// blocks until the mutex is available.
func (lm *LRWMutex) Lock() {
	const isWriteLock = true
	lm.lockLoop(context.Background(), lm.id, lm.source, math.MaxInt64, isWriteLock)
}

// GetLock tries to get a write lock on lm before the timeout occurs.
func (lm *LRWMutex) GetLock(ctx context.Context, id string, source string, timeout time.Duration) (locked bool) {
	const isWriteLock = true
	return lm.lockLoop(ctx, id, source, timeout, isWriteLock)
}

func BenchmarkErasureEncodeQuick(b *testing.B) {
	const size = 12 * 1024 * 1024
	b.Run(" 00|00 ", func(b *testing.B) { benchmarkErasureEncode(2, 2, 0, 0, size, b) })
	b.Run(" 00|X0 ", func(b *testing.B) { benchmarkErasureEncode(2, 2, 0, 1, size, b) })
	b.Run(" X0|00 ", func(b *testing.B) { benchmarkErasureEncode(2, 2, 1, 0, size, b) })
}

func BenchmarkErasureEncode_4_64KB(b *testing.B) {
	const size = 64 * 1024

           int32_t step = 1) {
  for (int32_t i = start; i < end; i += step) {
    (*data)[i] = i;
  }
}

// Fills out_dims with the dimensions of the given tensor.
void GetDims(const TF_Tensor* t, int64_t* out_dims) {
  int num_dims = TF_NumDims(t);
  for (int i = 0; i < num_dims; i++) {
    out_dims[i] = TF_Dim(t, i);
  }
}

// Runs model as is if output is a scalar,

      TFE_NewContext(opts.get(), status.get()), TFE_DeleteContext);
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());

  const char* custom0 = "/job:localhost/replica:0/task:0/device:CUSTOM:0";
  const char* custom1 = "/job:localhost/replica:0/task:0/device:CUSTOM:1";
  bool arrived = false;
  bool executed = false;
  RegisterLoggingDevice(context.get(), custom0,

	}))

	// local to remote
	remoteConn := local.Connection(remoteHost)
	remoteConn.WaitForConnect(t.Context())
	defer testlogger.T.SetErrorTB(t)()

	t.Run("localToRemote", func(t *testing.T) {
		const testPayload = "Hello Grid World!"

		start := time.Now()
		resp, err := remoteConn.Request(t.Context(), handlerTest, []byte(testPayload))
		errFatal(err)
		if string(resp) != testPayload {

	// Output:
	// true
}

// Use a Scanner to implement a simple word-count utility by scanning the
// input as a sequence of space-delimited tokens.
func ExampleScanner_words() {
	// An artificial input source.
	const input = "Now is the winter of our discontent,\nMade glorious summer by this sun of York.\n"
	scanner := bufio.NewScanner(strings.NewReader(input))
	// Set the split function for the scanning operation.
	scanner.Split(bufio.ScanWords)

  TensorReference reference;
  std::vector<int64_t> shape;
  std::vector<int64_t> strides;
  DLManagedTensor tensor;

  explicit TfDlManagedTensorCtx(const TensorReference& ref) : reference(ref) {}
};

// Gets tensor from eager tensor handle.
const Tensor* GetTensorFromHandle(TFE_TensorHandle* h, TF_Status* status) {
  if (h == nullptr) {
    status->status = tensorflow::errors::InvalidArgument("Invalid handle");

 */
object Punycode {
  val PREFIX_STRING = "xn--"
  val PREFIX = PREFIX_STRING.encodeUtf8()

  private const val BASE = 36
  private const val TMIN = 1
  private const val TMAX = 26
  private const val SKEW = 38
  private const val DAMP = 700
  private const val INITIAL_BIAS = 72
  private const val INITIAL_N = 0x80

  /**
   * Returns null if any label is oversized so much that the encoder cannot encode it without

	errFatal := func(err error) {
		b.Helper()
		if err != nil {
			b.Fatal(err)
		}
	}
	grid, err := SetupTestGrid(n)
	errFatal(err)
	b.Cleanup(grid.Cleanup)
	const messages = 10
	// Create n managers.
	const payloadSize = 512
	rng := rand.New(rand.NewSource(time.Now().UnixNano()))
	payload := make([]byte, payloadSize)
	_, err = rng.Read(payload)
	errFatal(err)

 * fills, it is doubled.
 */
@Suppress("NAME_SHADOWING")
object Hpack {
  private const val PREFIX_4_BITS = 0x0f
  private const val PREFIX_5_BITS = 0x1f
  private const val PREFIX_6_BITS = 0x3f
  private const val PREFIX_7_BITS = 0x7f

  private const val SETTINGS_HEADER_TABLE_SIZE = 4_096

  /**