},

		perG: func(b *testing.B, pb *testing.PB, i int, m mapInterface) {
			for ; pb.Next(); i++ {
				m.Delete(0)
			}
		},
	})
}

func BenchmarkSwapCollision(b *testing.B) {
	benchMap(b, bench{
		setup: func(_ *testing.B, m mapInterface) {
			m.LoadOrStore(0, 0)
		},

		perG: func(b *testing.B, pb *testing.PB, i int, m mapInterface) {
			for ; pb.Next(); i++ {
				m.Swap(0, 0)
			}

	data := []byte(`3.14`)
	b.RunParallel(func(pb *testing.PB) {
		var f float64
		for pb.Next() {
			if err := Unmarshal(data, &f); err != nil {
				b.Fatalf("Unmarshal error: %v", err)
			}
		}
	})
}

func BenchmarkUnmarshalInt64(b *testing.B) {
	b.ReportAllocs()
	data := []byte(`3`)
	b.RunParallel(func(pb *testing.PB) {
		var x int64
		for pb.Next() {
			if err := Unmarshal(data, &x); err != nil {

        "test_graph_tfmatmulandadd.pb",
        "test_graph_tfsplits.pb",
        "test_graph_tftop_k.pb",
        "test_graph_tfvariable.pb",
        "test_graph_tfvariable_readonly.pb",
        "test_graph_tfvariable_sequential_updates.pb",
    ],
    # Set CUDA_VISIBLE_DEVICES='' to prevent the code we launch from using any
    # GPUs which might be present.  This is important because builds may run

func (b *profileBuilder) flush() {
	const dataFlush = 4096
	if b.pb.nest == 0 && len(b.pb.data) > dataFlush {
		b.zw.Write(b.pb.data)
		b.pb.data = b.pb.data[:0]
	}
}

// pbValueType encodes a ValueType message to b.pb.
func (b *profileBuilder) pbValueType(tag int, typ, unit string) {
	start := b.pb.startMessage()
	b.pb.int64(tagValueType_Type, b.stringIndex(typ))
	b.pb.int64(tagValueType_Unit, b.stringIndex(unit))

#include "tensorflow/core/framework/graph.pb.h"
#include "tensorflow/core/platform/path.h"
#include "tensorflow/core/protobuf/meta_graph.pb.h"
#include "tensorflow/core/protobuf/saved_object_graph.pb.h"
#include "tensorflow/tools/proto_splitter/cc/util.h"
#include "tensorflow/tools/proto_splitter/chunk.pb.h"
#include "tensorflow/tools/proto_splitter/testdata/test_message.pb.h"
#include "tsl/lib/core/status_test_util.h"

		t.Errorf("reqs.Value() = %v, want -2", i)
	}
}

func BenchmarkIntAdd(b *testing.B) {
	var v Int

	b.RunParallel(func(pb *testing.PB) {
		for pb.Next() {
			v.Add(1)
		}
	})
}

func BenchmarkIntSet(b *testing.B) {
	var v Int

	b.RunParallel(func(pb *testing.PB) {
		for pb.Next() {
			v.Set(1)
		}
	})
}

func TestFloat(t *testing.T) {
	RemoveAll()
	reqs := NewFloat("requests-float")

// IntPerLayer-DAG: "tf.DumpTensor"(%[[output1_quantized]]) <{enabled = true, file_name = "quantized_tensor_data.pb", func_name = "conv", log_dir_path = "/tmp/dumps/composite_conv2d_with_bias_and_relu6_fn_1", node_name = "Conv2D_1"}> : (tensor<*xf32>) -> ()

	// but also not used by Istio at all.
	if pb, ok := s.(protoreflect.ProtoMessage); ok {
		return protoconv.MessageToAnyWithError(pb)
	}

	// gogo protobuf
	if pb, ok := s.(gogoproto.Message); ok {
		gogoany, err := gogotypes.MarshalAny(pb)
		if err != nil {
			return nil, err
		}
		return &anypb.Any{
			TypeUrl: gogoany.TypeUrl,

		benchmark(b, func(pb *testing.PB) {
			for pb.Next() {
				NewTimer(1 * Second).Stop()
			}
		})
	})
	b.Run("impl=func", func(b *testing.B) {
		benchmark(b, func(pb *testing.PB) {
			for pb.Next() {
				newTimerFunc(1 * Second).Stop()
			}
		})
	})
}

func BenchmarkSimultaneousAfterFunc1000(b *testing.B) {
	benchmark(b, func(pb *testing.PB) {
		for pb.Next() {

// total samples collected.
func (p *Profile) Merge(pb *Profile, r float64) error {
	if err := p.Compatible(pb); err != nil {
		return err
	}

	pb = pb.Copy()

	// Keep the largest of the two periods.
	if pb.Period > p.Period {
		p.Period = pb.Period
	}

	p.DurationNanos += pb.DurationNanos

	p.Mapping = append(p.Mapping, pb.Mapping...)
	for i, m := range p.Mapping {
		m.ID = uint64(i + 1)