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

namespace tensorflow {

// Collects all devices known to the system by name and adds them as a
// `tf.devices` dictionary attribute with a full device name as a key, and
// device metadata as a value.
//
// Device names added in full parsed device form:
//   /job:<name>/replica:<replica>/task:<task>/device:<type>:<device_num>
//
// Supported device metadata types:
// (1) GpuDeviceMetadata: GPU device compute capability.

// CHECK: device = "/TPU:2"
// CHECK: "tf.opA"


// Tests devices are remapped if device is in replicate devices.
// CHECK-LABEL: func @remap_device
func.func @remap_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"() : () -> ()
          tf_device.return

};

// Caches some miscellaneous information about TF devices.  Thread compatible.
class DeviceInfoCache {
 public:
  bool IsGpu(DeviceId device) const { return is_gpu_[device.id()]; }
  bool IsCpu(DeviceId device) const { return is_cpu_[device.id()]; }

  absl::string_view GetNameFor(DeviceId device) const {
    return names_[device.id()];
  }

  absl::StatusOr<DeviceId> GetIdFor(absl::string_view name);

	if len(parts) != 3 || !strings.HasPrefix(parts[1], "dev") {
		return devices
	}
	disk := parts[2]
	slavesPath := filepath.Join("/sys/block/", disk, "/slaves/")
	if files, err := io.ReadDir(slavesPath); err == nil {
		for _, f := range files {
			devices = append(devices, filepath.Join("/dev/", f.Name()))
		}
	}
	return devices
}

// GetISCSIPortalHostMapForTarget given a target iqn, find all the scsi hosts logged into

    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;
  }

    SessionOptions options;
    std::vector<std::unique_ptr<Device>> devices;
    Status s = device_factory->CreateDevices(
        options, "/job:worker/replica:0/task:0", &devices);
    device_ = std::move(devices[0]);

    tensorflow::AllocatorAttributes host_alloc_attr;
    host_alloc_attr.set_on_host(true);
    host_allocator_ = device_->GetAllocator(host_alloc_attr);

func.func @serving_default(%arg0: tensor<1x3xf32>) -> () {
  %outputs  =  "tf.TPUCompilationResult"() {_tpu_compilation_status = "cluster", device = ""} : () -> tensor<!tf_type.string>

	}

	if err := validateVendorName(vendor); err != nil {
		return "", "", device, fmt.Errorf("invalid device %q: %v", device, err)
	}
	if err := validateClassName(class); err != nil {
		return "", "", device, fmt.Errorf("invalid device %q: %v", device, err)
	}
	if err := validateDeviceName(name); err != nil {
		return "", "", device, fmt.Errorf("invalid device %q: %v", device, err)
	}

	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