public void testElapsed_notRunning() {
    ticker.advance(1);
    stopwatch.start();
    ticker.advance(4);
    stopwatch.stop();
    ticker.advance(9);
    assertEquals(4, stopwatch.elapsed(NANOSECONDS));
  }

  public void testElapsed_multipleSegments() {
    stopwatch.start();
    ticker.advance(9);
    stopwatch.stop();

    ticker.advance(16);

    stopwatch.start();

    cache.asMap().put(1, -1);
    ticker.advance(1, MILLISECONDS);
    assertEquals(Integer.valueOf(1), cache.getUnchecked(0));
    assertEquals(Integer.valueOf(-1), cache.getUnchecked(1));
    assertEquals(Integer.valueOf(2), cache.getUnchecked(2));
    assertEquals(expectedLoads, loader.getLoadCount());
    assertEquals(expectedReloads, loader.getReloadCount());

    // refresh 2
    ticker.advance(1, MILLISECONDS);

            _dst.enc_ndr_small(sub_authority_count);
            int _identifier_authoritys = 6;
            int _identifier_authorityi = _dst.index;
            _dst.advance(1 * _identifier_authoritys);
            int _sub_authorityi = _dst.index;
            _dst.advance(4 * _sub_authoritys);

            _dst = _dst.derive(_identifier_authorityi);
            for (int _i = 0; _i < _identifier_authoritys; _i++) {

  // returned by DeviceName should be "/device:GPU:*" until a particular GPU is
  // chosen for the operation by the device placement logic in the
  // executor. After that, the value returned by DeviceName will be a full
  // device name such as "/job:localhost/replica:0/task:0/device:GPU:1".
  virtual const string& DeviceName() const = 0;

  // Sets the operation device name.
  //

	}
	// Failure case where we detected successfully cross device mounts.
	{
		absPaths := []string{"/path/to/1"}
		if err = checkCrossDevice(absPaths, mountsPath); err == nil {
			t.Fatal("Expected to fail, but found success")
		}

		mp := []mountInfo{
			{"/dev/2", "/path/to/1/2", "type2", []string{"flags"}, "2", "2"},
		}

  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  const DLTensor* dltensor_out = &dlm_out->dl_tensor;
  EXPECT_EQ(dltensor_out->device.device_type, dltensor_in->device.device_type);
  EXPECT_EQ(dltensor_out->device.device_id, dltensor_in->device.device_id);
  EXPECT_EQ(dltensor_out->ndim, dltensor_in->ndim);
  EXPECT_EQ(dltensor_out->dtype.code, dltensor_in->dtype.code);

    cache.asMap().put(1, -1);
    ticker.advance(1, MILLISECONDS);
    assertEquals(Integer.valueOf(1), cache.getUnchecked(0));
    assertEquals(Integer.valueOf(-1), cache.getUnchecked(1));
    assertEquals(Integer.valueOf(2), cache.getUnchecked(2));
    assertEquals(expectedLoads, loader.getLoadCount());
    assertEquals(expectedReloads, loader.getReloadCount());

    // refresh 2
    ticker.advance(1, MILLISECONDS);

// C API for device. The API is under active development and eventually
// should allow registering a plugin device with TensorFlow.

#ifdef __cplusplus
extern "C" {
#endif

// TF_Device is a C wrapper to the C++ TF Device class. This is to be passed
// through TF_OpKernelContext, and is opaque to plugin.
typedef struct TF_Device TF_Device;

typedef struct TF_VariableInfo TF_VariableInfo;

  const char remote_device_name[] =
      "/job:localhost/replica:0/task:1/device:CPU:0";
  auto* h0_task1 =
      TFE_TensorHandleCopyToDevice(h0_task0, ctx, remote_device_name, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  auto* h1_task1 =
      TFE_TensorHandleCopyToDevice(h1_task0, ctx, remote_device_name, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

        System.arraycopy(b, i, buf, index, l);
        advance(l);
    }
    public void readOctetArray(byte[] b, int i, int l) {
        System.arraycopy(buf, index, b, i, l);
        advance(l);
    }


    public int getLength() {
        return deferred.length;
    }
    public void setLength(int length) {
        deferred.length = length;
    }
    public void advance(int n) {
        index += n;