latestConn    *ZtunnelConnection
	mu            sync.Mutex
}

func (c *connMgr) addConn(conn *ZtunnelConnection) {
	log.Debug("ztunnel connected")
	c.mu.Lock()
	defer c.mu.Unlock()
	c.connectionSet[conn] = struct{}{}
	c.latestConn = conn
	ztunnelConnected.RecordInt(int64(len(c.connectionSet)))
}

func (c *connMgr) LatestConn() *ZtunnelConnection {
	c.mu.Lock()
	defer c.mu.Unlock()
	return c.latestConn
}

}

func (t *apiConfig) odirectEnabled() bool {
	t.mu.RLock()
	defer t.mu.RUnlock()

	return t.enableODirect
}

func (t *apiConfig) shouldGzipObjects() bool {
	t.mu.RLock()
	defer t.mu.RUnlock()

	return t.gzipObjects
}

func (t *apiConfig) permitRootAccess() bool {
	t.mu.RLock()
	defer t.mu.RUnlock()

	return t.rootAccess
}

	return h
}

func (h healingTracker) getLastUpdate() time.Time {
	h.mu.RLock()
	defer h.mu.RUnlock()

	return h.LastUpdate
}

func (h healingTracker) getBucket() string {
	h.mu.RLock()
	defer h.mu.RUnlock()

	return h.Bucket
}

func (h *healingTracker) setBucket(bucket string) {
	h.mu.Lock()
	defer h.mu.Unlock()

	h.Bucket = bucket
}

}

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();
  }

			go func(i int, set *erasureObjects) {
				defer wg.Done()
				err := set.listPath(listCtx, o, innerResults)
				mu.Lock()
				defer mu.Unlock()
				if err == nil {
					allAtEOF = false
				}
				errs[i] = err
			}(len(errs), set)
			errs = append(errs, nil)
		}
	}
	mu.Unlock()

	// Gather results to a single channel.
	// Quorum is one since we are merging across sets.

					}
					uploadsCancel()
					return
				}
				response := time.Since(t)
				atomic.AddUint64(&totalBytesWritten, uint64(info.Size))
				objCountPerThread[i]++
				mu.Lock()
				uploadTimes = append(uploadTimes, response)
				mu.Unlock()
			}
		}(i)
	}
	wg.Wait()

	// We already saw write failures, no need to proceed into read's
	if retError != "" {
		return SpeedTestResult{

	type PaddedMutex struct {
		*DRWMutex
	}
	b.RunParallel(func(pb *testing.PB) {
		mu := PaddedMutex{NewDRWMutex(ds, "")}
		for pb.Next() {
			mu.Lock(id, source)
			mu.Unlock(context.Background())
		}
	})
}

func benchmarkMutex(b *testing.B, slack, work bool) {
	b.ResetTimer()
	b.ReportAllocs()

	mu := NewDRWMutex(ds, "")
	if slack {
		b.SetParallelism(10)
	}

		return nil
	}
	workers := *w
	return workers[h%uint64(len(workers))]
}

func (es *expiryState) ResizeWorkers(n int) {
	// Lock to avoid multiple resizes to happen at the same time.
	es.mu.Lock()
	defer es.mu.Unlock()
	var workers []chan expiryOp
	if v := es.workers.Load(); v != nil {
		// Copy to new array.
		workers = append(workers, *v...)
	}

	if n == len(workers) || n < 1 {
		return
	}

	// 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()
			returned = done
			mu.Unlock()
			if returned {
				resCh = nil
				continue
			}

  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()) {