public:
  Status ListPhysicalDevices(std::vector<string>* devices) override;
  Status CreateDevices(const SessionOptions& options, const string& name_prefix,
                       std::vector<std::unique_ptr<Device>>* devices) override;
};

Status XlaGpuDeviceFactory::ListPhysicalDevices(std::vector<string>* devices) {
  XlaDeviceFlags* flags = GetXlaDeviceFlags();

	mockDeviceUtil := NewDeviceHandler(&mockOsIOHandler{})
	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)
	}

// CHECK: "tf_device.launch"
// CHECK: device = "CORE_0"
// CHECK: "tf.opA"


// Tests devices are not remapped if device is not in replicate devices.
// CHECK-LABEL: func @no_override_device
func.func @no_override_device() {
  tf_executor.graph {
    %0 = tf_executor.island {
      tf_device.replicate {n = 2 : i32, devices = {CORE_0 = ["/CPU:0", "/GPU:1"]}} {
        "tf_device.launch"() ({
          "tf.opA"() : () -> ()

	podresourcesapi "k8s.io/kubelet/pkg/apis/podresources/v1"
)

// DevicesProvider knows how to provide the devices used by the given container
type DevicesProvider interface {
	// UpdateAllocatedDevices frees any Devices that are bound to terminated pods.
	UpdateAllocatedDevices()
	// GetDevices returns information about the devices assigned to pods and containers
	GetDevices(podUID, containerName string) []*podresourcesapi.ContainerDevices

void AddDevicesToOp(mlir::Operation* op, const DeviceSet* device_set);

// Collects devices information from an op `tf.devices` attributes. Returns
// failure if can't parse device metadata from the attribute.
mlir::LogicalResult GetDevicesFromOp(mlir::Operation* op,
                                     mlir::TF::RuntimeDevices* devices);

// Parses a device string and returns its ordinal (id). This will return an

// which are managed by the devicemapper dm-1.
func (handler *deviceHandler) FindSlaveDevicesOnMultipath(dm string) []string {
	var devices []string
	io := handler.getIo
	// Split path /dev/dm-1 into "", "dev", "dm-1"
	parts := strings.Split(dm, "/")
	if len(parts) != 3 || !strings.HasPrefix(parts[1], "dev") {
		return devices
	}
	disk := parts[2]

    return signalPassFailure();
  }

  // Get the number of devices per host.
  int device_num = 0;
  mlir::TF::RuntimeDevices devices;
  if (failed(tensorflow::GetDevicesFromOp(
          getOperation()->getParentOfType<ModuleOp>(), &devices)))
    return signalPassFailure();
  for (const auto& device_name : devices.device_names()) {
    if (device_name.has_type && device_name.type == "TPU") ++device_num;
  }

// RUN: tf-opt -split-input-file -verify-diagnostics %s -tf-replica-id-to-device-ordinal | FileCheck %s


// Tests device ordinal is set correctly for multiple devices.
// CHECK-LABEL: func @device_ordinal_attr_added_multiple_devices
module attributes {tf.devices = ["/job:worker/replica:0/task:0/device:CPU:0", "/job:worker/replica:0/task:0/device:TPU_SYSTEM:0", "/job:worker/replica:0/task:0/device:TPU:0", "/job:worker/replica:0/task:0/device:TPU:1"]} {

// CHECK-SAME: tfrt_ifrt_serving.program_id = [[PROGRAM_ID]] : i64
// CHECK:      return

// RUN: tf-opt %s -split-input-file -tf-xla-rewrite | FileCheck %s


module attributes {tf.devices = ["/job:worker/replica:0/task:0/device:CPU:0", "/job:worker/replica:0/task:0/device:GPU:0"]} {
  // CHECK-LABEL: func.func @convert_cluster_func
  func.func @convert_cluster_func(%arg0: tensor<i32>) -> tensor<i32> {
    // CHECK: "tf.XlaLaunch"(%arg0) <{function = @func, operandSegmentSizes = array<i32: 0, 1, 0>}> : (tensor<i32>) -> tensor<i32>