How to use the chemprop.features.atom_features function in chemprop

:return: A string representing the featurization of the substructure.
    """
    if fg_features is None:
        fg_features = [None] * mol.GetNumAtoms()

    substructure = list(substructure)
    atoms = [Chem.Mol.GetAtomWithIdx(mol, idx) for idx in substructure]
    bonds = []
    for i in range(len(substructure)):
        for j in range(i + 1, len(substructure)):
            a1, a2 = substructure[i], substructure[j]
            bond = mol.GetBondBetweenAtoms(a1, a2)
            if bond is not None:
                bonds.append(bond)

    features = [str(atom_features(atom, fg_features[atom.GetIdx()])) for atom in atoms] + \
               [str(bond_features(bond)) for bond in bonds]
    features.sort()  # ensure identical feature string for different atom/bond ordering
    features = str(features)

    return features

if vocab_func not in ['atom', 'atom_features', 'feature_vector', 'substructure']:
        raise ValueError(f'vocab_func "{vocab_func}" not supported.')

    mol = Chem.MolFromSmiles(smiles)
    atoms = mol.GetAtoms()

    if args is not None and \
            ('functional_group' in args.additional_atom_features or
             'functional_group' in args.additional_output_features):
        fg_featurizer = FunctionalGroupFeaturizer(args)
        fg_features = fg_featurizer.featurize(mol)
    else:
        fg_features = [None] * len(atoms)

    if vocab_func == 'feature_vector':
        features = [atom_features(atom, fg) for atom, fg in zip(atoms, fg_features)]
    elif vocab_func == 'atom_features':
        features = [str(atom_features(atom, fg)) for atom, fg in zip(atoms, fg_features)]
    elif vocab_func == 'atom':
        features = [str(atom.GetAtomicNum()) for atom in atoms]
    elif vocab_func == 'substructure':
        substructures = get_substructures(list(atoms), substructure_sizes)
        features = [substructure_to_feature(mol, substructure, fg_features) for substructure in substructures]
    else:
        raise ValueError(f'vocab_func "{vocab_func}" not supported.')

    if nb_info:
        nb_indices = []
        for atom in atoms:
            nb_indices.append([nb.GetIdx() for nb in atom.GetNeighbors()])  # atoms are sorted by idx

        return features, nb_indices

mol = Chem.MolFromSmiles(smiles)
    atoms = mol.GetAtoms()

    if args is not None and \
            ('functional_group' in args.additional_atom_features or
             'functional_group' in args.additional_output_features):
        fg_featurizer = FunctionalGroupFeaturizer(args)
        fg_features = fg_featurizer.featurize(mol)
    else:
        fg_features = [None] * len(atoms)

    if vocab_func == 'feature_vector':
        features = [atom_features(atom, fg) for atom, fg in zip(atoms, fg_features)]
    elif vocab_func == 'atom_features':
        features = [str(atom_features(atom, fg)) for atom, fg in zip(atoms, fg_features)]
    elif vocab_func == 'atom':
        features = [str(atom.GetAtomicNum()) for atom in atoms]
    elif vocab_func == 'substructure':
        substructures = get_substructures(list(atoms), substructure_sizes)
        features = [substructure_to_feature(mol, substructure, fg_features) for substructure in substructures]
    else:
        raise ValueError(f'vocab_func "{vocab_func}" not supported.')

    if nb_info:
        nb_indices = []
        for atom in atoms:
            nb_indices.append([nb.GetIdx() for nb in atom.GetNeighbors()])  # atoms are sorted by idx

        return features, nb_indices

    return features