}
		if !reflect.DeepEqual(test.want, got) {
			t.Errorf("%s: want %v got %v", test.name, test.want, got)
		}
	}
	ss1 := newStatefulSet(3, "ss1", types.UID("ss1"), map[string]string{"foo": "bar"})
	ss2 := newStatefulSet(3, "ss2", types.UID("ss2"), map[string]string{"goo": "car"})
	sel1, err := metav1.LabelSelectorAsSelector(ss1.Spec.Selector)
	if err != nil {
		t.Fatal(err)
	}

	dsw.AddNode(nodeName1)
	dsw.AddNode(nodeName2)

	generatedVolumeName, podAddErr := dsw.AddPod(types.UniquePodName(podName1), controllervolumetesting.NewPod(podName1, podName1), volumeSpec, nodeName1)
	if podAddErr != nil {
		t.Fatalf("AddPod failed. Expected: <no error> Actual: <%v>", podAddErr)
	}

	_, podAddErr = dsw.AddPod(types.UniquePodName(podName2), controllervolumetesting.NewPod(podName2, podName2), volumeSpec, nodeName2)

# TODO(mdan): Use class definitions so that we can mix these with Python types.


class TFRTypes(enum.Enum):
  """All the supported types.

    1-3: tfr types
    4-99: mlir built-in types
    100-199: TF related translator internal types
    200- : Python related translator internal types
  """
  TENSOR = 1
  TENSOR_LIST = 2
  ATTR = 3
  NONE = 4
  SHAPE = 5  # shape -> !shape.shape

	podCache kubecontainer.Cache,
) PodWorkers {
	return &podWorkers{
		podSyncStatuses:                    map[types.UID]*podSyncStatus{},
		podUpdates:                         map[types.UID]chan struct{}{},
		startedStaticPodsByFullname:        map[string]types.UID{},
		waitingToStartStaticPodsByFullname: map[string][]types.UID{},
		podSyncer:                          podSyncer,
		recorder:                           recorder,

		}
		if isComparison(x.Op) {
			// The result type is independent of operand types
			// and the operand types must have final types.
		} else if isShift(x.Op) {
			// The result type depends only on lhs operand.
			// The rhs type was updated when checking the shift.
			check.updateExprType0(x, x.X, typ, final)
		} else {
			// The operand types match the result type.
			check.updateExprType0(x, x.X, typ, final)

		}
		if isComparison(x.Op) {
			// The result type is independent of operand types
			// and the operand types must have final types.
		} else if isShift(x.Op) {
			// The result type depends only on lhs operand.
			// The rhs type was updated when checking the shift.
			check.updateExprType0(x, x.X, typ, final)
		} else {
			// The operand types match the result type.
			check.updateExprType0(x, x.X, typ, final)

    ++i;
  }
}

// Updates the tensorlist types to unranked tensor types based on the input
// index.
template <typename R>
void ChangeVariantToUnrankedTensorType(
    const llvm::SmallSet<int, 4> &tensor_list_index, ArrayRef<Type> types,
    R &&range, llvm::SmallVectorImpl<Type> *updated_types) {
  int i = 0;
  for (const auto it : llvm::zip(types, range)) {
    if (tensor_list_index.count(i)) {

	fakecsi "k8s.io/kubernetes/pkg/volume/csi/fake"
	"k8s.io/kubernetes/pkg/volume/util"
	volumetypes "k8s.io/kubernetes/pkg/volume/util/types"
)

var (
	testDriver  = "test-driver"
	testVol     = "vol-123"
	testns      = "test-ns"
	testPod     = "test-pod"
	testPodUID  = types.UID("test-pod")
	testAccount = "test-service-account"
)

	runFunc             func(podFullName string, uid types.UID, containerName string, cmd []string) ([]byte, error)
	getExecCheck        func(string, types.UID, string, []string, remotecommandserver.Options)
	getAttachCheck      func(string, types.UID, string, remotecommandserver.Options)
	getPortForwardCheck func(string, string, types.UID, portforward.V4Options)

std::vector<Type> GetValueTypes(const InputContainer& input) {
  // Convert a list of mlir::Value's into a list of mlir::Type's
  std::vector<Type> types;
  types.reserve(input.size());
  for (auto val : input) types.push_back(val.getType());
  return types;
}

bool IsTPUOp(mlir::Operation* op) {
  return op->hasAttr(TF::kReplicationInfoAttr);
}

template <typename Vector, typename Container>