import tensorflow as tf

                             [None, num_classes])
        images = tf.random_uniform((batch_size, height, width, 3))

        with self.test_session() as sess:
            sess.run(tf.global_variables_initializer())
            output = sess.run(logits, {inputs: images.eval()})
            self.assertEqual(output.shape, (batch_size, num_classes))

    def testEvaluation(self):
        batch_size = 2
        height, width = 224, 224
        num_classes = 1000

        eval_inputs = tf.random_uniform((batch_size, height, width, 3))
        logits, _ = mobilenet_v1.mobilenet_v1(eval_inputs, num_classes,
                                              is_training=False)
        predictions = tf.argmax(logits, 1)

        with self.test_session() as sess:
            sess.run(tf.global_variables_initializer())
            output = sess.run(predictions)
            self.assertEqual(output.shape, (batch_size,))

    def testTrainEvalWithReuse(self):
        train_batch_size = 5
        eval_batch_size = 2
