code: def test_multi_task_scorer(self):
      mt_model = model_lib.ModelBuilder(
          input_creator=self._input_creator,
          preprocessor=self._preprocessor,
          scorer=DummyMultiTaskScorer(),
          mask_feature_name="mask",
          name="test_model",
      ).build()
      output = mt_model(
          {
              "context_1": tf.ragged.constant([[3, 1, 4, 1]]),
              "feature_1": tf.convert_to_tensor([[[0.0], [1], [2]]]),
              "feature_2": tf.convert_to_tensor([[[0.0], [1], [2]]]),
              "mask": tf.convert_to_tensor([[True, True, True]]),
          }
      )
      self.assertEqual(len(output), 2)
      self.assertAllEqual(output["task1"].numpy(), [[1.0, 2.0, 3.0]])
      self.assertAllEqual(output["task2"].numpy(), [[2.0, 4.0, 6.0]])
  
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 4 for calling the ModelBuilderTest obj's underlying member method code with example usage: obj.test_multi_task_scorer() without return types