code: def _standardize_default_value(
      spec: tf.io.FixedLenFeature,
  ) -> tf.io.FixedLenFeature:
      """Converts bytes to strings and unwraps lists with a single element."""
      if spec.default_value is None:
          return spec
      default_value = spec.default_value
      assert isinstance(default_value, list), spec.default_value
      # Convert bytes to string
      if spec.dtype == tf.string:
          # Handle bytes string by trying to decode them (for legacy backwards
          # compatibility) and if failed, keep the default value as bytes.
          def try_decode(value: bytes) -> Union[str, bytes]:
              try:
                  return value.decode("utf-8")
              except UnicodeError:
                  return value
  
          default_value = [try_decode(value) for value in default_value]
      # Unwrap a list with a single element.
      if len(default_value) == 1:
          default_value = default_value[0]
      return tf.io.FixedLenFeature(
          shape=spec.shape,
          dtype=spec.dtype,
          default_value=default_value,
      )
  
imports: import dataclasses
  import typing
  from typing import Dict, List, Mapping, Optional, Tuple, Union
  import tensorflow
  from tensorflow_transform import common_types
  from tensorflow_transform.tf_metadata import schema_utils_legacy
  from tfx_bsl.tfxio import tensor_representation_util
  from tensorflow_metadata.proto.v0 import path_pb2
  from tensorflow_metadata.proto.v0 import schema_pb2
label_desc: Use image node_id 7 for calling a global function with example usage: _standardize_default_value(spec) and returns: tf, spec, value, value