code: def test_huber_loss_hand_example(self):
      with self.cached_session():
          # loss should be: mean( 0.2 ** 2/ 2 + (2-0.5) ) == 1.52/2 == 0.76
          predicted = tf.constant(
              [1.2, 1], dtype=tf.float32, name="predicted"
          )
          gold_standard = tf.constant(
              [1, 3], dtype=tf.float32, name="gold_standard"
          )
          loss = huber_loss(predicted, gold_standard, delta=1.0)
          self.assertAlmostEqual(loss.eval(), 0.76)
  
imports: from __future__ import absolute_import, print_function
  import tensorflow
  from niftynet.layer.loss_regression import LossFunction
  from niftynet.layer.loss_regression import l1_loss, l2_loss, huber_loss, smooth_l1_loss, cosine_loss
  from tests.niftynet_testcase import NiftyNetTestCase
label_desc: Use image node_id 3 for calling the HuberLossTests obj's underlying member method code with example usage: obj.test_huber_loss_hand_example() without return types