code: def _deserialize_single_field(
      example_data, tensor_info: feature_lib.TensorInfo
  ):
      """Reconstruct the serialized field."""
      # Ragged tensor case:
      if tensor_info.sequence_rank > 1:
          example_data = _dict_to_ragged(example_data, tensor_info)
  
      # Restore shape if possible. TF Example flattened it.
      elif tensor_info.shape.count(None) < 2:
          shape = [-1 if i is None else i for i in tensor_info.shape]
          example_data = tf.reshape(example_data, shape)
  
      # Restore dtype
      if example_data.dtype != tensor_info.tf_dtype:
          example_data = tf.dtypes.cast(
              example_data, tensor_info.tf_dtype
          )
      return example_data
  
imports: from __future__ import annotations
  import abc
  from collections.abc import Iterable, Mapping, Sequence
  import dataclasses
  import re
  from typing import Any, Union
  import numpy
  from tensorflow_datasets.core import utils
  from tensorflow_datasets.core.features import feature
  from tensorflow_datasets.core.utils import dtype_utils
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  from tensorflow_datasets.proto import tf_example_pb2
  from tensorflow_datasets.proto import tf_feature_pb2
label_desc: Use image node_id 9 for calling a global function with example usage: _deserialize_single_field(example_data, tensor_info) and returns: example_data