code: def test_huber_loss(self):
      with self.cached_session():
          predicted = tf.constant(
              [[0, 10], [10, 0], [10, 0], [10, 0]],
              dtype=tf.float32,
              name="predicted",
          )
          gold_standard = tf.constant(
              [[0, 10], [10, 0], [10, 0], [10, 0]],
              dtype=tf.float32,
              name="gold_standard",
          )
          self.assertEqual(
              huber_loss(predicted, gold_standard).eval(), 0.0
          )
  
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 1 for calling the HuberLossTests obj's underlying member method code with example usage: obj.test_huber_loss() without return types