func.return %0 : tensor<4x2x3x1x1xi32>
  }

  // CHECK-LABEL: mirror_pad
  func.func @mirror_pad(%arg0: tensor<2x3xcomplex<f64>>) -> tensor<4x7xcomplex<f64>> {
    %0 = mhlo.constant dense<[[1, 1], [2, 2]]> : tensor<2x2xi32>
    // CHECK-NOT: tf.MirrorPad
    %1 = "tf.MirrorPad"(%arg0, %0) {mode = "SYMMETRIC"} : (tensor<2x3xcomplex<f64>>, tensor<2x2xi32>) -> tensor<4x7xcomplex<f64>>

  REDUCE_ANY = 91,
  SQUARE = 92,
  ZEROS_LIKE = 93,
  FILL = 94,
  FLOOR_MOD = 95,
  RANGE = 96,
  RESIZE_NEAREST_NEIGHBOR = 97,
  LEAKY_RELU = 98,
  SQUARED_DIFFERENCE = 99,
  MIRROR_PAD = 100,
  ABS = 101,
  SPLIT_V = 102,
  UNIQUE = 103,
  CEIL = 104,
  REVERSE_V2 = 105,
  ADD_N = 106,
  GATHER_ND = 107,
  COS = 108,
  WHERE = 109,
  RANK = 110,
  ELU = 111,

}

func.func @mirror_pad(tensor<2x1x3xf32>, tensor<3x2xi32>) -> tensor<? x f32> {
^bb0(%arg0: tensor<2x1x3xf32>, %arg1: tensor<3x2xi32>):
  %0 = "tf.MirrorPad"(%arg0, %arg1) { mode = "SYMMETRIC" }: (tensor<2x1x3xf32>, tensor<3x2xi32>) -> tensor<? x f32>
  func.return %0#0 : tensor<? x f32>

  // CHECK-LABEL: mirror_pad

  REDUCE_ANY = 91,
  SQUARE = 92,
  ZEROS_LIKE = 93,
  FILL = 94,
  FLOOR_MOD = 95,
  RANGE = 96,
  RESIZE_NEAREST_NEIGHBOR = 97,
  LEAKY_RELU = 98,
  SQUARED_DIFFERENCE = 99,
  MIRROR_PAD = 100,
  ABS = 101,
  SPLIT_V = 102,
  UNIQUE = 103,
  CEIL = 104,
  REVERSE_V2 = 105,
  ADD_N = 106,
  GATHER_ND = 107,
  COS = 108,
  WHERE = 109,
  RANK = 110,
  ELU = 111,

}

func TestSyncBatchCleanupVersions(t *testing.T) {
	m := newTestManager(&fake.Clientset{})
	testPod := getTestPod()
	mirrorPod := getTestPod()
	mirrorPod.UID = "mirror-uid"
	mirrorPod.Name = "mirror_pod"
	mirrorPod.Annotations = map[string]string{
		kubetypes.ConfigSourceAnnotationKey: "api",
		kubetypes.ConfigMirrorAnnotationKey: "mirror",
	}

	}
	return podToMirror, mirrorToPod
}

// IsMirrorPodOf returns true if pod and mirrorPod are associated with each other.
func IsMirrorPodOf(mirrorPod, pod *v1.Pod) bool {
	// Check name and namespace first.
	if pod.Name != mirrorPod.Name || pod.Namespace != mirrorPod.Namespace {
		return false
	}
	hash, ok := getHashFromMirrorPod(mirrorPod)
	if !ok {
		return false
	}
	return hash == getPodHash(pod)
}

		kl.podManager.AddPod(pod)

		pod, mirrorPod, wasMirror := kl.podManager.GetPodAndMirrorPod(pod)
		if wasMirror {
			if pod == nil {
				klog.V(2).InfoS("Unable to find pod for mirror pod, skipping", "mirrorPod", klog.KObj(mirrorPod), "mirrorPodUID", mirrorPod.UID)
				continue
			}
			kl.podWorkers.UpdatePod(UpdatePodOptions{
				Pod:        pod,
				MirrorPod:  mirrorPod,
				UpdateType: kubetypes.SyncPodUpdate,

// LINT.ThenChange(//tensorflow/compiler/mlir/lite/transforms/while_loop_outline.cc)

def TFL_MirrorPadOp: TFL_Op<"mirror_pad", [
                     SameOperandsAndResultsScale,
                     QuantizableResult,
                     Pure,
                     TFL_OperandHasRank<1, 2>]> {
  let summary = "MirrorPad Operator. Pads a tensor with mirrored values.";

  let description = [{

}

type simpleFakeKubelet struct {
	pod       *v1.Pod
	mirrorPod *v1.Pod
	podStatus *kubecontainer.PodStatus
	wg        sync.WaitGroup
}

func (kl *simpleFakeKubelet) SyncPod(ctx context.Context, updateType kubetypes.SyncPodType, pod, mirrorPod *v1.Pod, podStatus *kubecontainer.PodStatus) (bool, error) {
	kl.pod, kl.mirrorPod, kl.podStatus = pod, mirrorPod, podStatus
	return false, nil
}

		opts.Pod = other.Pod
	}
	// running pods will not persist but will be remembered for replay
	opts.RunningPod = other.RunningPod
	// if mirrorPod was not provided, remember the last one for replay
	if other.MirrorPod != nil {
		opts.MirrorPod = other.MirrorPod
	}
	// accumulate kill pod options
	if other.KillPodOptions != nil {
		opts.KillPodOptions = &KillPodOptions{}
		if other.KillPodOptions.Evict {