def test_training_args_call_build(self): input_dim = 2 model = model_util.TrainingNoDefaultModel() self.assertFalse(model.built, 'Model should not have been built') self.assertFalse(model.weights, ('Model should have no weights since it ' 'has not been built.')) model.build((None, input_dim)) self.assertTrue(model.weights, ('Model should have weights now that it ' 'has been properly built.')) self.assertTrue(model.built, 'Model should be built after calling `build`.')
def test_training_no_default(self): if not tf.executing_eagerly(): return model = model_util.TrainingNoDefaultModel() arg = tf.ones([1, 1]) model(arg, True)