b := 3
			return func(y int) int { // ERROR "can inline main.func27.1" "can inline main.main.func27.func34"
				c := 5
				return func(z int) int { // ERROR "can inline main.func27.1.1" "can inline main.main.func27.func34.1" "can inline main.func27.main.func27.1.2" "can inline main.main.func27.main.main.func27.func34.func36"
					return a*x + b*y + c*z
				}(10) // ERROR "inlining call to main.func27.1.1"

// This pass is used to fold tfl.const ops to each subgraph (func::FuncOp):
// See the example below:
//
// In main:
// %0 = tfl.const...
// %1 = tfl.const...
// %2 = call func_1(..., %0,...)
// %3 = call func_2(..., %0, ..., %1...)
// ...
//
// Then those consts will be copied into each function and replace their usage.
// func_1:
//   %0 = tfl.const...
// func_2:
//   %0 = tfl.const...
//   %1 = tfl.const...

// Returns true iff the function's symbol is public.
bool IsPublicFuncOp(func::FuncOp func_op) {
  return SymbolTable::getSymbolVisibility(&*func_op) ==
         SymbolTable::Visibility::Public;
}

}  // namespace

func::FuncOp FindMainFuncOp(ModuleOp module_op) {
  if (const auto main_func_op = module_op.lookupSymbol<func::FuncOp>(
          kImportModelDefaultGraphFuncName);

void ConvertNMSPaddedFunc::RewriteFunc() {
  func_->setAttr(kTFImplements,
                 StringAttr::get(func_.getContext(), kTfNMSPadded));
  Value boxes = func_.getArgument(0);
  Value scores = func_.getArgument(1);
  Value max_output_size = func_.getArgument(2);
  Value iou_threshold = func_.getArgument(3);
  Value score_threshold = func_.getArgument(4);
  auto output_type0 = func_.getFunctionType().getResult(0);

LogicalResult ConvertDenseImageWarpFunc::RewriteFunc() {
  func_.eraseBody();
  func_.addEntryBlock();
  func_->setAttr(kTFImplements,
                 StringAttr::get(func_.getContext(), kImageWarping));

  OpBuilder builder(func_.getBody());
  auto op = builder.create<CustomOp>(func_.getLoc(),
                                     func_.getFunctionType().getResults(),
                                     func_.getArguments(), kImageWarping,

	"deferreturn": abi.FuncIDWrapper,
}

// Get the function ID for the named function in the named file.
// The function should be package-qualified.
func GetFuncID(name string, isWrapper bool) abi.FuncID {
	if isWrapper {
		return abi.FuncIDWrapper
	}
	if strings.HasPrefix(name, "runtime.") {
		if id, ok := funcIDs[name[len("runtime."):]]; ok {
			return id
		}
	}

	// the rest of the test, they will block.
	go func() { // func1
		select {}
	}()
	go func() { // func2
		var c chan int
		c <- 0
	}()
	go func() { // func3
		var c chan int
		<-c
	}()
	done1 := make(chan bool)
	go func() { // func4
		<-done1
	}()
	done2 := make(chan bool)
	go func() { // func5
		done2 <- true
	}()
	c1 := make(chan int)
	c2 := make(chan int)

      builder.getFunctionType(input_types, return_types);

  std::string function_name = absl::StrCat("func_", subgraph.subgraph_id_);

  func::FuncOp new_func = func::FuncOp::create(builder.getUnknownLoc(),
                                               function_name, function_type);
  new_func.setVisibility(func::FuncOp::Visibility::Private);
  new_func.addEntryBlock();

Por exemplo, se você precisar armazená-lo em um banco de dados.

Para isso, **FastAPI** fornece uma função `jsonable_encoder()`.

## Usando a função `jsonable_encoder`

Vamos imaginar que você tenha um banco de dados `fake_db` que recebe apenas dados compatíveis com JSON.

                               TF::kStablehloEntryFunctionAttrName)
                           .getValue();
  func::FuncOp func_op = symbol_table.lookup<func::FuncOp>(function_name);

  // We should not unwrap if the function is not from
  // ReplaceStablehloOpsInMainFunctionWithXlaCallModuleOpsPass.
  if (!func_op->hasAttr(TF::kFromXlaCallModuleAttrName)) {
    return;
  }

  MLIRContext* context = call_op.getContext();