code: def test_eval(self):
      with tf.Graph().as_default():
          metric_fns = {
              "metric/precision@1": metrics_lib.make_ranking_metric_fn(
                  metrics_lib.RankingMetricKey.PRECISION, topn=1
              ),
          }
          head = ranking_head.create_ranking_head(
              loss_fn=_make_loss_fn(), eval_metric_fns=metric_fns
          )
  
          # Create estimator spec.
          spec = head.create_estimator_spec(
              features={},
              mode=tf_estimator.ModeKeys.EVAL,
              logits=self._default_logits,
              labels=self._default_labels,
          )
  
          expected_metrics = [
              "labels_mean",
              "logits_mean",
              "metric/precision@1",
          ]
  
          # Assert spec contains expected tensors.
          self.assertIsNotNone(spec.loss)
          self.assertIsNone(spec.train_op)
          self.assertIsNone(spec.export_outputs)
          self.assertItemsEqual(
              expected_metrics, spec.eval_metric_ops.keys()
          )
  
          # Assert predictions, loss, and metrics.
          with self.cached_session() as sess:
              _initialize_variables(self, spec.scaffold)
              self.assertIsNone(spec.scaffold.summary_op)
              update_ops = {
                  k: spec.eval_metric_ops[k][1]
                  for k in spec.eval_metric_ops
              }
              loss, metrics = sess.run((spec.loss, update_ops))
              self.assertAllClose(self._default_loss, loss)
              self.assertItemsEqual(expected_metrics, metrics.keys())
  
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 5 for calling the RankingHeadTest obj's underlying member method code with example usage: obj.test_eval() without return types