@combinations.generate(combinations.combine(distribution=[combinations.tpu_strategy_one_step], mode=['graph']))
def test_dataset_input_shape_fully_defined(self, distribution):
    with self.cached_session():
        model = get_model()
        optimizer = rmsprop.RMSPropOptimizer(learning_rate=0.001)
        loss = 'mse'
        model.compile(optimizer, loss, distribute=distribution)
        dataset = get_dataset(distribution)
        dataset = dataset.repeat(100).batch(10)
        with self.assertRaisesRegexp(ValueError, 'requires fully defined shapes'):
            model.fit(dataset, epochs=1, steps_per_epoch=2, verbose=0)
@combinations.generate(combinations.combine(distribution=[combinations.tpu_strategy_one_step], mode=['graph']))
def test_dataset_input_shape_fully_defined(self, distribution):
    with self.cached_session():
        model = get_model()
        optimizer = rmsprop.RMSPropOptimizer(learning_rate=0.001)
        loss = 'mse'
        model.compile(optimizer, loss, distribute=distribution)
        dataset = get_dataset(distribution)
        dataset = dataset.repeat(100).batch(10)
        with self.assertRaisesRegexp(ValueError, 'requires fully defined shapes'):
            model.fit(dataset, epochs=1, steps_per_epoch=2, verbose=0)