}

  // Infers shape of tf.While/tf.WhileRegion. If `shape_invariant` attribute is
  // set, operand types are set as result types if associated body result types
  // match the operand type (does not change per loop iteration). If operand and
  // body result types are not the same, only handle types are propagated to
  // result types. This is necessary to not incorrectly change result shapes

		terminatingErr          error
		prepareWorker           func(t *testing.T, w *podWorkers, records map[types.UID][]syncPodRecord)
		wantWorker              func(t *testing.T, w *podWorkers, records map[types.UID][]syncPodRecord)
		wantWorkerAfterRetry    func(t *testing.T, w *podWorkers, records map[types.UID][]syncPodRecord)
		wantErr                 bool
		expectMetrics           map[string]string

components have identical types. In detail:
</p>

<ul>
	<li>Two array types are identical if they have identical element types and
	    the same array length.</li>

	<li>Two slice types are identical if they have identical element types.</li>

	<li>Two struct types are identical if they have the same sequence of fields,

// two types are equal.

template <typename T1, typename T2>
struct AssertTypeEq;

template <typename T>
struct AssertTypeEq<T, T> {
  typedef bool type;
};

// A unique type used as the default value for the arguments of class
// template Types.  This allows us to simulate variadic templates
// (e.g. Types<int>, Type<int, double>, and etc), which C++ doesn't

    capture.

    input: A list of input tensors whose types are T.
    output: A list of output tensors whose types are T.
    cond: A region that takes 'input' and returns a boolean scalar tensor.
    body: A region that takes a list of tensors and returns another
          list of tensors. Both lists have the same types.
  }];

  let arguments = (ins
    Variadic<AnyTensor>:$input,

    llvm::function_ref<APFloat(APFloat, APFloat)> float_calculate,
    llvm::function_ref<APInt(APInt, APInt)> int_calculate) {
  // Note: All types are wrapped in tensor types in TFlite. E.g., f32 is
  // represented as tensor<f32>. So we are only handling tensor types here.
  auto type = result_type.dyn_cast<ShapedType>();
  if (!type) return {};

  auto elemType = type.getElementType();

	if expect, actual := []types.UID(nil), kubelet.podWorkers.(*fakePodWorkers).triggeredDeletion; !reflect.DeepEqual(expect, actual) {
		t.Fatalf("expected %v kills, got %v", expect, actual)
	}

	ready = true
	kubelet.HandlePodRemoves(pods)
	time.Sleep(2 * time.Second)

	// Sources are ready. Remove unwanted pods.

	}

	var types strings.Builder
	if len(cl.Types) == 0 {
		fmt.Fprintf(&types, "%*sTypes: nil", indent+2, "")
	} else {
		fmt.Fprintf(&types, "%*sTypes:", indent+2, "")
		for i, t := range cl.Types {
			types.WriteByte('\n')
			types.WriteString(t.goString(indent+4, fmt.Sprintf("%d: ", i)))
		}
	}

	var callConstraint string

}

// Get a list of pods that have data directories.
func (kl *Kubelet) listPodsFromDisk() ([]types.UID, error) {
	podInfos, err := os.ReadDir(kl.getPodsDir())
	if err != nil {
		return nil, err
	}
	pods := []types.UID{}
	for i := range podInfos {
		if podInfos[i].IsDir() {
			pods = append(pods, types.UID(podInfos[i].Name()))
		}
	}
	return pods, nil
}

						Succeeded: func() []types.UID {
							uids := make([]types.UID, 499)
							for i := range uids {
								uids[i] = types.UID(strconv.Itoa(i))
							}
							return uids
						}(),
						Failed: []types.UID{"b"},
					},
					Failed: 1,
				},
				{
					UncountedTerminatedPods: &batch.UncountedTerminatedPods{
						Failed: []types.UID{"b"},
					},
					Succeeded: 499,