%2 = func.call @func_2_CPU_FLOAT(%0, %1) {tac.device = "CPU", tac.inference_type = "FLOAT", tac.interface_name = "func_2"} : (tensor<100xf32>, tensor<100xf32>) -> tensor<2x100xf32>
    func.return %2 : tensor<2x100xf32>
  }

module {
  func.func @simpleTest(%arg0: tensor<1xf32>, %arg1: tensor<1xf32>, %arg2: tensor<1xf32>, %arg3: tensor<1xf32>) -> tensor<2x1xf32> {
    %0 = func.call @func_0_GPU_FLOAT(%arg0, %arg1, %arg2) {tac.interface_name = "func_0"} : (tensor<1xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>
    %1 = func.call @func_1_GPU_FLOAT(%arg0, %arg3) {tac.interface_name = "func_1"} : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>

 public:
  explicit ConvertEmbeddedLookupFunc(func::FuncOp func) : func_(func) {}

  void RewriteFunc() {
    func_->setAttr(kTFImplements,
                   StringAttr::get(func_.getContext(), "embedding_lookup"));
    Value lookup = func_.getArgument(1);
    Value value = func_.getArgument(0);
    auto output_type = func_.getFunctionType().getResult(0);

    OpBuilder builder(func_.getBody());

    ret_operands.push_back(operand->getValue());
  }
  builder_.create<func::ReturnOp>(func_.getLoc(), ret_operands);

  auto arg_types = body.getArgumentTypes();
  auto result_types = body.getTerminator()->getOperandTypes();
  func_.setType(FunctionType::get(func_.getContext(), arg_types, result_types));
  *f = new MlirFunction(std::move(context_), std::move(module_), func_);
  return absl::OkStatus();
}

extern "C" {

func funcpctab(ctxt *Link, func_ *LSym, desc string, valfunc func(*Link, *LSym, int32, *Prog, int32, interface{}) int32, arg interface{}) *LSym {
	dbg := desc == ctxt.Debugpcln
	dst := []byte{}
	sym := &LSym{
		Type:      objabi.SRODATA,
		Attribute: AttrContentAddressable | AttrPcdata,
	}

	if dbg {
		ctxt.Logf("funcpctab %s [valfunc=%s]\n", func_.Name, desc)
	}

	val := int32(-1)
	oldval := val

	return m
}

// addValueFuncs adds to values the functions in funcs, converting them to reflect.Values.
func addValueFuncs(out map[string]reflect.Value, in FuncMap) {
	for name, fn := range in {
		if !goodName(name) {
			panic(fmt.Errorf("function name %q is not a valid identifier", name))
		}
		v := reflect.ValueOf(fn)
		if v.Kind() != reflect.Func {
			panic("value for " + name + " not a function")
		}

  TF_Function* funcs[1];
  DefineFunction(func_name_, &func_);

  TF_GraphCopyFunction(func_graph_, func_, nullptr, s_);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  EXPECT_EQ(TF_GraphNumFunctions(func_graph_), 1);
  EXPECT_EQ(TF_GraphGetFunctions(func_graph_, funcs, 1, s_), 1);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  TF_GraphRemoveFunction(func_graph_, func_name_, s_);

func (n *Func) editChildren(edit func(Node) Node)           { editNodes(n.Body, edit) }
func (n *Func) editChildrenWithHidden(edit func(Node) Node) { editNodes(n.Body, edit) }

func (f *Func) Type() *types.Type                { return f.Nname.Type() }
func (f *Func) Sym() *types.Sym                  { return f.Nname.Sym() }
func (f *Func) Linksym() *obj.LSym               { return f.Nname.Linksym() }

  ASSERT_TRUE(module_op);

  auto func_op = module_op->lookupSymbol<func::FuncOp>("fully_quantized_add");
  ASSERT_THAT(func_op, NotNull());

  auto add_op_itr = func_op.getBody().op_begin<mlir::stablehlo::AddOp>();
  ASSERT_THAT(add_op_itr,
              Ne(func_op.getBody().op_end<mlir::stablehlo::AddOp>()));

  EXPECT_TRUE(IsOpFullyQuantized(*add_op_itr));
}

      }
      SymbolTable::setSymbolName(func_op, new_func_name);
    }
    // Move all functions from XlaCallModuleOp's stablehlo module, to parent
    // module. Also marks the stablehlo module entry function as private.
    func::FuncOp main_fn;
    for (auto func_op : stablehlo_module_op.get().getOps<func::FuncOp>()) {
      func::FuncOp cloned_func_op = func_op.clone();
      if (IsShloMainFuncOp(cloned_func_op)) {