type wrappedManagerImpl struct {
	*ManagerImpl
	socketdir string
	callback  func(string, []pluginapi.Device)
}

func (m *wrappedManagerImpl) PluginListAndWatchReceiver(r string, resp *pluginapi.ListAndWatchResponse) {
	var devices []pluginapi.Device
	for _, d := range resp.Devices {
		devices = append(devices, *d)
	}
	m.callback(r, devices)
}

func tmpSocketDir() (socketDir, socketName, pluginSocketName string, err error) {

    const Cluster& cluster_a, const Cluster& cluster_b) {
  DeviceSet devices = cluster_a.devices();
  devices.UnionWith(cluster_b.devices());

  TF_ASSIGN_OR_RETURN(
      std::optional<jit::DeviceId> maybe_chosen_device,
      MaybePickDeviceForXla(device_info_cache_, devices,
                            /*allow_mixing_unknown_and_cpu=*/false));
  if (!maybe_chosen_device.has_value()) {

    }
    auto tag = tensorflow::strings::StrCat("Device #", i, " (", name, ")");
    // Copy to device
    TFE_TensorHandle* hdevice =
        TFE_TensorHandleCopyToDevice(hcpu, ctx, name.c_str(), status.get());
    if (TF_GetCode(status.get()) != TF_OK) {
      ADD_FAILURE() << tag << " -- " << TF_Message(status.get());
      continue;
    }
    // Copy from device to the same device.
    TFE_TensorHandle* hdevice2 =

}

// makeDevices generates container devices for kubelet runtime v1.
func makeDevices(opts *kubecontainer.RunContainerOptions) []*runtimeapi.Device {
	devices := make([]*runtimeapi.Device, len(opts.Devices))

	for idx := range opts.Devices {
		device := opts.Devices[idx]
		devices[idx] = &runtimeapi.Device{
			HostPath:      device.PathOnHost,
			ContainerPath: device.PathInContainer,
			Permissions:   device.Permissions,

// DICS_STATE specifies values indicating a change in a device's state
type DICS_STATE uint32

const (
	DICS_ENABLE     DICS_STATE = 0x00000001 // The device is being enabled.
	DICS_DISABLE    DICS_STATE = 0x00000002 // The device is being disabled.
	DICS_PROPCHANGE DICS_STATE = 0x00000003 // The properties of the device have changed.

      session_options, "/job:localhost/replica:0/task:0", &devices));
  if (devices.empty()) {
    return errors::NotFound(
        "Failed to create a CPU device for EncapsulateSubgraphsPass");
  }

  std::unique_ptr<DeviceMgr> device_mgr =
      std::make_unique<StaticDeviceMgr>(std::move(devices));
  const auto* config = &options.session_options->config;

}

void ExtractOutsideCompilation::runOnOperation() {
  // Get runtime devices information from the closest parent module.
  auto module = getOperation();
  if (failed(CheckPreconditions(module))) signalPassFailure();

  mlir::TF::RuntimeDevices devices;
  if (failed(tensorflow::GetDevicesFromOp(module, &devices)))
    return signalPassFailure();

  llvm::SmallVector<mlir::tf_device::ParallelExecuteOp, 4>

    to change, and the implementation is incomplete. This is a big new API we
    are eager for feedback.

 *  New: Support ALPN via Google Play Services' Dynamic Security Provider. This
    expands HTTP/2 support to older Android devices that have Google Play
    Services.
 *  New: Consider all routes when looking for candidate coalesced connections.
    This increases the likelihood that HTTP/2 connections will be shared.

    TF_ImportGraphDefOptions* opts, const char* prefix);

// Set the execution device for nodes in `graph_def`.
// Only applies to nodes where a device was not already explicitly specified.
// `device` is copied and has no lifetime requirements.
TF_CAPI_EXPORT extern void TF_ImportGraphDefOptionsSetDefaultDevice(
    TF_ImportGraphDefOptions* opts, const char* device);

// Set whether to uniquify imported operation names. If true, imported operation

        "-parse_headers",  # buildifier: disable=no-parse-headers
    ],
    deps = [":get_compiler_ir_hdrs"],
)

# This target can be used by XLA device plugins to prevent circular dependencies, and provides access to all of the required headers for building a device library.
cc_header_only_library(
    name = "xla_jit_headers_lib",
    visibility = ["//visibility:public"],
    deps = [
        ":xla_cpu_device",