Handle backwards compatibility where .sdf.csv exists storing tasks

  def get_shards(self, input_files, shard_size):

    """Defines a generator which returns data for each shard"""

    return load_sdf_files(input_files, self.clean_mols, self.tasks)

    return load_sdf_files(input_files, self.clean_mols, tasks=self.tasks)

  def featurize_shard(self, shard):

    """Featurizes a shard of an input dataframe."""

    suppl = Chem.SDMolSupplier(str(input_file), clean_mols, False, False)

    df_rows = []

    for ind, mol in enumerate(suppl):

      if mol is not None:

      if mol is None:

        continue

      smiles = Chem.MolToSmiles(mol)

      df_row = [ind, smiles, mol]

      if not has_csv:  # Get task targets from .sdf file

        for task in tasks:

          df_row.append(mol.GetProp(str(task)))

      df_rows.append(df_row)

    mol_df = pd.DataFrame(

        df_rows, columns=('mol_id', 'smiles', 'mol') + tuple(tasks))

    # Tasks are stored either in .sdf.csv file

    if has_csv:

      mol_df = pd.DataFrame(df_rows, columns=('mol_id', 'smiles', 'mol'))

      raw_df = next(load_csv_files([input_file + ".csv"], shard_size=None))

      dataframes.append(pd.concat([mol_df, raw_df], axis=1, join='inner'))

    else:

      mol_df = pd.DataFrame(

        df_rows, columns=('mol_id', 'smiles', 'mol') + tuple(tasks))

      dataframes.append(mol_df)

  return dataframes