import tensorflow as tf

            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
        height, width = 150, 150
        num_classes = 1000

        train_inputs = tf.random_uniform((train_batch_size, height, width, 3))
        mobilenet_v1.mobilenet_v1(train_inputs, num_classes)
        eval_inputs = tf.random_uniform((eval_batch_size, height, width, 3))
        logits, _ = mobilenet_v1.mobilenet_v1(eval_inputs, num_classes,
                                              reuse=True)
        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, (eval_batch_size,))

    def testLogitsNotSqueezed(self):
        num_classes = 25
