var q ir.NameQueue

	for _, fn := range typecheck.Target.Funcs {
		symToFunc[fn.LSym] = fn

		// Make nowritebarrierrec functions BFS roots.
		if fn.Pragma&ir.Nowritebarrierrec != 0 {
			funcs[fn] = nowritebarrierrecCall{}
			q.PushRight(fn.Nname)
		}
		// Check go:nowritebarrier functions.
		if fn.Pragma&ir.Nowritebarrier != 0 && fn.WBPos.IsKnown() {
			base.ErrorfAt(fn.WBPos, 0, "write barrier prohibited")
		}
	}

    signalPassFailure();
    return;
  }

  // Copy all functions used by this signature to the final MLIR module.
  for (func::FuncOp func : module_ref->getOps<func::FuncOp>()) {
    // Do nothing if the function already exists.
    if (symbol_table.lookup(func.getSymName()) != nullptr) continue;

    // Set the function to private and insert to the module.
    func::FuncOp new_func = func.clone();

  MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(OptimizeFunctionalOpsPass)

  void runOnOperation() override;
};

// Updates function return type of the given functions to match the terminator
// op operands' types.
//
// Requires the function has exactly one block.
void UpdateFuncType(func::FuncOp func) {
  Operation* terminator = func.front().getTerminator();

final class MainKt$ArticleScreenContent$1$1 {
    // source: 'main.kt'
    enclosing method MainKt$ArticleScreenContent$1.invoke()Lkotlin/jvm/functions/Function0;
    synthetic final field $title: java.lang.String
    inner (anonymous) class MainKt$ArticleScreenContent$1
    inner (anonymous) class MainKt$ArticleScreenContent$1$1
    method <init>(p0: java.lang.String): void
    public synthetic bridge method invoke(): java.lang.Object

    // functional form, all such external values need to become function
    // arguments of the outlined functions, and become pass through values in
    // the outlined body function. So when outlining the while body, in addition
    // to the region arguments, all these external references need to be added
    // as function arguments.
    llvm::SmallVector<Value, 4> extern_values =

constexpr char kResourceFunctionMsg[] =
    "expects function level resource argument";
constexpr char kInvalidResourceMsg[] =
    "expects resource to be a VarHandleOp or function argument";
constexpr char kResourceNameArgAttr[] = "tf.resource_name";

// Checks if a function has only one block.
mlir::LogicalResult CheckSingleBlockFunction(func::FuncOp function) {
  if (!llvm::hasSingleElement(function)) {
    return function.emitError()

// function name when loading it back.
inline constexpr StringRef kOriginalStablehloEntryFunctionAttrName =
    "_original_entry_function";

// FunctionCallOpType to be generated as the function call operator when
// function lifting will happen.
enum FunctionCallOpType { TFPartitionedCallOp = 0, TFXlaCallModuleOp = 1 };

// Checks if an op is inside a lifted function.

                    val functions = superClassSymbol.getDeclaredMemberScope().getAllSymbols()
                        .filterIsInstance<KaFunctionSymbol>()
                        .toList()
                    if (functions.isNotEmpty()) {
                        appendLine("Substituted callables:")
                        withIndent {
                            for (function in functions) {

// function, which might not exist in case of multi-signature graphs. In that
// case, this pass will create a new main function, which calls signature
// functions.
//
// An already existing @main function will be renamed by attaching a numeric
// suffix like `@main_0` to avoid conflict with the newly created main function.
class InsertMainFunctionPass

    mlir::ModuleOp module, const GraphExportConfig& configs);

// Converts an MLIR module to TensorFlow graph and FunctionLibraryDefinition.
// The "main" function of the module is stored in the graph and the rest of
// functions are stored in the library. Control ret nodes are stored separately
// in `control_ret_nodes`.
Status ConvertMlirToGraph(mlir::ModuleOp module,