for (const std::string& func_name :
       function_library->ReachableDefinitions(graph_def).ListFunctionNames()) {
    const FunctionDef* func_def = function_library->Find(func_name);
    std::unique_ptr<FunctionBody> func_body;
    absl::Status status = FunctionDefToBodyHelper(
        *func_def, AttrSlice(&func_def->attr()), function_library, &func_body);
    // This is not expected to happen in practice
    if (!status.ok()) {

  FunctionLibraryRuntime* flr =
      pflr->GetFLR(ProcessFunctionLibraryRuntime::kDefaultFLRDevice);

  for (Node* node : graph->nodes()) {
    if (CanCreateXlaKernel(node->def())) {
      const FunctionBody* fbody = nullptr;
      std::vector<int> constant_arg_indices;
      std::vector<int> resource_arg_indices;

      NameAttrList function;
      TF_RETURN_IF_ERROR(NameAndAttrsFromFunctionCall(node->def(), &function));

  XlaOpRegistry::RegisterCompilationKernels();

  // Get function body, constant args, and resource args.
  NameAttrList function;
  TF_RETURN_IF_ERROR(NameAndAttrsFromFunctionCall(node_def, &function));
  const FunctionBody* fbody = nullptr;
  std::vector<int> constant_arg_indices;
  std::vector<int> resource_arg_indices;
  TF_RETURN_IF_ERROR(GetBodyAndConstantsAndResources(

// [Experimental]
// Given a Function, returns a MLIR module containing the graph, expressed with
// tf_executor dialect.
absl::StatusOr<mlir::OwningOpRef<mlir::ModuleOp>> ConvertFunctionToMlir(
    const FunctionBody* fbody, const FunctionLibraryDefinition& flib_def,
    mlir::MLIRContext* context);

// Given a SavedModel, returns a MLIR module containing the functions, expressed
// with tf_executor dialect.