@combinations.generate(strategy_and_optimizer_combinations())
def test_fit_eval_and_predict_with_optimizer(self, distribution, optimizer):
    with self.cached_session():
        model = get_model()
        loss = 'mse'
        model.compile(optimizer(), loss, distribute=distribution)
        dataset = get_dataset(distribution)
        model.fit(dataset, epochs=1, steps_per_epoch=2, verbose=1)
        model.evaluate(dataset, steps=2, verbose=1)
        model.predict(get_predict_dataset(distribution), steps=2)
@combinations.generate(strategy_and_optimizer_combinations())
def test_fit_eval_and_predict_with_optimizer(self, distribution, optimizer):
    with self.cached_session():
        model = get_model()
        loss = 'mse'
        model.compile(optimizer(), loss, distribute=distribution)
        dataset = get_dataset(distribution)
        model.fit(dataset, epochs=1, steps_per_epoch=2, verbose=1)
        model.evaluate(dataset, steps=2, verbose=1)
        model.predict(get_predict_dataset(distribution), steps=2)