ctx->GetAttr("Tconstants", &constant_types));
  std::vector<int> constants(constant_types.size());
  std::iota(constants.begin(), constants.end(), 0);
  return constants;
}

std::vector<int> ResourcesVector(OpKernelConstruction* ctx) {
  DataTypeVector constant_types;
  OP_REQUIRES_OK_RETURN(ctx, std::vector<int>(),
                        ctx->GetAttr("Tconstants", &constant_types));

    cc_type v;                                                                 \
    auto* cc_ctx = reinterpret_cast<::tensorflow::OpKernelConstruction*>(ctx); \
    absl::Status s = cc_ctx->GetAttr(attr_name, &v);                           \
    ::tensorflow::Set_TF_Status_from_Status(status, s);                        \
    if (s.ok()) {                                                              \

	includeMx bool,
) []*listener.Filter {
	idleTimeout := destinationRule.GetTrafficPolicy().GetConnectionPool().GetTcp().GetIdleTimeout()
	if idleTimeout == nil {
		idleTimeout = parseDuration(lb.node.Metadata.IdleTimeout)
	}
	tcpProxy := &tcp.TcpProxy{
		StatPrefix:                      statPrefix,

func NewCachingConfigMapManager(kubeClient clientset.Interface, getTTL manager.GetObjectTTLFunc) Manager {
	getConfigMap := func(namespace, name string, opts metav1.GetOptions) (runtime.Object, error) {
		return kubeClient.CoreV1().ConfigMaps(namespace).Get(context.TODO(), name, opts)
	}
	configMapStore := manager.NewObjectStore(getConfigMap, clock.RealClock{}, getTTL, defaultTTL)
	return &configMapManager{

func NewCachingSecretManager(kubeClient clientset.Interface, getTTL manager.GetObjectTTLFunc) Manager {
	getSecret := func(namespace, name string, opts metav1.GetOptions) (runtime.Object, error) {
		return kubeClient.CoreV1().Secrets(namespace).Get(context.TODO(), name, opts)
	}
	secretStore := manager.NewObjectStore(getSecret, clock.RealClock{}, getTTL, defaultTTL)
	return &secretManager{

  void runOnOperation() override {
    auto module = getOperation();
    // If TFLite variable legalization is not allowed, then we skip this pass.
    if (auto legalize_tfl_variables_attr =
            module->getAttr(kLegalizeTflVariables)) {
      if (!mlir::cast<BoolAttr>(legalize_tfl_variables_attr).getValue()) return;
    }

    RewritePatternSet patterns(&getContext());
    populateWithGenerated(patterns);

    }
  }

  if (!in_order) {
    // Functions do not get reused in practice, so skip the check for if the
    // callee has been updated.
    StringAttr callee_sym = cluster_func_op.getFuncAttr().getAttr();
    MoveResourceArgsToEnd(symtab.lookup<func::FuncOp>(callee_sym));
  }
  builder.setInsertionPoint(cluster_func_op);
  auto xla_launch_op = builder.create<TF::XlaLaunchOp>(

  StringAttr device = mlir::cast<StringAttr>(
      added_func_op->getRegion(0).getBlocks().front().front().getAttr(kDevice));
  StringAttr inference_type = mlir::cast<StringAttr>(
      added_func_op->getRegion(0).getBlocks().front().front().getAttr(
          kInferenceType));
  added_call_op->setAttr(kDevice, device);
  added_call_op->setAttr(kInferenceType, inference_type);

  LogicalResult matchAndRewrite(mlir::stablehlo::CustomCallOp op,
                                PatternRewriter &rewriter) const override {
    auto backendConfig =
        mlir::dyn_cast<DictionaryAttr>(op->getAttr("composite.backend_config"));
    if (!backendConfig)
      return op->emitError(
          "custom_call has no 'composite.backend_config' attribute or the "
          "attribute is not a dictionary");

    if (op->getDialect() != tf_dialect) return WalkResult::advance();

    if (parallel_group_attr) {
      op->setAttr(TF::kParallelExecAnnotation, parallel_group_attr);
    }
    auto device_attr = op->getAttr(kDeviceAttr);
    if (!device_attr) {
      op->setAttr(kDeviceAttr, launch.getDeviceAttr());
      return WalkResult::advance();
    }

    if (auto device_str_attr = mlir::dyn_cast<StringAttr>(device_attr)) {