code: def test_predict(self):
      with tf.Graph().as_default():
          head = ranking_head.create_ranking_head(
              loss_fn=_make_loss_fn()
          )
          logits = [[1.0, 3.0], [1.0, 2.0]]
          spec = head.create_estimator_spec(
              features={},
              mode=tf_estimator.ModeKeys.PREDICT,
              logits=logits,
          )
  
          # Assert spec contains expected tensors.
          self.assertIsNone(spec.loss)
          self.assertEqual({}, spec.eval_metric_ops)
          self.assertIsNone(spec.train_op)
          self.assertItemsEqual(
              (
                  ranking_head._DEFAULT_SERVING_KEY,
                  "regression",
                  "predict",
              ),
              spec.export_outputs.keys(),
          )
  
          # Assert predictions.
          with self.cached_session() as sess:
              _initialize_variables(self, spec.scaffold)
              self.assertIsNone(spec.scaffold.summary_op)
              predictions = sess.run(spec.predictions)
              self.assertAllClose(logits, predictions)
              self.assertAllClose(
                  logits,
                  sess.run(
                      spec.export_outputs[
                          ranking_head._DEFAULT_SERVING_KEY
                      ].value
                  ),
              )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  from tensorflow import estimator
  from tensorflow_ranking.python import head
  from tensorflow_ranking.python import metrics
label_desc: Use image node_id 4 for calling the RankingHeadTest obj's underlying member method code with example usage: obj.test_predict() without return types