auto op = builder.create<CustomOp>(
      func.getLoc(), func.getFunctionType().getResults(), func.getArguments(),
      api, CustomOption(&builder, custom_option_buffer));
  builder.create<func::ReturnOp>(func.getLoc(), op.getResults());
  return success();
}

LogicalResult VerifySgnnProjection(func::FuncOp func, FuncAttr attr) {
  if (func.getFunctionType().getNumInputs() != 2 ||
      func.getFunctionType().getNumResults() != 1) {

### Passo 4: defina uma **função de rota**

Esta é a nossa "**função de rota**":

* **rota**: é `/`.
* **operação**: é `get`.
* **função**: é a função abaixo do "decorador" (abaixo do `@app.get("/")`).

```Python hl_lines="7"
{!../../../docs_src/first_steps/tutorial001.py!}
```

Esta é uma função Python.

  func->setAttr(kTfSavedModelExportedNamesAttr,
                builder.getStrArrayAttr({kSessionInitFuncName}));
  func->setAttr(kTfSavedModelInitializerTypeAttr,
                builder.getStringAttr(kTfSavedModelInitializerRestoreType));
  func.setVisibility(mlir::func::FuncOp::Visibility::Public);
  auto func_builder = OpBuilder::atBlockBegin(func.addEntryBlock());
  func_builder.create<mlir::func::ReturnOp>(func.getLoc());

// qint types to int types and surround TF UniformQuantized ops with qint <->
// int casts.
std::unique_ptr<OperationPass<func::FuncOp>> CreateConvertTFQuantTypesPass();

// Creates an instance of the VerifyQuantLegalization pass, which verifies all
// quant ops and types are lowered.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateVerifyQuantLegalizationPass();

// Add all passes for lowering TF quant ops and types to MHLO int.

bool IsMainOrInitializerFunction(ModuleOp module, func::FuncOp func) {
  if (func.getSymName() ==
          llvm::StringRef(tensorflow::kImportModelDefaultGraphFuncName) ||
      func.getSymName() == kTfQuantSaveFuncName) {
    return true;
  }

  for (func::FuncOp init_func :
       tf_saved_model::GetInitializerFunctions(module)) {
    if (func.getSymName() == init_func.getSymName()) {
      return true;
    }

  ASSERT_TRUE(result);
  EXPECT_EQ(noinline_pcall_ops.size(), 2);
  auto func =
      llvm::dyn_cast<mlir::func::FuncOp>(noinline_pcall_ops[0]->getParentOp());
  ASSERT_TRUE(func);
  EXPECT_EQ(func.getSymName(), "while_body_func");
  func =
      llvm::dyn_cast<mlir::func::FuncOp>(noinline_pcall_ops[1]->getParentOp());
  ASSERT_TRUE(func);
  EXPECT_EQ(func.getSymName(), "outer_stateful_pcall_func");

    // restriction, it would require tensor cast ops.
    func::FuncOp parent_op = op->getParentOfType<func::FuncOp>();
    if (!llvm::hasSingleElement(parent_op)) return failure();

    // Find the then and else branch functions.
    func::FuncOp then_func = op.then_function();
    func::FuncOp else_func = op.else_function();

    // If the If has no uses and its functions are side-effect free, then

// Create an instance of the TargetAnnotationPass.
// TODO(b/177376459): Remove in favor of the one below.
std::unique_ptr<OperationPass<func::FuncOp>> CreateTargetAnnotationPass(
    llvm::ArrayRef<std::string> device_specs);

// Create and instance of TargetAnnotationPass.
std::unique_ptr<OperationPass<func::FuncOp>> CreateTargetAnnotationPass(
    const TacModule* module);

			if ipk == 0 {
				fmt.Fprintf(os.Stderr, "\n")
				reportErrorInHardcodedList(int32(i), ipk, funcId, nCtrs)
			} else if ipk < 0 {
				if newId, ok := s.pkgmap[int(ipk)]; ok {
					pkgId = uint32(newId)
				} else {
					fmt.Fprintf(os.Stderr, "\n")
					reportErrorInHardcodedList(int32(i), ipk, funcId, nCtrs)
				}
			} else {
				// The package ID value stored in the counter array

	FuncFlagAsm
)

// A FuncID identifies particular functions that need to be treated
// specially by the runtime.
// Note that in some situations involving plugins, there may be multiple
// copies of a particular special runtime function.
type FuncID uint8

const (
	// If you add a FuncID, you probably also want to add an entry to the map in
	// ../../cmd/internal/objabi/funcid.go