// Check plugin registration
		if callbackCount == 0 {
			require.Len(t, devices, 3)
			require.Equal(t, devices[0].ID, devs[0].ID)
			require.Equal(t, devices[1].ID, devs[1].ID)
			require.Equal(t, devices[2].ID, devs[2].ID)
			require.Equal(t, devices[0].Health, devs[0].Health)
			require.Equal(t, devices[1].Health, devs[1].Health)
			require.Equal(t, devices[2].Health, devs[2].Health)
		}

		// Check plugin update

  mlir::Builder builder(ctx);

  // Collect devices with attached metadata.
  llvm::SmallVector<mlir::NamedAttribute, 8> devices;
  devices.reserve(device_set->devices().size());

  // For device that do not have any metadata, or if we failed to parse metadata
  // from the DeviceSet, we add a unit attribute to the `tf.devices` attribute.
  for (Device* device : device_set->devices()) {

  llvm::SmallVector<std::unique_ptr<Device>, 2> devices;
  devices.push_back(FakeDevice::Make(cpu0));
  devices.push_back(FakeDevice::Make(gpu0, "compute capability: 7.0"));
  devices.push_back(FakeDevice::Make(gpu1));

  DeviceSet device_set;
  for (auto& device : devices) device_set.AddDevice(device.get());
  AddDevicesToOp(*module_ref, &device_set);

  auto devices_attr =

        "Multiple CPU devices ", device_info_cache.DebugString(devices)));
  }

  if (multiple_gpu_devices) {
    FAILED_TO_PICK_DEVICE(errors::Internal(
        "Multiple GPU devices ", device_info_cache.DebugString(devices)));
  }

  if (multiple_unknown_devices) {
    FAILED_TO_PICK_DEVICE(errors::Internal(
        "Multiple unknown devices ", device_info_cache.DebugString(devices)));
  }

// (NVIDIA compute capability >= 7.0).
bool CanUseTensorCores(const RuntimeDevices &devices) {
  auto has_tensor_cores = [&](const DeviceNameUtils::ParsedName &device) {
    auto md = devices.GetGpuDeviceMetadata(device);
    return md ? md->getCcMajor() >= 7 : false;
  };
  return llvm::all_of(
      llvm::make_filter_range(devices.device_names(), IsGpuDevice),
      has_tensor_cores);
}

		pods             []*v1.Pod
		devices          []*podresourcesv1.ContainerDevices
		expectedResponse *v1alpha1.ListPodResourcesResponse
	}{
		{
			desc:             "no pods",
			pods:             []*v1.Pod{},
			devices:          []*podresourcesv1.ContainerDevices{},
			expectedResponse: &v1alpha1.ListPodResourcesResponse{},
		},
		{
			desc: "pod without devices",
			pods: []*v1.Pod{
				{

func New(devEntries []PodDevicesEntry, devices map[string][]string) DeviceManagerCheckpoint {
	return newV2(devEntries, devices)
}

func newV2(devEntries []PodDevicesEntry, devices map[string][]string) DeviceManagerCheckpoint {
	return &Data{
		Data: checkpointData{
			PodDeviceEntries:  devEntries,
			RegisteredDevices: devices,
		},
	}
}

// MarshalCheckpoint returns marshalled data

	// owning device plugin to allow setup procedures to take place, and for
	// the device plugin to provide runtime settings to use the device
	// (environment variables, mount points and device files).
	Allocate(pod *v1.Pod, container *v1.Container) error

	// UpdatePluginResources updates node resources based on devices already
	// allocated to pods. The node object is provided for the device manager to

    auto device = std::make_unique<XlaDevice>(session_options, options);

    Status status = device->UseAcceleratorDeviceInfo();
    if (!status.ok()) {
      LOG(INFO) << "Ignoring visible " << DEVICE_GPU_XLA_JIT
                << " device. Device number is " << i << ", reason: " << status;
      continue;
    }

    devices->push_back(std::move(device));
  }
  return absl::OkStatus();
}

	devices, err := mockDeviceUtil.FindDevicesForISCSILun("target1", 1)
	if err != nil {
		t.Fatalf("error getting devices for lun: %v", err)
	}
	if devices == nil {
		t.Fatal("no devices returned")
	}
	if len(devices) != 1 {
		t.Fatalf("wrong number of devices: %d", len(devices))
	}
	if devices[0] != "sda" {
		t.Fatalf("incorrect device %v", devices)
	}