code: def build_ranking_serving_input_receiver_fn_with_parsing_fn(
      parsing_fn, receiver_name, default_batch_size=None
  ):
      """Returns a receiver function with the provided `parsing_fn`.
  
      Args:
        parsing_fn: (function) It has a single argument parsing_fn(serialized).
          Users can customize this for their own data formats.
        receiver_name: (string) The name for the receiver Tensor that contains the
          serialized data.
        default_batch_size: (int) Number of instances expected per batch. Leave
          unset for variable batch size (recommended).
  
      Returns:
        A `tf.estimator.export.ServingInputReceiver` object, which packages the
        placeholders and the resulting feature Tensors together.
      """
  
      def _serving_input_receiver_fn():
          """Returns a serving input receiver."""
          serialized = tf.compat.v1.placeholder(
              dtype=tf.string,
              shape=[default_batch_size],
              name="input_ranking_tensor",
          )
          receiver_tensors = {receiver_name: serialized}
          features = parsing_fn(serialized)
          return tf_estimator.export.ServingInputReceiver(
              features, receiver_tensors
          )
  
      return _serving_input_receiver_fn
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import abc
  import functools
  import six
  import tensorflow
  from tensorflow import estimator
  from google.protobuf import descriptor_pb2
  from tensorflow_ranking.python import utils
label_desc: Use image node_id 11 for calling a global function with example usage: build_ranking_serving_input_receiver_fn_with_parsing_fn(parsing_fn, receiver_name, default_batch_size) and returns: _serving_input_receiver_fn, tf_estimator