class_docstr: Executor for [Evaluator](https://www.tensorflow.org/tfx/guide/evaluator).
docstr: Given a feature slicing spec, returns a List of SingleSliceSpecs.
  
  Args:
    spec: slice specification.
  
  Returns:
    List of corresponding SingleSliceSpecs. Always includes the overall slice,
    even if it was not specified in the given spec.
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code: def _get_slice_spec_from_feature_slicing_spec(
      self, spec: evaluator_pb2.FeatureSlicingSpec
  ) -> List[tfma.slicer.SingleSliceSpec]:
      """Given a feature slicing spec, returns a List of SingleSliceSpecs.
  
      Args:
        spec: slice specification.
  
      Returns:
        List of corresponding SingleSliceSpecs. Always includes the overall slice,
        even if it was not specified in the given spec.
      """
      result = []
      for single_spec in spec.specs:
          columns = single_spec.column_for_slicing
          result.append(tfma.slicer.SingleSliceSpec(columns=columns))
      # Always include the overall slice.
      if tfma.slicer.SingleSliceSpec() not in result:
          result.append(tfma.slicer.SingleSliceSpec())
      return result
  
imports: import os
  from typing import Any, Dict, List
  from absl import logging
  import apache_beam
  import tensorflow_model_analysis
  import tensorflow_model_analysis.addons.fairness.post_export_metrics.fairness_indicators
  from tfx import types
  from tfx.components.evaluator import constants
  from tfx.components.util import udf_utils
  from tfx.components.util import tfxio_utils
  from tfx.dsl.components.base import base_beam_executor
  from tfx.proto import evaluator_pb2
  from tfx.types import artifact_utils
  from tfx.types import standard_component_specs
  from tfx.utils import io_utils
  from tfx.utils import json_utils
  from tfx.utils import path_utils
  from tfx.utils import proto_utils
  from tfx_bsl.tfxio import tensor_adapter
label_desc: Use image node_id 1 for calling the Executor obj's underlying member method code with example usage: obj._get_slice_spec_from_feature_slicing_spec(spec) and returns: result