code: def _example_to_dict(
      example: bytes,
  ) -> Dict[str, Optional[np.ndarray]]:
      """Converts serialized tf.Example to Python dictionary."""
      example = tf.train.Example.FromString(example)
      result = {}
      # Sort the produced dict by keys to make the order deterministic.
      for name, feature in sorted(example.features.feature.items()):
          kind = feature.WhichOneof("kind")
          # Use None if the value kind is not set (can occur for passthrough values).
          result[name] = (
              None
              if kind is None
              else np.array(
                  getattr(feature, kind).value,
                  dtype=_FEATURE_VALUE_KIND_TO_NP_DTYPE[kind],
              )
          )
      return result
  
imports: import functools
  import os
  import re
  from typing import Callable, Dict, List, Mapping, Optional, FrozenSet
  from absl import logging
  import numpy
  import pyarrow
  import tensorflow
  from tensorflow_transform import analyzer_nodes
  from tensorflow_transform import annotators
  from tensorflow_transform import common_types
  from tensorflow_transform import graph_context
  from tensorflow_transform import graph_tools
  from tensorflow_transform import schema_inference
  from tensorflow_transform import tf2_utils
  from tensorflow_transform import tf_utils
  from tensorflow_transform.output_wrapper import TFTransformOutput
  from tensorflow_transform.saved import saved_transform_io
  from tensorflow_transform.saved import saved_transform_io_v2
  from tensorflow_transform.tf_metadata import dataset_metadata
  from tensorflow_transform.tf_metadata import metadata_io
  from tensorflow_transform.tf_metadata import schema_utils
  from tfx_bsl.coders import example_coder
  from tfx_bsl.tfxio import tensor_to_arrow
  from tensorflow.python.eager import function
  from tensorflow.python.framework import ops
  from tensorflow_metadata.proto.v0 import schema_pb2
label_desc: Use image node_id 6 for calling a global function with example usage: _example_to_dict(example) and returns: result