return err
		}
	} else {
		// Add single devicepath to devices
		devices = append(devices, dstPath)
	}
	klog.V(4).Infof("fc: DetachDisk devicePath: %v, dstPath: %v, devices: %v", devicePath, dstPath, devices)
	var lastErr error
	for _, device := range devices {
		err := util.detachFCDisk(c.io, c.exec, device)
		if err != nil {
			klog.Errorf("fc: detachFCDisk failed. device: %v err: %v", device, err)

 private:
  void runOnOperation() override;

  // Given a func and targeted devices, we will try to clonse the func &
  // transform/optimize for those devices.
  // This will only happen if the whole subgraph can be supported by the target
  // or can be supported after some transformations.
  void GetAlternativeGraphForFunc(ArrayRef<std::string> devices,
                                  func::FuncOp func, ModuleOp module,

// 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"]} {

  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());

  std::vector<std::string> devices{
      "/job:localhost/replica:0/task:0/device:CPU:0",
      "/job:localhost/replica:0/task:0/device:CPU:1"};
  ParallelDevice parallel_device(std::move(devices));
  std::unique_ptr<TFE_Op, decltype(&TFE_DeleteOp)> handle_op(
      TFE_NewOp(context.get(), "VarHandleOp", status.get()), TFE_DeleteOp);

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

   */
  public static final byte DLE = 16;

  /**
   * Device Control 1. Characters for the control of ancillary devices associated with data
   * processing or telecommunication systems, more especially switching devices "on" or "off." (If a
   * single "stop" control is required to interrupt or turn off ancillary devices, DC4 is the
   * preferred assignment.)
   *
   * @since 8.0
   */

// 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>

### This jcifs or jcifs-ng

jcifs-ng will be a proper choice for many users. 
There are a lot of SMB devices in the world.
Some of them only work with the old jcifs library.
If you want to support many SMB devices, CodeLibs jcifs library will be helpful.
For example, since [Fess](https://github.com/codelibs/fess) needs to support many SMB devices, it uses this library.