func Stats() (*statsapi.RlimitStats, error) {
	rlimit := &statsapi.RlimitStats{}

	taskMax := int64(-1)
	// Calculate the minimum of kernel.pid_max and kernel.threads-max as they both specify the
	// system-wide limit on the number of tasks.
	for _, file := range []string{"/proc/sys/kernel/pid_max", "/proc/sys/kernel/threads-max"} {
		if content, err := os.ReadFile(file); err == nil {

}

func podsMapToPods(UIDMap map[kubetypes.ResolvedPodUID]*v1.Pod) []*v1.Pod {
	pods := make([]*v1.Pod, 0, len(UIDMap))
	for _, pod := range UIDMap {
		pods = append(pods, pod)
	}
	return pods
}

func mirrorPodsMapToMirrorPods(UIDMap map[kubetypes.MirrorPodUID]*v1.Pod) []*v1.Pod {
	pods := make([]*v1.Pod, 0, len(UIDMap))
	for _, pod := range UIDMap {
		pods = append(pods, pod)
	}
	return pods

          << "Malformed " << TF::kParallelExecAnnotation << " attribute";
      return failure();
    }
    if (id_pairs.empty()) continue;

    TF::ParallelIdsMap& ids_map = op_to_parallel_ids_map[island];
    for (const auto& [group_id, branch_id] : id_pairs)
      ids_map[group_id] = branch_id;
  }
  return success();
}

// Fills `op_to_parallel_ids_map` from parallel execution attributes in

  std::vector<int> b_size = {};
  std::vector<int> b_map = {};
  PopulateEncodingParams(block_size, &traversal_order, &format, &b_map,
                         &b_size);

  if (type.getElementType().isF32()) {
    tflite::internal::sparsity::FormatConverter<float> format_converter(
        shape, traversal_order, format, b_size, b_map);
    std::vector<float> data;
    data.reserve(type.getNumElements());

	isInt(Int(0))
	i = 10
	asInt(*&i)
	isInt(*&i)
	asInt(23)
	asInt(Int(f))
	isInt(Int(f))

	asMap(m)
	isMap(m)
	asMap(nil)
	m = nil
	asMap(make(Map))
	isMap(make(Map))
	asMap(*&m)
	isMap(*&m)
	asMap(Map(nil))
	isMap(Map(nil))
	asMap(Map{})
	isMap(Map{})

	asSlice(slice)
	isSlice(slice)
	asSlice(make(Slice, 5))
	isSlice(make(Slice, 5))
	asSlice([]byte{1, 2, 3})

            boolean isCollection = false;
            boolean isMap = false;
            boolean isProperties = false;
            if (!isArray) {
                try {
                    // assuming Type is available in current ClassLoader
                    isCollection = Collection.class.isAssignableFrom(Class.forName(param.getType()));
                    isMap = Map.class.isAssignableFrom(Class.forName(param.getType()));

// (ref: https://github.com/torvalds/linux/commit/35dfb013149f74c2be1ff9c78f14e6a3cd1539d1)
const IPVSConnReuseModeFixedKernelVersion = "5.9"

// UserNamespacesSupportKernelVersion is the kernel version where idmap for tmpfs support was added
// (ref: https://github.com/torvalds/linux/commit/05e6295f7b5e05f09e369a3eb2882ec5b40fff20)
const UserNamespacesSupportKernelVersion = "6.3"

	etags = make([]string, len(partsMetadata))
	vidMap := map[string]int{}
	for index, metadata := range partsMetadata {
		if errs[index] != nil {
			continue
		}
		vid := metadata.VersionID
		if metadata.VersionID == "" {
			vid = nullVersionID
		}
		vidMap[vid]++
		etags[index] = metadata.Metadata["etag"]
	}

	for _, count := range vidMap {
		// do we have enough common versions

// > 0 if the first is greater.
func _New[K, V any](compare func(K, K) int) *_Map[K, V] {
	return &_Map[K, V]{compare: compare}
}

// _NewOrdered returns a new map whose key is an ordered type.
// This is like _New, but does not require providing a compare function.
// The map compare function uses the obvious key ordering.
func _NewOrdered[K Ordered, V any]() *_Map[K, V] {
	return _New[K, V](func(k1, k2 K) int {
		switch {
		case k1 < k2:

	type specVal struct {
		ref     statsapi.UserDefinedMetricDescriptor
		valType cadvisorapiv1.DataType
		time    time.Time
		value   float64
	}
	udmMap := map[string]*specVal{}
	for _, spec := range info.Spec.CustomMetrics {
		udmMap[spec.Name] = &specVal{
			ref: statsapi.UserDefinedMetricDescriptor{
				Name:  spec.Name,
				Type:  statsapi.UserDefinedMetricType(spec.Type),
				Units: spec.Units,
			},