code: def create_bounded_result(self):
      return EvalResult(
          slicing_metrics=[
              (
                  (),
                  {
                      "": {
                          "": {
                              "post_export_metrics/negative_rate@0.10": {
                                  "boundedValue": {
                                      "lowerBound": 0.07,
                                      "upperBound": 0.09,
                                      "value": 0.08,
                                      "methodology": "POISSON_BOOTSTRAP",
                                  }
                              },
                              "accuracy": {
                                  "boundedValue": {
                                      "lowerBound": 0.07,
                                      "upperBound": 0.09,
                                      "value": 0.444,
                                      "methodology": "POISSON_BOOTSTRAP",
                                  }
                              },
                          }
                      }
                  },
              ),
              (
                  (("gender", "female"),),
                  {
                      "": {
                          "": {
                              "post_export_metrics/negative_rate@0.10": {
                                  "boundedValue": {
                                      "lowerBound": 0.07,
                                      "upperBound": 0.09,
                                      "value": 0.09,
                                      "methodology": "POISSON_BOOTSTRAP",
                                  }
                              },
                              "accuracy": {
                                  "boundedValue": {
                                      "lowerBound": 0.07,
                                      "upperBound": 0.09,
                                      "value": 0.333,
                                      "methodology": "POISSON_BOOTSTRAP",
                                  }
                              },
                          }
                      }
                  },
              ),
              (
                  (
                      ("gender", "female"),
                      (
                          "sexual_orientation",
                          "homosexual_gay_or_lesbian",
                      ),
                  ),
                  {
                      "": {
                          "": {
                              "post_export_metrics/negative_rate@0.10": {
                                  "boundedValue": {
                                      "lowerBound": 0.07,
                                      "upperBound": 0.09,
                                      "value": 0.1,
                                      "methodology": "POISSON_BOOTSTRAP",
                                  }
                              },
                              "accuracy": {
                                  "boundedValue": {
                                      "lowerBound": 0.07,
                                      "upperBound": 0.09,
                                      "value": 0.222,
                                      "methodology": "POISSON_BOOTSTRAP",
                                  }
                              },
                          }
                      }
                  },
              ),
          ]
      )
  
file_path: fairness-indicators/fairness_indicators/remediation/weight_utils_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  from fairness_indicators.remediation import weight_utils
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling the WeightUtilsTest obj's underlying member method code with example usage: obj.create_bounded_result() and returns: EvalResult