code: def _create_test_ranking_models():
      inputs = {}
      inputs["query_length"] = tf.keras.Input(
          name="query_length", shape=(1,), dtype=tf.int64
      )
      inputs["unigrams"] = tf.keras.Input(
          name="unigrams", shape=(None, 1), dtype=tf.string, ragged=True
      )
      inputs["utility"] = tf.keras.Input(
          name="utility", shape=(None, 1), dtype=tf.float32
      )
      inputs[_MASK] = tf.keras.Input(
          name=_MASK, shape=(None,), dtype=tf.bool
      )
      features = inputs
  
      # Create dummy logits.
      logits = tf.ones_like(features["utility"])
      logits = tf.squeeze(logits, axis=-1)
      scores = -tf.ones_like(features["utility"])
      scores = tf.squeeze(scores, axis=-1)
      model = tf.keras.Model(
          inputs=inputs, outputs=logits, name="dummy_ranking_model"
      )
      model_with_dict_output = tf.keras.Model(
          inputs=inputs,
          outputs={"logits": logits, "scores": scores},
          name="dummy_ranking_model_with_dict_output",
      )
      model_with_list_output = tf.keras.Model(
          inputs=inputs,
          outputs=[logits, scores],
          name="dummy_ranking_model_with_list_output",
      )
      return model, model_with_dict_output, model_with_list_output
  
file_path: ranking/tensorflow_ranking/python/keras/saved_model_test.py
imports: import tensorflow
  from google.protobuf import text_format
  from tensorflow_ranking.python.keras import saved_model
  from tensorflow_serving.apis import input_pb2
label_desc: Use image node_id 1 for calling a global function with example usage: _create_test_ranking_models() and returns: model,  model_with_dict_output,  model_with_list_output