':wearable:generateDebugResources': FROM_CACHE,
        ':wearable:javaPreCompileDebug': FROM_CACHE,
        ':wearable:kaptDebugKotlin': SKIPPED,
        ':wearable:kaptGenerateStubsDebugKotlin': SKIPPED,
        ':wearable:mapDebugSourceSetPaths': SUCCESS,
        ':wearable:mergeDebugAssets': SUCCESS,
        ':wearable:mergeDebugGlobalSynthetics': FROM_CACHE,

		},
		{
			name: "one RemovePod() is skipped",
			plugins: []*TestPlugin{
				{
					name: "success1",
				},
				{
					name: "skipped",
					// To confirm it's skipped, return error so that this test case will fail when it isn't skipped.
					inj: injectedResult{PreFilterRemovePodStatus: int(framework.Error)},
				},
			},
			skippedPluginNames: sets.New("skipped"),
			wantStatusCode:     framework.Success,

				"oldSelf.v == 'old' && self.v == 'new'",
			},
		},
		{name: "skipped transition rule for nil old primitive",
			expectSkipped: true,
			obj:           "exists",
			oldObj:        nil,
			schema:        &stringType,
			valid: []string{
				"oldSelf == self",
			},
		},
		{name: "skipped transition rule for nil old array",
			expectSkipped: true,
			obj:           []interface{}{},

		},
		"overlapping intervals, corrupted completed interval skipped": {
			completedIndexesStr: "0,2-4,x,6-8,12-19",
			failedIndexesStr:    "1,8,9-10",
			completions:         20,
			wantError:           errors.New("failedIndexes and completedIndexes overlap at index: 8"),
		},
		"overlapping intervals, corrupted failed interval skipped": {
			completedIndexesStr: "0,2-4,6-8,12-19",

  // Queue of functions being processed.
  llvm::DenseSet<func::FuncOp> queue_set_;
  std::queue<func::FuncOp> queue_;

  int64_t graph_version_;

  // Op types for which shape inference should be skipped.
  llvm::SmallDenseSet<TypeID> ops_to_skip_;

  // TODO(b/154065712): Remove propagate_caller_callee_constants once using
  // SCCP pass instead.
  bool propagate_caller_callee_constants_;

	// It's ok to ignore the error, returning error is not expected from this function.
	// If an error case occurred during the function generation, this error case(skipped one) will also trigger an error
	// while the generated function is executed. And those errors will be handled during the execution of the generated
	// function with a back off policy.

			metrics = append(metrics, MetricV2{
				Description: MetricDescription{
					Namespace: minioNamespace,
					Subsystem: notifySubsystem,
					Name:      "events_skipped_total",
					Help:      "Events that were skipped to be sent to the targets due to the in-memory queue being full",
					Type:      counterMetric,
				},
				Value: float64(nstats.EventsSkipped),
			})
			metrics = append(metrics, MetricV2{

            "items": {
              "allOf": [
                {

						},
						{
							Name:  "NodeResourcesBalancedAllocation",
							Score: 100,
						},
					},
					TotalScore: 200,
				},
			},
		},
		{
			name:  "all score plugins are skipped",
			pod:   &v1.Pod{},
			nodes: []*v1.Node{makeNode("node1", 1000, schedutil.DefaultMemoryRequest*10), makeNode("node2", 1000, schedutil.DefaultMemoryRequest*10)},
			pluginRegistrations: []tf.RegisterPluginFunc{

            "items": {
              "allOf": [
                {