def METHOD_NAME(self):
    config = {}
    for k, v in iter(self._fn_kwargs.items()):
        config[k] = tf.keras.backend.eval(v) if is_tensor_or_variable(v) else v
    base_config = super().METHOD_NAME()
    return {**base_config, **config}