code: def test_create_keras_model(self, size_feature_name, list_size):
      network = _DummyUnivariateRankingNetwork(
          context_feature_columns=self.context_feature_columns,
          example_feature_columns=self.example_feature_columns,
      )
      ranker = model_lib.create_keras_model(
          network=network,
          loss=self.loss,
          metrics=self.metrics,
          optimizer=self.optimizer,
          size_feature_name=size_feature_name,
          list_size=list_size,
      )
      self.assertEqual(ranker.optimizer, self.optimizer)
      self.assertEqual(ranker.loss, self.loss)
      if size_feature_name:
          self.assertIn("example_list_size", ranker.input_names)
      else:
          self.assertNotIn("example_list_size", ranker.input_names)
  
imports: from absl.testing import parameterized
  import tensorflow
  from google.protobuf import text_format
  from tensorflow_ranking.python import data
  from tensorflow_ranking.python.keras import feature
  from tensorflow_ranking.python.keras import losses
  from tensorflow_ranking.python.keras import metrics
  from tensorflow_ranking.python.keras import model
  from tensorflow_ranking.python.keras import network
  from tensorflow_serving.apis import input_pb2
label_desc: Use image node_id 2 for calling the FunctionalRankingModelTest obj's underlying member method code with example usage: obj.test_create_keras_model(size_feature_name, list_size) without return types