code: def deserialize_slice_spec(
      slice_spec: Union[
          config_pb2.SlicingSpec, config_pb2.CrossSlicingSpec
      ]
  ) -> Union[SingleSliceSpec, CrossSliceSpec]:
      """Creates the appropriate hashable slicing spec object.
  
      Args:
        slice_spec: Proto counnterpart of slicing spec.
  
      Returns:
        The python object of single slice spec or cross slice spec.
  
      Raises:
        NotImplementedError: if the type of slice_spec is not supported.
      """
      if isinstance(slice_spec, config_pb2.SlicingSpec):
          return SingleSliceSpec(spec=slice_spec)
      elif isinstance(slice_spec, config_pb2.CrossSlicingSpec):
          return CrossSliceSpec(spec=slice_spec)
      else:
          raise NotImplementedError(
              f"Not implemented for slice_spec type: {type(slice_spec)}"
          )
  
imports: import itertools
  from typing import Any, Callable, Dict, Generator, Iterable, List, NamedTuple, Optional, Tuple, Union
  import apache_beam
  import numpy
  import tensorflow
  from tensorflow_model_analysis import constants
  from tensorflow_model_analysis.api import types
  from tensorflow_model_analysis.proto import config_pb2
  from tensorflow_model_analysis.proto import metrics_for_slice_pb2
  from tensorflow_model_analysis.slicer import slice_accessor
label_desc: Use image node_id 1 for calling a global function with example usage: deserialize_slice_spec(slice_spec) and returns: SingleSliceSpec, CrossSliceSpec