"encountered session initializers with arguments");
      continue;
    }

    // Since we're now calling this function, savedmodel verification
    // needs it to be private.
    func.setVisibility(SymbolTable::Visibility::Private);
    func->removeAttr("tf_saved_model.exported_names");

    ArrayRef<Value> args;
    builder.create<func::CallOp>(session_initializer.getLoc(),

}

// Convert a savedmodel public function into a private function.
// This means we need to remove any attributes that are only allowed
// on exported (public) functions.
void Unexport(func::FuncOp f) {
  f.setVisibility(mlir::SymbolTable::Visibility::Private);
  f->removeAttr(kTfSavedModelExportedNamesAttr);
  for (int i = 0; i < f.getNumArguments(); ++i) {
    llvm::ArrayRef<mlir::NamedAttribute> attrs =

                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());

    StringRef func_name, IRRewriter::InsertPoint original_point,
    Type quantize_result_type) {
  rewriter.create<func::ReturnOp>(input.getLoc(), ArrayRef<Value>({output}));

  quantization_func.setVisibility(func::FuncOp::Visibility::Private);
  SymbolTable symbol_table(quantized_op->getParentOfType<ModuleOp>());

  symbol_table.insert(quantization_func);

  FlatSymbolRefAttr func_name_attr =

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

  // To form the body of the new function we need to clone each
  // Operation along with its respective operands and result Values(s).

  return !func_op.isPrivate() && IsExported(func_op) &&
         IsEntryFunction(func_op);
}

// Sets a function to be private so it can be referred internally.
void SetFunctionPrivate(func::FuncOp func) {
  func.setVisibility(SymbolTable::Visibility::Private);

  // The `tf_saved_model` attributes can only be applied to public functions.
  for (auto& attr : func->getAttrs()) {
    StringRef attr_name = attr.getName().getValue();

  SmallVector<Location> arg_locs;
  for (Value arg : arguments) {
    arg_locs.push_back(arg.getLoc());
  }

  auto wrap_func = builder.create<func::FuncOp>(location, func_name, func_type);
  wrap_func.setVisibility(SymbolTable::Visibility::Private);
  // The callee function for TF::XlaCallModuleOp must have this attribute.
  if (call_op_type == FunctionCallOpType::TFXlaCallModuleOp) {

  auto stablehlo_func_op = builder.create<func::FuncOp>(
      module_op.getLoc(), CreateStablehloFunctionName(stablehlo_func_id),
      FunctionType::get(ctx, arg_types, result_types));
  stablehlo_func_op.setVisibility(SymbolTable::Visibility::Private);
  stablehlo_func_op->setAttr(TF::kFromXlaCallModuleAttrName,
                             builder.getUnitAttr());

    auto then_branch_op =
        rewriter.create<func::FuncOp>(loc, "cond_true", func_type);
    CreateCondTrueBranch(op, shape_dtype, result_type, then_branch_op,
                         &rewriter);
    then_branch_op.setVisibility(func::FuncOp::Visibility::Private);

    // Constructs `else_branch`, which is executed when `if_cond` evaluates to
    // false.
    auto else_branch_op =

    auto visibility = function.getName() == graph_func_name
                          ? mlir::func::FuncOp::Visibility::Public
                          : mlir::func::FuncOp::Visibility::Private;
    function.setVisibility(visibility);
  }
  VLOG(2) << "Imported: "
          << tensorflow::DumpMlirOpToFile("tf_mlir_imported_base",
                                          module.get());
  return module;
}