code: def testFairnessAucs(self):
      temp_eval_export_dir = self._getEvalExportDir()
      (
          _,
          eval_export_dir,
      ) = fixed_prediction_estimator_extra_fields.simple_fixed_prediction_estimator_extra_fields(
          None, temp_eval_export_dir
      )
      examples = [
          # Subgroup
          self._makeExample(
              prediction=0.0000, label=0.0000, fixed_int=1
          ),
          self._makeExample(
              prediction=0.0000, label=1.0000, fixed_int=1
          ),
          self._makeExample(
              prediction=1.0000, label=0.0000, fixed_int=1
          ),
          self._makeExample(
              prediction=1.0000, label=1.0000, fixed_int=1
          ),
          # Background
          self._makeExample(
              prediction=0.0000, label=0.0000, fixed_int=0
          ),
          self._makeExample(
              prediction=0.0000, label=1.0000, fixed_int=0
          ),
          self._makeExample(
              prediction=1.0000, label=0.0000, fixed_int=0
          ),
          self._makeExample(
              prediction=1.0000, label=1.0000, fixed_int=0
          ),
      ]
      fairness_auc = post_export_metrics.fairness_auc(
          subgroup_key="fixed_int"
      )
  
      def check_result(got):
          try:
              self.assertEqual(1, len(got), "got: %s" % got)
              (slice_key, value) = got[0]
              self.assertEqual((), slice_key)
              expected_value = {
                  # Subgroup
                  "post_export_metrics/fairness/auc/subgroup_auc/fixed_int": 0.5,
                  "post_export_metrics/fairness/auc/subgroup_auc/fixed_int/lower_bound": 0.25,
                  "post_export_metrics/fairness/auc/subgroup_auc/fixed_int/upper_bound": 0.75,
                  # BNSP
                  "post_export_metrics/fairness/auc/bnsp_auc/fixed_int": 0.5,
                  "post_export_metrics/fairness/auc/bnsp_auc/fixed_int/lower_bound": 0.25,
                  "post_export_metrics/fairness/auc/bnsp_auc/fixed_int/upper_bound": 0.75,
                  # BPSN
                  "post_export_metrics/fairness/auc/bpsn_auc/fixed_int": 0.5,
                  "post_export_metrics/fairness/auc/bpsn_auc/fixed_int/lower_bound": 0.25,
                  "post_export_metrics/fairness/auc/bpsn_auc/fixed_int/upper_bound": 0.75,
                  "average_loss": 0.5,
              }
              self.assertDictElementsAlmostEqual(value, expected_value)
          except AssertionError as err:
              raise util.BeamAssertException(err)
  
      self._runTestWithCustomCheck(
          examples,
          eval_export_dir,
          [fairness_auc],
          custom_metrics_check=check_result,
      )
  
imports: import os
  import apache_beam
  from apache_beam.testing import util
  import tensorflow
  from tensorflow_model_analysis import constants
  from tensorflow_model_analysis.addons.fairness.post_export_metrics import fairness_indicators
  from tensorflow_model_analysis.api import model_eval_lib
  from tensorflow_model_analysis.api import tfma_unit
  from tensorflow_model_analysis.eval_saved_model import testutil
  from tensorflow_model_analysis.eval_saved_model.example_trainers import fixed_prediction_estimator_extra_fields
  from tensorflow_model_analysis.eval_saved_model.example_trainers import multi_head
  from tensorflow_model_analysis.evaluators import legacy_metrics_and_plots_evaluator
  from tensorflow_model_analysis.post_export_metrics import post_export_metrics
  import tensorflow_model_analysis.post_export_metrics.metric_keys
  from tensorflow_model_analysis.proto import config_pb2
  from tensorflow_model_analysis.proto import metrics_for_slice_pb2
  from tensorflow_model_analysis.slicer import slicer_lib
  from tfx_bsl.tfxio import raw_tf_record
label_desc: Use image node_id 13 for calling the FairnessIndicatorsTest obj's underlying member method code with example usage: obj.testFairnessAucs() without return types