code: def _score_flattened(
      self,
      context_features: Dict[str, tf.Tensor],
      example_features: Dict[str, tf.Tensor],
  ) -> Dict[str, tf.Tensor]:
      f = next(iter(example_features.values()))
      return {
          "task1": tf.keras.layers.Dense(1)(f),
          "task2": tf.keras.layers.Dense(1)(f),
      }
  
file_path: ranking/tensorflow_ranking/python/keras/pipeline_test.py
imports: import os
  from typing import Dict
  from absl.testing import parameterized
  import tensorflow
  from tensorflow_ranking.python.keras import model
  from tensorflow_ranking.python.keras import pipeline
  from google.protobuf import text_format
  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