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 score(
      self, context_features=None, example_features=None, training=True
  ):
      example_input = [
          tf.keras.layers.Flatten()(example_features[name])
          for name in sorted(self.example_feature_columns)
      ]
      return self._score_layer(tf.concat(example_input, axis=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 2 for calling the _DummyUnivariateRankingNetwork obj's underlying member method code with example usage: obj.score(context_features, example_features, training) and returns: self