let description = [{
    The ExecuteOp executes an operation on the specified device using a custom device.
  }];

  let arguments = (ins
    TFDeviceType:$device,
    Variadic<TFTensorType>:$args,
    StrAttr:$node_def,
    I32Attr:$op_key
  );

  let results = (outs
    Variadic<TFTensorType>:$results
  );

    DeviceBase* device, const XlaDevice::Metadata** metadata) {
  *metadata = nullptr;
  XlaDevice* xla_device = dynamic_cast<XlaDevice*>(device->UnderlyingDevice());
  if (xla_device == nullptr) {
    return errors::Internal(
        "Cannot get XLA metadata from non-XLA device \"", device->name(),
        "\". GetMetadata must only be called on an XLA device. Either an "

CreateConvertReadonlyReferenceVariablesToResourceVariablesPass();

// Creates a simple device assignment pass on TF dialect for CoreRT use case.
std::unique_ptr<OperationPass<func::FuncOp>> CreateSimpleTFDeviceAssignmentPass(
    llvm::StringRef default_device = "cpu");

// Creates a pass to perform device assignment for TF dialect ops that do not
// have device assignment, by using the device attribute of the function.
std::unique_ptr<OperationPass<func::FuncOp>>

}

def SimpleTFDeviceAssignmentPass : Pass<"tf-simple-device-assignment", "mlir::func::FuncOp"> {
  let summary = "Simple device assignment in TF dialect.";
  let constructor = "TF::CreateSimpleTFDeviceAssignmentPass()";
  let options = [
    Option<"default_device_", "default-device", "std::string", /*default=*/"\"cpu\"",
           "The default device to assign.">
  ];
  let description = [{

    const ResourceHandle& resource_handle =
        resource_tensor.scalar<ResourceHandle>()();

    Device* device;
    if (!(device_manager->LookupDevice(resource_handle.device(), &device)
              .ok())) {
      return module.emitOpError() << "failed to look up device";
    }

    tensorflow::Var* var_ptr;
    if (!(device->resource_manager()
              ->Lookup(resource_handle.container(), resource_handle.name(),

  });
}

// Copies attributes that are either `device` or whose name begins with an _
// from `from` to `to`.
// TODO(b/158769932): This should be a general feature instead post some policy
// discussion.
inline void CopyDeviceAndUnderscoredAttributes(Operation *from, Operation *to) {
  auto device = mlir::StringAttr::get(from->getContext(), "device");
  CopyAttributes(from, to, [&device](const NamedAttribute &attr) {

	require.NoError(t, err)
	defer os.RemoveAll(socketDir)
	m, _, p, _ := setupInProbeMode(t, []*pluginapi.Device{}, func(n string, d []pluginapi.Device) {}, socketName, pluginSocketName)
	cleanup(t, m, p)
}

// Tests that the device plugin manager correctly handles registration and re-registration by
// making sure that after registration, devices are correctly updated and if a re-registration

  %cst = "tf.Const"() <{value = dense<1> : tensor<i32>}> {device = ""} : () -> tensor<i32>
  %0 = "tf.MultiDeviceIteratorFromStringHandle"(%arg0) <{output_shapes = [#tf_type.shape<>], output_types = [!tf_type.string]}> {device = ""} : (tensor<!tf_type.string>) -> tensor<!tf_type.resource>
  %1 = "tf.MultiDeviceIteratorGetNextFromShard"(%0, %cst, %arg1) {device = ""} : (tensor<!tf_type.resource>, tensor<i32>, tensor<i64>) -> tensor<!tf_type.string>

    const StreamExecutorConfig& config) {
  // Fill device creation params
  SE_CreateDeviceParams device_params{SE_CREATE_DEVICE_PARAMS_STRUCT_SIZE};
  SP_Device device{SP_DEVICE_STRUCT_SIZE};
  device_params.device = &device;
  device_params.ext = nullptr;
  device_params.ordinal = config.ordinal;
  OwnedTFStatus c_status(TF_NewStatus());

  // Create Device

// and pod device map path.
type BlockVolume interface {
	// GetGlobalMapPath returns a global map path which contains
	// bind mount associated to a block device.
	// ex. plugins/kubernetes.io/{PluginName}/{DefaultKubeletVolumeDevicesDirName}/{volumePluginDependentPath}/{pod uuid}
	GetGlobalMapPath(spec *Spec) (string, error)
	// GetPodDeviceMapPath returns a pod device map path