GraphDef def;
  {
    mutex_lock l(graph->mu);
    graph->graph.ToGraphDef(&def);
  }
  status->status = MessageToBuffer(def, output_graph_def);
}

void TF_GraphGetOpDef(TF_Graph* graph, const char* op_name,
                      TF_Buffer* output_op_def, TF_Status* status) {
  const OpDef* op_def;
  {
    mutex_lock l(graph->mu);

  return nullptr;
#else
  TF_Library* lib_handle = new TF_Library;
  static tensorflow::mutex mu(tensorflow::LINKER_INITIALIZED);
  static std::unordered_map<std::string, void*>* loaded_libs =
      new std::unordered_map<std::string, void*>();
  tensorflow::Env* env = tensorflow::Env::Default();
  {
    tensorflow::mutex_lock lock(mu);
    auto it = loaded_libs->find(library_filename);
    if (it != loaded_libs->end()) {

)

var printEndpointError = func() func(Endpoint, error, bool) {
	var mutex sync.Mutex
	printOnce := make(map[Endpoint]map[string]int)

	return func(endpoint Endpoint, err error, once bool) {
		reqInfo := (&logger.ReqInfo{}).AppendTags("endpoint", endpoint.String())
		ctx := logger.SetReqInfo(GlobalContext, reqInfo)
		mutex.Lock()
		defer mutex.Unlock()

		m, ok := printOnce[endpoint]
		if !ok {
			m = make(map[string]int)

}

int TF_GraphNumFunctions(TF_Graph* g) {
  tensorflow::mutex_lock l(g->mu);
  return g->graph.flib_def().num_functions();
}

int TF_GraphGetFunctions(TF_Graph* g, TF_Function** funcs, int max_func,
                         TF_Status* status) {
  tensorflow::FunctionDefLibrary lib;
  {
    tensorflow::mutex_lock l(g->mu);
    lib = g->graph.flib_def().ToProto();
  }

	// into an SSE-S3 request. If enabled a valid, non-empty KMS
	// configuration must be present.
	globalAutoEncryption bool

	// Is compression enabled?
	globalCompressConfigMu sync.Mutex
	globalCompressConfig   compress.Config

	// Some standard object extensions which we strictly dis-allow for compression.

// object sets. NOTE: There is no dynamic scaling allowed or intended in
// current design.
type erasureSets struct {
	sets []*erasureObjects

	// Reference format.
	format *formatErasureV3

	// erasureDisks mutex to lock erasureDisks.
	erasureDisksMu sync.RWMutex

	// Re-ordered list of disks per set.
	erasureDisks [][]StorageAPI

	// Distributed locker clients.
	erasureLockers setsDsyncLockers

	"math/rand"
	"sync"
	"time"

	"github.com/minio/pkg/v2/sync/errgroup"
)

func (er erasureObjects) getOnlineDisks() (newDisks []StorageAPI) {
	disks := er.getDisks()
	var wg sync.WaitGroup
	var mu sync.Mutex
	r := rand.New(rand.NewSource(time.Now().UnixNano()))
	for _, i := range r.Perm(len(disks)) {
		i := i
		wg.Add(1)
		go func() {
			defer wg.Done()
			if disks[i] == nil {
				return
			}

	resultsDone := make(chan metaCacheEntriesSorted)
	// Copy so we can mutate
	resCh := resultsDone
	var done bool
	var mu sync.Mutex
	resErr := io.EOF

	go func() {
		var results metaCacheEntriesSorted
		var returned bool
		for entry := range in {
			if returned {
				// past limit
				continue
			}
			mu.Lock()

	return err
}

type writerAt struct {
	w      *io.PipeWriter
	r      *io.PipeReader
	wg     *sync.WaitGroup
	buffer map[int64][]byte
	err    error

	nextOffset int64
	m          sync.Mutex
}

func (w *writerAt) WriteAt(b []byte, offset int64) (n int, err error) {
	w.m.Lock()
	defer w.m.Unlock()

	if w.nextOffset == offset {
		n, err = w.w.Write(b)
		w.nextOffset += int64(n)

			runtime.SetBlockProfileRate(0)
			return buf.Bytes(), err
		}
	case madmin.ProfilerMutex:
		prof.record("mutex", 0, "before")
		runtime.SetMutexProfileFraction(1)
		prof.stopFn = func() ([]byte, error) {
			var buf bytes.Buffer
			err := pprof.Lookup("mutex").WriteTo(&buf, 0)
			runtime.SetMutexProfileFraction(0)
			return buf.Bytes(), err
		}
	case madmin.ProfilerThreads: