code: def _score_flattened(self, context_features, example_features):
      return {
          "task1": tf.convert_to_tensor([[1.0], [2.0], [3.0]]),
          "task2": tf.convert_to_tensor([[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 1 for calling the DummyMultiTaskScorer obj's underlying member method code with example usage: obj._score_flattened(context_features, example_features) and returns: dict