code: def build_sequence_example_serving_input_receiver_fn(
      input_size,
      context_feature_spec,
      example_feature_spec,
      default_batch_size=None,
  ):
      """Creates a serving_input_receiver_fn for `SequenceExample` inputs.
  
      A string placeholder is used for inputs. Note that the context_feature_spec
      and example_feature_spec shouldn't contain weights, labels or training
      only features in general.
  
      Args:
        input_size: (int) The number of frames to keep in a SequenceExample. If
          specified, truncation or padding may happen. Otherwise, set it to None to
          allow dynamic list size (recommended).
        context_feature_spec: (dict) Map from feature keys to `FixedLenFeature` or
          `VarLenFeature` values.
        example_feature_spec: (dict) Map from  feature keys to `FixedLenFeature` or
          `VarLenFeature` values.
        default_batch_size: (int) Number of query examples 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.
      """
      return build_ranking_serving_input_receiver_fn(
          SEQ,
          context_feature_spec,
          example_feature_spec,
          list_size=input_size,
          receiver_name="sequence_example",
          default_batch_size=default_batch_size,
      )
  
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 14 for calling a global function with example usage: build_sequence_example_serving_input_receiver_fn(input_size, context_feature_spec, example_feature_spec, default_batch_size) and returns: build_ranking_serving_input_receiver_fn