizerFast, MolecularFeaturizer):
  
    def __init__(self, **kwargs):
      super().__init__(**kwargs)
      return
  
    def _featurize(self, mol: RDKitMol, **kwargs):
      """Calculate encoding using HuggingFace's RobertaTokenizerFast
  
          Parameters
          ----------
          mol: rdkit.Chem.rdchem.Mol
            RDKit Mol object
  
          Returns
          -------
          np.ndarray
            1D array of RDKit descriptors for `mol`. The length is 881.
  
          """
      try:
        from rdkit import Chem
      except ModuleNotFoundError:
        raise ImportError("This class requires RDKit to be installed.")
      smiles_string = Chem.MolToSmiles(mol)
      # the encoding is natively a dictionary with keys 'input_ids' and 'attention_mask'
      # -> make this a list of two arrays to allow np to handle it
      encoding = list(self(smiles_string, **kwargs).values())
      return encoding
  
    def __call__(self, *args, **kwargs):
      return super().__call__(*args, **kwargs)
  
new_contents: from deepchem.feat import MolecularFeaturizer
  from transformers import RobertaTokenizerFast
  from deepchem.utils.typing import RDKitMol
  
  from typing import Dict, List
  
  
  class RobertaFeaturizer(RobertaTokenizerFast, MolecularFeaturizer):
  
    def __init__(self, **kwargs):
      super().__init__(**kwargs)
      return
  
    def _featurize(self, mol: RDKitMol, **kwargs) -> List[List[int]]:
      """Calculate encoding using HuggingFace's RobertaTokenizerFast
  
          Parameters
          ----------
          mol: rdkit.Chem.rdchem.Mol
            RDKit Mol object
  
          Returns
          -------
          encoding: List
            List containing two lists; the `input_ids` and the `attention_mask`
  
          """
      try:
        from rdkit import Chem
      except ModuleNotFoundError:
        raise ImportError("This class requires RDKit to be installed.")
      smiles_string = Chem.MolToSmiles(mol)
      # the encoding is natively a dictionary with keys 'input_ids' and 'attention_mask'
      # -> make this a list of two arrays to allow np to handle it
      encoding = list(self(smiles_string, **kwargs).values())
      return encoding
  
    def __call__(self, *args, **kwargs) -> Dict[str, List[int]]:
      return super().__call__(*args, **kwargs)
  
subject: update docstrings