class_docstr: A layer that produces dense `Tensors` from context and example features.
code: def get_config(self):
      config = super(EncodeListwiseFeatures, self).get_config()
  
      config.update(
          {
              "context_feature_columns": serialize_feature_columns(
                  self._context_feature_columns
              ),
              "example_feature_columns": serialize_feature_columns(
                  self._example_feature_columns
              ),
          }
      )
      return config
  
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 5 for calling the EncodeListwiseFeatures obj's underlying member method code with example usage: obj.get_config() and returns: config