as.True(ok)
	checkAllocatableDevicesConsistsOf(as, devInstances, []string{"R1Device1", "R1Device2"})

	// Unhealthy device becomes healthy
	resource1Devs = []pluginapi.Device{
		{ID: "R1Device1", Health: pluginapi.Healthy},
		{ID: "R1Device2", Health: pluginapi.Healthy},
		{ID: "R1Device3", Health: pluginapi.Healthy},
	}
	testManager.genericDeviceUpdateCallback(resourceName1, resource1Devs)

    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()) {

  TF_DeviceList* devices = TFE_ContextListDevices(ctx, status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  const int num_devices = TF_DeviceListCount(devices);

  const char* kCPUDevice = "CPU:0";
  for (int i = 0; i < num_devices; ++i) {
    const string name(TF_DeviceListName(devices, i, status.get()));
    if (TF_GetCode(status.get()) != TF_OK) {

	}
	return err
}

// 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,

  std::vector<std::unique_ptr<Device>> devices;

  DeviceFactory* cpu_factory = DeviceFactory::GetFactory("CPU");
  if (!cpu_factory) {
    return errors::NotFound(
        "CPU Factory not registered. Can't run EncapsulateSubgraphsPass");
  }
  TF_RETURN_IF_ERROR(cpu_factory->CreateDevices(
      session_options, "/job:localhost/replica:0/task:0", &devices));
  if (devices.empty()) {
    return errors::NotFound(

}

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>

// * We could allow NULL for some arguments (e.g., NULL options arg).
//   However since convenience is not a primary goal, we don't do this.
// * Devices are not in this API.  Instead, they are created/used internally
//   and the API just provides high level controls over the number of
//   devices of each type.

#ifdef __cplusplus
extern "C" {
#endif

// --------------------------------------------------------------------------

# builds.
filegroup(
    name = "mobile_srcs_no_runtime",
    srcs = [
        "defs.cc",
        "defs.h",
    ],
    visibility = [":friends"],
)

# Target that bundles up the XLA CPU and GPU JIT devices.
cc_library(
    name = "jit",
    visibility = [
        ":friends",
        "//learning/tfx:__subpackages__",
    ],
    deps = [
        ":xla_cpu_device",
        ":xla_cpu_jit",

    within the same symbol scope as the call and is mapped to a GraphDef node
    with the function name as the op name. Unlike a PartitionedCall which
    represents asynchronously executing a function across multiple devices, a
    LegacyCall ignores specification for ops in the attached function and
    instead executes it on the device assigned to this op.
  }];

  let arguments = (ins
    Variadic<TF_Tensor>:$args,

/** Correct `inline-block` display not defined in IE 8/9. */
audio,
canvas,
video {
	display: inline-block;
}

/** Prevent modern browsers from displaying `audio` without controls. Remove excess height in iOS 5 devices. */
audio:not([controls]) {
	display: none;
	height: 0;
}

/** Address `[hidden]` styling not present in IE 8/9. Hide the `template` element in IE, Safari, and Firefox < 22. */
[hidden],
template {