import tensorflow as tf

            fake_loss, tf.trainable_variables('.*/progressive_gan_block_1/.*')),
        _get_grad_norm(
            fake_loss, tf.trainable_variables('.*/progressive_gan_block_2/.*')),
        _get_grad_norm(
            fake_loss, tf.trainable_variables('.*/progressive_gan_block_3/.*'))
    ]

    grad_norms_output = None
    with self.test_session(use_gpu=True) as sess:
      sess.run(tf.global_variables_initializer())
      x1_np = sess.run(x, feed_dict={current_image_id_ph: 0.12})
      x2_np = sess.run(x, feed_dict={current_image_id_ph: 1.8})
      grad_norms_output = np.array([
          sess.run(grad_norms, feed_dict={current_image_id_ph: i})
          for i in range(15)  # total num of images
      ])

    self.assertEqual((2, 16, 16, 3), x1_np.shape)
