import tensorflow as tf

                            normalizer_fn=slim.batch_norm):
            mobilenet_v1.mobilenet_v1_base(inputs)
            total_params, _ = slim.model_analyzer.analyze_vars(
                slim.get_model_variables())
            self.assertAlmostEqual(3217920, total_params)

    def testBuildEndPointsWithDepthMultiplierLessThanOne(self):
        batch_size = 5
        height, width = 224, 224
        num_classes = 1000

        inputs = tf.random_uniform((batch_size, height, width, 3))
        _, end_points = mobilenet_v1.mobilenet_v1(inputs, num_classes)

        endpoint_keys = [key for key in end_points.keys() if key.startswith('Conv')]

        _, end_points_with_multiplier = mobilenet_v1.mobilenet_v1(
            inputs, num_classes, scope='depth_multiplied_net',
            depth_multiplier=0.5)

        for key in endpoint_keys:
            original_depth = end_points[key].get_shape().as_list()[3]
