class_docstr: Dummy univariate ranking network with a simple scoring function.
class_docstr_tok: ["Dummy","univariate","ranking","network","with","a","simple","scoring","function","."]
code: def __init__(
      self,
      context_feature_columns=None,
      example_feature_columns=None,
      name="dummy_ranking_network",
      **kwargs,
  ):
      super(_DummyUnivariateRankingNetwork, self).__init__(
          context_feature_columns=context_feature_columns,
          example_feature_columns=example_feature_columns,
          name=name,
          **kwargs,
      )
      self._score_layer = tf.keras.layers.Dense(units=1)
  
imports: import os
  from absl.testing import parameterized
  import tensorflow
  from tensorflow import estimator
  from tensorflow.compat.v1 import estimator
  from google.protobuf import text_format
  from tensorflow_ranking.python import data
  from tensorflow_ranking.python.keras import estimator
  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 to create a new _DummyUnivariateRankingNetwork object from inherited base classes: network with example: obj = _DummyUnivariateRankingNetwork(context_feature_columns, example_feature_columns, name)