//            returned TF_SavedModel pointer.
  //  tags - Optional set of tags. If tags = nullptr, we expect the SavedModel
  //         to contain a single Metagraph (as for those exported from TF2's
  //         `tf.saved_model.save`). If tags != nullptr, we load the metagraph
  //         matching the tags:

        dependsOn(task3, [task4])
        dependsOn(transform1, [task4])

        when:
        collector.collectNodes([task1, task2, task3, task4, transform1])
        def graph = collector.getGraph()
        def nodes = graph.getNodes(PlannedNodeGraph.DetailLevel.LEVEL1_TASKS) as List<TestPlannedNode>
        then:
        nodes.size() == 4
        nodes*.nodeIdentity*.nodeType =~ [NodeType.TASK]
        verifyAll {

package dag

import (
	"cmp"
	"fmt"
	"slices"
	"strings"
)

type Graph struct {
	Nodes   []string
	byLabel map[string]int
	edges   map[string]map[string]bool
}

func newGraph() *Graph {
	return &Graph{byLabel: map[string]int{}, edges: map[string]map[string]bool{}}
}

func (g *Graph) addNode(label string) bool {
	if _, ok := g.byLabel[label]; ok {
		return false
	}

	selected map[string]string       // path → version
}

// NewGraph returns an incremental MVS graph containing only a set of root
// dependencies and using the given max function for version strings.
//
// The caller must ensure that the root slice is not modified while the Graph
// may be in use.
func NewGraph(cmp func(p, v1, v2 string) int, roots []module.Version) *Graph {
	g := &Graph{
		cmp:      cmp,

	g := NewGraph()
	populate(g, nodes, pods, pvs, attachments, slices)
	// Garbage collect before the first iteration
	runtime.GC()
	b.ResetTimer()

	b.SetParallelism(100)
	b.RunParallel(func(pb *testing.PB) {
		for pb.Next() {
			g.AddPod(pods[0])
		}
	})
}

func BenchmarkAuthorization(b *testing.B) {
	g := NewGraph()

	opts := &sampleDataOpts{

			valueIndex = i
			break
		}
	}

	if valueIndex == -1 {
		return nil, fmt.Errorf(`profile does not contain a sample index with value/type "samples/count" or cpu/nanoseconds"`)
	}

	g := profile.NewGraph(p, &profile.Options{
		SampleValue: func(v []int64) int64 { return v[valueIndex] },
	})

	namedEdgeMap, totalWeight, err := createNamedEdgeMap(g)
	if err != nil {
		return nil, err
	}

	if totalWeight == 0 {

    "header file that gives access to the functionality in the object file.\n"
    "A typical invocation looks like this:\n"
    "\n"
    "   $ tfcompile --graph=mygraph.pb --config=myfile.pbtxt "
    "--cpp_class=\"mynamespace::MyComputation\"\n"
    "\n";

}  // end namespace tfcompile
}  // end namespace tensorflow

int main(int argc, char** argv) {

            PlannedNodeGraph.Collector collector = new PlannedNodeGraph.Collector(converterRegistry);
            scheduledWork.visitNodes((nodes, entryNodes) -> collector.collectNodes(nodes));
            return collector.getGraph();
        }

        private static class CalculateTaskGraphResult implements Result, CustomOperationTraceSerialization {

            private final Set<Task> requestedTasks;

import spock.lang.Specification

class ParameterAwareBuildControllerAdapterTest extends Specification {
    def graphAdapter = Mock(ObjectGraphAdapter)
    def adapter = Mock(ProtocolToModelAdapter) {
        newGraph() >> graphAdapter
    }
    def mapping = Stub(ModelMapping) {
        getModelIdentifierFromModelType(_) >> { Class type ->
            return Stub(ModelIdentifier) {
                getName() >> type.simpleName

	}

	if unit != "" {
		o.OutputUnit = unit
	} else {
		o.OutputUnit = o.SampleUnit
	}
}

// newGraph creates a new graph for this report. If nodes is non-nil,
// only nodes whose info matches are included. Otherwise, all nodes
// are included, without trimming.
func (rpt *Report) newGraph(nodes graph.NodeSet) *graph.Graph {
	o := rpt.options

	// Clean up file paths using heuristics.
	prof := rpt.prof