code: def create_bytes_list_feature_list(
      name, key, prefix="", module_dict=None
  ):
      """Creates accessor functions for list of bytes feature lists.
  
      The provided functions are has_${NAME}, get_${NAME}_size, get_${NAME}_at,
      clear_${NAME}, and add_${NAME}.
  
      example = tensorflow.train.SequenceExample()
      add_bbox_label_string(["dog", "cat"], example)
      add_bbox_label_string(["cat", "dog"], example)
      if has_bbox_label_string:
        for i in range(get_bbox_label_string_size(example):
          timestamp = get_bbox_label_string_at(i, example)
        clear_bbox_label_string(example)
  
      Args:
        name: the name of the feature to use in function names.
        key: the key for this feature in the SequenceExample.
        prefix: a prefix to append to the key in the SequenceExample
        module_dict: adds the functions to the corresponding module dict.
      """
  
      def _has(sequence_example, prefix=prefix):
          return has_feature_list(key, sequence_example, prefix=prefix)
  
      def _get_size(sequence_example, prefix=prefix):
          return get_feature_list_size(
              key, sequence_example, prefix=prefix
          )
  
      def _get_at(index, sequence_example, prefix=prefix):
          return get_bytes_list_at(
              key, index, sequence_example, prefix=prefix
          )
  
      def _clear(sequence_example, prefix=prefix):
          clear_feature_list(key, sequence_example, prefix=prefix)
  
      def _add(value, sequence_example, prefix=prefix):
          add_bytes_list(key, value, sequence_example, prefix=prefix)
  
      def _get_key(prefix=prefix):
          return merge_prefix(prefix, key)
  
      def _get_default_parser():
          return tf.io.VarLenFeature(tf.string)
  
      function_dict = {
          "has_" + name: _has,
          "get_" + name + "_size": _get_size,
          "get_" + name + "_at": _get_at,
          "clear_" + name: _clear,
          "add_" + name: _add,
          "get_" + name + "_key": _get_key,
          "get_" + name + "_default_parser": _get_default_parser,
      }
      add_functions_to_module(function_dict, module_dict)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import types
  import tensorflow.compat.v1
label_desc: Use image node_id 42 for calling a global function with example usage: create_bytes_list_feature_list(name, key, prefix, module_dict) and returns: has_feature_list, get_feature_list_size, get_bytes_list_at, merge_prefix, tf