FunctionDef empty_function =
      tensorflow::FunctionDefHelper::Create("empty", {}, {}, {}, {}, {});

  tensorflow::FunctionDefLibrary fdef;
  *(fdef.add_function()) = empty_function;
  tensorflow::FunctionLibraryDefinition flib_def(
      tensorflow::OpRegistry::Global(), fdef);

  OpInputList guaranteed_constants;
  NameAttrList function;
  function.set_name("empty");

  // so we define the `graph_` by the following `flib` in this test point
  // instead of the way we do in the Init method.
  FunctionDefLibrary flib;
  *flib.add_function() = XTimesTwo();
  FunctionLibraryDefinition flib_def(OpRegistry::Global(), flib);
  graph_ = std::make_unique<Graph>(flib_def);

  GraphDef original_graph_def;
  graph_->ToGraphDef(&original_graph_def);

}

TEST(LegalizeTFTest, RecordsStreamzForNoMlirFallback) {
  FunctionDef my_func =
      tensorflow::FunctionDefHelper::Create("empty", {}, {}, {}, {}, {});

  tensorflow::FunctionDefLibrary fdef;
  *(fdef.add_function()) = my_func;
  tensorflow::FunctionLibraryDefinition flib_def(
      tensorflow::OpRegistry::Global(), fdef);

  OpInputList guaranteed_constants;
  NameAttrList function;

}

TEST(EncapsulateXlaComputations, BuildXlaLaunchOp) {
  std::unique_ptr<Graph> body_graph = MakeBodyGraph();
  FunctionDefLibrary flib;
  TF_ASSERT_OK(GraphToFunctionDef(*body_graph, "launch0", flib.add_function()));

  FunctionLibraryDefinition flib_def(OpRegistry::Global(), flib);

  std::unique_ptr<Graph> graph = MakeOuterGraph(flib_def, "launch0");

	DIF_DETECT                         DI_FUNCTION = 0x0000000F
	DIF_INSTALLWIZARD                  DI_FUNCTION = 0x00000010
	DIF_DESTROYWIZARDDATA              DI_FUNCTION = 0x00000011
	DIF_PROPERTYCHANGE                 DI_FUNCTION = 0x00000012
	DIF_ENABLECLASS                    DI_FUNCTION = 0x00000013
	DIF_DETECTVERIFY                   DI_FUNCTION = 0x00000014
	DIF_INSTALLDEVICEFILES             DI_FUNCTION = 0x00000015

        singleTypeParameterRenderer = KaSingleTypeParameterSymbolRenderer.WITHOUT_BOUNDS
        samConstructorRenderer = KaSamConstructorSymbolRenderer.AS_FUNCTION
        typeRenderer = KaTypeRendererForDebug.WITH_QUALIFIED_NAMES
        declarationTypeApproximator = KaRendererTypeApproximator.NO_APPROXIMATION
    }

            symbol: KaSamConstructorSymbol,
            declarationRenderer: KaDeclarationRenderer,
            printer: PrettyPrinter,
        ) {
            printer {}
        }
    }

    public object AS_FUNCTION : KaSamConstructorSymbolRenderer {
        override fun renderSymbol(
            analysisSession: KaSession,
            symbol: KaSamConstructorSymbol,
            declarationRenderer: KaDeclarationRenderer,

		}
		symbolizeOneMapping(m, locs, f, addFunction)
		f.Close()
	}

	if missingBinaries {
		ui.PrintErr("Some binary filenames not available. Symbolization may be incomplete.\n" +
			"Try setting PPROF_BINARY_PATH to the search path for local binaries.")
	}
	return nil
}

func symbolizeOneMapping(m *profile.Mapping, locs []*profile.Location, obj plugin.ObjFile, addFunction func(*profile.Function) *profile.Function) {

    }

    def renameSourceFile(SourceFile sourceFile, String name) {
        return new SourceFile(sourceFile.path, name, sourceFile.content)
    }

    def addFunction(SourceFile sourceFile) {
        return new SourceFile(sourceFile.path, sourceFile.name, sourceFile.content + """
            // Extra function to ensure library has different size
            int otherFunction() {

      "    }",
      &def));
  return def.SerializeAsString();
}

// a + a
string AddFunction() {
  tensorflow::FunctionDef def;
  CHECK(tensorflow::protobuf::TextFormat::ParseFromString(
      "    signature {"
      "      name: 'AddFunction'"
      "      input_arg {"
      "        name: 'a'"
      "        type: DT_FLOAT"
      "      }"