destroyFunc, registry := NewTestGenericStoreRegistry(t)
			defer destroyFunc()
			registry.Decorator = tc.decorator
			registry.UpdateStrategy.(*testRESTStrategy).allowCreateOnUpdate = true
			registry.BeginUpdate = tc.beginUpdate
			registry.AfterUpdate = tc.afterUpdate
			registry.BeginCreate = tc.beginCreate
			registry.AfterCreate = tc.afterCreate
			registry.TTLFunc = tc.ttl

func metricsNodeHandler() http.Handler {
	registry := prometheus.NewRegistry()

	logger.CriticalIf(GlobalContext, registry.Register(nodeCollector))
	if err := registry.Register(prometheus.NewProcessCollector(prometheus.ProcessCollectorOpts{
		Namespace:    minioNamespace,
		ReportErrors: true,
	})); err != nil {
		logger.CriticalIf(GlobalContext, err)
	}
	if err := registry.Register(prometheus.NewGoCollector()); err != nil {

[plugins."io.containerd.grpc.v1.cri".registry.mirrors."docker.io"]
  endpoint = ["https://mirror.gcr.io","https://registry-1.docker.io"]
# Enable registry.k8s.io as the primary mirror for k8s.gcr.io
# See: https://github.com/kubernetes/k8s.io/issues/3411
[plugins."io.containerd.grpc.v1.cri".registry.mirrors."k8s.gcr.io"]
  endpoint = ["https://registry.k8s.io", "https://k8s.gcr.io",]

	imageList := []kubecontainer.Image{
		{
			ID:       "abc",
			RepoTags: []string{"registry.k8s.io:v1", "registry.k8s.io:v2"},
			Size:     123,
		},
		{
			ID:       "efg",
			RepoTags: []string{"registry.k8s.io:v3", "registry.k8s.io:v4"},
			Size:     456,
		},
	}

    // It is a terrible idea to have local MLIR contexts so we need to
    // register extensions here, again.
    mlir::DialectRegistry registry;
    registry.insert<mlir::func::FuncDialect>();
    mlir::func::registerAllExtensions(registry);
    xla_call_module_context_.appendDialectRegistry(registry);

    auto l = tensorflow::XlaCallModuleLoader::Create(
        &xla_call_module_context_, op.getVersion(), op.getModule().str(),

					{
						Name: "FakeNodeSelector",
						Args: &runtime.Unknown{Raw: []byte(`{"nodeName":"node3"}`)},
					},
				},
			},
		),
		WithFrameworkOutOfTreeRegistry(frameworkruntime.Registry{
			"FakeNodeSelector": newFakeNodeSelector,
		}),
	)
	if err != nil {
		t.Fatal(err)
	}

	// Capture the bindings and events' controllers.
	var wg sync.WaitGroup
	wg.Add(2 * len(pods))

  let description = [{
    Fixed point shape refinement pass that utilizes the shape functions
    registered on ops using the InferTypeOpInterface as well as by bridging to
    the TensorFlow op registry's shape functions. This is an interprocedural
    pass that propagates information across function calls/control flow
    operations where possible (the GuaranteeAllFuncsOneUsePass is often run

		return fmt.Errorf("error creating plugins directory: %v", err)
	}
	if err := os.MkdirAll(kl.getPluginsRegistrationDir(), 0750); err != nil {
		return fmt.Errorf("error creating plugins registry directory: %v", err)
	}
	if err := os.MkdirAll(kl.getPodResourcesDir(), 0750); err != nil {
		return fmt.Errorf("error creating podresources directory: %v", err)
	}

						Value: "test-test-test",
					},
					{
						Name: "POD_NAME",
						ValueFrom: &v1.EnvVarSource{
							FieldRef: &v1.ObjectFieldSelector{
								APIVersion: "v1", //legacyscheme.Registry.GroupOrDie(v1.GroupName).GroupVersion.String(),
								FieldPath:  "metadata.name",
							},
						},
					},
					{
						Name:  "OUT_OF_ORDER_TEST",
						Value: "$(OUT_OF_ORDER_TARGET)",
					},