class_docstr: A layer that produces dense `Tensors` from context and example features.
docstr: Constructs a ListwiseDenseFeatures layer.
  
  Args:
   context_feature_columns: (dict) context feature names to columns.
   example_feature_columns: (dict) example feature names to columns.
   name: (str) name of the layer.
   **kwargs: keyword arguments.
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code: def __init__(
      self,
      context_feature_columns=None,
      example_feature_columns=None,
      name="listwise_dense_features",
      **kwargs,
  ):
      """Constructs a ListwiseDenseFeatures layer.
  
      Args:
       context_feature_columns: (dict) context feature names to columns.
       example_feature_columns: (dict) example feature names to columns.
       name: (str) name of the layer.
       **kwargs: keyword arguments.
      """
      super(EncodeListwiseFeatures, self).__init__(name=name, **kwargs)
      self._context_feature_columns = context_feature_columns
      self._example_feature_columns = example_feature_columns
      if self._context_feature_columns:
          self._context_dense_layer = tf.keras.layers.DenseFeatures(
              feature_columns=six.itervalues(
                  self._context_feature_columns
              ),
              name=name,
          )
      self._example_dense_layer = tf.keras.layers.DenseFeatures(
          feature_columns=six.itervalues(self._example_feature_columns),
          name=name,
      )
  
imports: import six
  import tensorflow.compat.v2
  from tensorflow.python.feature_column import feature_column_lib
  from tensorflow_ranking.python import utils
label_desc: Use image node_id 1 to create a new EncodeListwiseFeatures object from inherited base classes: tf.keras.layers with example: obj = EncodeListwiseFeatures(context_feature_columns, example_feature_columns, name)