def METHOD_NAME(self):
    K.clear_session()
    DCRM = build_discriminator()
    GEN = build_generator()
    IMAGE = Input(shape=g_input_shape)
    GENERATED_IMAGE = GEN(IMAGE)
    CONF_GENERATED_IMAGE = DCRM(GENERATED_IMAGE)
    keras_model = Model(IMAGE, [CONF_GENERATED_IMAGE, GENERATED_IMAGE])
    g_input_shape_batch = (2,) + g_input_shape
    data = np.random.rand(*g_input_shape_batch).astype(np.float32)
    expected = keras_model.predict(data)
    onnx_model = mock_keras2onnx.convert_keras(keras_model, keras_model.name)
    self.assertTrue(
        run_keras_and_ort(onnx_model.graph.name, onnx_model, keras_model, data, expected, self.model_files,
                          atol=1e-2, rtol=1e-2))