const Graph& graph, const FunctionLibraryDefinition* function_library,
    const std::function<bool(const Graph& graph)>& predicate) {
  if (predicate(graph)) {
    return success();
  }

  // Check if any reachable functions from the graph has the target attribute.
  GraphDef graph_def;
  graph.ToGraphDef(&graph_def);
  if (!function_library) return failure();
  for (const std::string& func_name :

		return
	}
	writeResponse(w, http.StatusOK, nil, mimeNone)
}

// ReadinessCheckHandler checks whether MinIO is up and ready to serve requests.
// It also checks whether the KMS is available and whether etcd is reachable,
// if configured.
func ReadinessCheckHandler(w http.ResponseWriter, r *http.Request) {
	if objLayer := newObjectLayerFn(); objLayer == nil {

					"159.122.219.2": 4,

					// 3 endpoints on network 3, weights split across 2 gateways.
					"159.122.219.3": 3,
					"179.114.119.3": 3,

					// no gateway defined for network 4 - treat as directly reachable.
					"10.4.0.1": 2,
					"10.4.0.2": 2,
					"10.4.0.3": 2,
					"10.4.0.4": 2,
				},
			},
		},
		{
			// Verify that EDS from network2 will return 2 local endpoints with local VIPs + 2 remote

	}

	// New symbols should not initially be reachable.
	if ldr.AttrReachable(es1) || ldr.AttrReachable(es2) || ldr.AttrReachable(es3) {
		t.Errorf("newly materialized symbols should not be reachable")
	}

	// ... however it should be possible to set/unset their reachability.
	ldr.SetAttrReachable(es3, true)
	if !ldr.AttrReachable(es3) {
		t.Errorf("expected reachable symbol after update")
	}
	ldr.SetAttrReachable(es3, false)

		visit(root)
	}
	for i, j := 0, len(topo)-1; i < j; i, j = i+1, j-1 {
		topo[i], topo[j] = topo[j], topo[i]
	}
	return topo
}

// TransitiveReduction removes edges from g that are transitively
// reachable. g must be transitively closed.
func (g *Graph) TransitiveReduction() {
	// For i -> j -> k, if i -> k exists, delete it.
	for _, i := range g.Nodes {
		for _, j := range g.Nodes {
			if g.HasEdge(i, j) {

#include "tensorflow/compiler/mlir/tensorflow/utils/tpu_rewrite_device_util.h"

namespace mlir {
namespace TFTPU {

// For each TPU cluster in `module`, walk over all ops inside the cluster
// and reachable in the call graph from the cluster.
// For each op walked, `callback` is applied to the op, the root cluster, and
// the root cluster's host device. `callback` returning WasInterrupted
// indicates failure.

    // the index doesn't cover classfiles from compiler output,
    // so the lowering fails.
    //
    // To solve the problem, we need to find all delegated properties with inline accessors
    // reachable from files that will be compiled, and include files these inline accessors
    // to the set of files that will be compiled (and do the same for these files recursively).

        // can potentially still execute
        // So visit all the finalizer groups reachable from groups that the node belongs to and the finalized nodes of those groups
        Set<FinalizerGroup> seen = new HashSet<>();
        List<FinalizerGroup> queue = new ArrayList<>(groups);
        while (!queue.isEmpty()) {

    private val directDependentsByKtModule: Map<KtModule, Set<KtModule>> by lazy {
        // Direct dependencies should be computed lazily, because the built-ins module will be reachable via module dependencies. Getting
        // the built-ins module relies on the built-ins session, which may depend on services that are registered after
        // `KtStaticModuleDependentsProvider`.

import java.util.Deque;
import java.util.HashMap;
import java.util.LinkedHashSet;
import java.util.List;
import java.util.Map;
import java.util.Set;

/**
 * A graph walker which collects the values reachable from a given set of start nodes. Handles cycles in the graph. Can
 * be reused to perform multiple searches, and reuses the results of previous searches.
 *