const numNodes = 50
	const podsPerNode = 100
	makeNodes := func() []*v1.Node {
		nodes := make([]*v1.Node, numNodes)
		// Node created long time ago, with status updated by kubelet exceeds grace period.
		// Expect pods status updated and Unknown node status posted from node controller
		for i := 0; i < numNodes; i++ {
			nodes[i] = &v1.Node{
				ObjectMeta: metav1.ObjectMeta{

      // TODO(b/74949947): turn this back into an error status
      LOG(WARNING) << mutation_warning;
      session->graph->sessions[session].clear();
    }

    const auto num_nodes = graph.num_node_ids();
    if (session->last_num_graph_nodes < num_nodes) {
      // TODO(nolivia): check this on a subset of the graph instead of all of
      // it.
      status->status = graph::ValidateGraphHasNoCycle(session->graph->graph);

				ShutdownGracePeriod:             metav1.Duration{Duration: 60 * time.Second},
				ShutdownGracePeriodCriticalPods: metav1.Duration{Duration: 60 * time.Second},
				ReservedMemory: []v1beta1.MemoryReservation{
					{
						NumaNode: 1,
						Limits:   v1.ResourceList{v1.ResourceMemory: resource.MustParse("1Gi")},
					},
				},
				EnableProfilingHandler:        utilpointer.Bool(true),
				EnableDebugFlagsHandler:       utilpointer.Bool(true),

	logger.V(5).Info("remembering potential nodes", "pod", klog.KObj(pod), "potentialnodes", klog.KObjSlice(nodes))
	numNodes := len(nodes)
	if numNodes > resourcev1alpha2.PodSchedulingNodeListMaxSize {
		numNodes = resourcev1alpha2.PodSchedulingNodeListMaxSize
	}
	potentialNodes := make([]string, 0, numNodes)
	if numNodes == len(nodes) {
		// Copy all node names.
		for _, node := range nodes {

      GetXlaAutoClusteringSummary(*graph_);

  VLOG(2) << "*** Clustering info for graph of size " << graph_->num_nodes();
  VLOG(2) << " Built " << auto_clustering_info.clusters_size()
          << " clusters, size "
          << RatioToString(auto_clustering_info.clustered_node_count(),
                           graph_->num_nodes());

  for (const XlaAutoClusteringSummary::Cluster& cluster :
       auto_clustering_info.clusters()) {

			MemoryType: string(b.Type),
			Size_:      b.Size,
			Topology: &podresourcesapi.TopologyInfo{
				Nodes: []*podresourcesapi.NUMANode{},
			},
		}

		for _, numaNodeID := range b.NUMAAffinity {
			containerMemory.Topology.Nodes = append(containerMemory.Topology.Nodes, &podresourcesapi.NUMANode{ID: int64(numaNodeID)})
		}

		containerMemories = append(containerMemories, &containerMemory)
	}

type ImageStateSummary struct {
	// Size of the image
	Size int64
	// Used to track how many nodes have this image, it is computed from the Nodes field below
	// during the execution of Snapshot.
	NumNodes int
	// A set of node names for nodes having this image present. This field is used for
	// keeping track of the nodes during update/add/remove events.
	Nodes sets.Set[string]
}

MASTER_KEY: $(yaml-quote "${MASTER_KEY_BASE64:-}")
KUBECFG_CERT: $(yaml-quote "${KUBECFG_CERT_BASE64:-}")
KUBECFG_KEY: $(yaml-quote "${KUBECFG_KEY_BASE64:-}")
KUBELET_APISERVER: $(yaml-quote "${KUBELET_APISERVER:-}")
NUM_NODES: $(yaml-quote "${NUM_NODES}")
STORAGE_BACKEND: $(yaml-quote "${STORAGE_BACKEND:-etcd3}")
STORAGE_MEDIA_TYPE: $(yaml-quote "${STORAGE_MEDIA_TYPE:-}")
ENABLE_GARBAGE_COLLECTOR: $(yaml-quote "${ENABLE_GARBAGE_COLLECTOR:-}")

  const Variant& v = input.scalar<Variant>()();
  // DT_VARIANT tensors must be allocated on CPU since they wrap C++
  // objects which can not be efficiently represented in GPU memory.
  int numa_node = cc_ctx->device()->NumaNode();
  Tensor out(::tensorflow::cpu_allocator(numa_node), ::tensorflow::DT_VARIANT,
             ::tensorflow::TensorShape({}));
  Variant* out_v = &(out.scalar<Variant>()());

  local -r cloud_provider="${KUBERNETES_PROVIDER}"
  local -r enable_hollow_node_logs="${ENABLE_HOLLOW_NODE_LOGS:-false}"
  local -r logexport_sleep_seconds="$(( 90 + NUM_NODES / 3 ))"
  if [[ -z "${ZONE_NODE_SELECTOR_DISABLED:-}" ]]; then
    local -r node_selector="${ZONE_NODE_SELECTOR_LABEL:-topology.kubernetes.io/zone}: ${ZONE}"
  fi