def METHOD_NAME(
    self, use_input_options
):
    model = sequential.Sequential([core_layers.Dense(10)])
    model.compile(gradient_descent.SGD(), loss="mse")
    input_options = (
        tf.distribute.InputOptions() if use_input_options else None
    )
    history = model.fit(
        dataset_creator.DatasetCreator(
            self._get_dataset_fn(), input_options
        ),
        epochs=10,
        steps_per_epoch=10,
        verbose=0,
    )
    self.assertLen(history.history["loss"], 10)