code: def testEvalResultGetMetrics(self, class_id, k, top_k):
      # Slices
      num_slices = 2
      overall_slice = ()
      male_slice = ("gender", "male")
  
      # Output name
      output_name = ""
  
      # Metrics for overall slice
      metrics_overall = {
          "accuracy": {
              "doubleValue": 0.5,
          },
          "auc": {
              "doubleValue": 0.8,
          },
      }
  
      # Metrics for male slice
      metrics_male = {
          "accuracy": {
              "doubleValue": 0.8,
          },
          "auc": {
              "doubleValue": 0.5,
          },
      }
  
      # EvalResult
      if all(v is None for v in [class_id, k, top_k]):
          sub_key = ""
      else:
          sub_key = str(metric_types.SubKey(class_id, k, top_k))
      slicing_metrics = [
          (overall_slice, {output_name: {sub_key: metrics_overall}}),
          (male_slice, {output_name: {sub_key: metrics_male}}),
      ]
      eval_result = view_types.EvalResult(
          slicing_metrics, None, None, None, None, None, None
      )
  
      # Test get_metrics_for_all_slices()
      actual_metrics = eval_result.get_metrics_for_all_slices(
          class_id=class_id, k=k, top_k=top_k
      )
  
      # Assert there is one metrics entry per slice
      self.assertLen(actual_metrics, num_slices)
  
      # Assert the metrics match the expected values
      self.assertDictEqual(
          actual_metrics[overall_slice], metrics_overall
      )
      self.assertDictEqual(actual_metrics[male_slice], metrics_male)
  
      # Test get_metrics_for_slice()
      self.assertDictEqual(
          eval_result.get_metrics_for_slice(
              class_id=class_id, k=k, top_k=top_k
          ),
          metrics_overall,
      )
      self.assertDictEqual(
          eval_result.get_metrics_for_slice(
              slice_name=male_slice, class_id=class_id, k=k, top_k=top_k
          ),
          metrics_male,
      )
  
      # Test get_metric_names()
      self.assertSameElements(
          eval_result.get_metric_names(), ["accuracy", "auc"]
      )
  
      # Test get_slice_names()
      self.assertListEqual(
          eval_result.get_slice_names(), [overall_slice, male_slice]
      )
  
imports: from absl.testing import parameterized
  import tensorflow
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.view import view_types
label_desc: Use image node_id 1 for calling the ViewTypesTest obj's underlying member method code with example usage: obj.testEvalResultGetMetrics(class_id, k, top_k) without return types