}

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();
  }

  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()) {

	h.Bucket = ""
}

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
}

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

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

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

	}

	return buf
}

// IsFull returns this ringbuffer is full.
func (r *RingBuffer) IsFull() bool {
	r.mu.Lock()
	defer r.mu.Unlock()

	return r.isFull
}

// IsEmpty returns this ringbuffer is empty.
func (r *RingBuffer) IsEmpty() bool {
	r.mu.Lock()
	defer r.mu.Unlock()

	return !r.isFull && r.w == r.r
}

// CloseWithError closes the writer; reads will return

		}
	}
}

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
}

// or deleting it for being stale.
func (c *LRU[K, V]) Contains(key K) (ok bool) {
	c.mu.RLock()
	defer c.mu.RUnlock()
	_, ok = c.items[key]
	return ok
}

// Peek returns the key value (or undefined if not found) without updating
// the "recently used"-ness of the key.
func (c *LRU[K, V]) Peek(key K) (value V, ok bool) {
	c.mu.RLock()
	defer c.mu.RUnlock()
	var ent *Entry[K, V]
	if ent, ok = c.items[key]; ok {

}

func (d *naughtyDisk) Close() (err error) {
	if err = d.calcError(); err != nil {
		return err
	}
	return d.disk.Close()
}

func (d *naughtyDisk) calcError() (err error) {
	d.mu.Lock()
	defer d.mu.Unlock()
	d.callNR++
	if err, ok := d.errors[d.callNR]; ok {
		return err
	}
	if d.defaultErr != nil {
		return d.defaultErr
	}
	return nil
}

    TF_RETURN_IF_ERROR(tensorflow::TensorShapeUtils::MakeShape(dims, shape));

    return absl::OkStatus();
  }

  tensorflow::FullTypeDef FullType() const override {
    const FullTypeDef* ft;
    mutex_lock l(graph_->mu);
    graph_->graph.NodeType(output_.oper->node.name(), &ft);
    if (ft == nullptr) {
      return FullTypeDef();
    } else {
      return *ft;
    }
  }

  TF_Output output_;

			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.