// their region based counterparts.
std::unique_ptr<OperationPass<ModuleOp>>
CreateTFFunctionalControlFlowToRegions();
std::unique_ptr<OperationPass<ModuleOp>> CreateTFFunctionalControlFlowToRegions(
    bool allow_passthrough_args);

// Transforms region bases control flow operations in the TensorFlow dialect to
// their functional counterparts.
std::unique_ptr<OperationPass<ModuleOp>>
CreateTFRegionControlFlowToFunctional();

      return %0 : tensor<1x3xf32>
    }
  }
)mlir";

TEST_F(AttrsAndConstraintsTest, HasStaticShapeSucceedsWithStaticShapes) {
  OwningOpRef<ModuleOp> module_op = ParseModuleOpString(kModuleStatic);
  ASSERT_TRUE(module_op);

  func::FuncOp main_fn = FindMainFuncOp(*module_op);
  ASSERT_THAT(main_fn, NotNull());

  Value dot_general_result =

absl::StatusOr<ExportedModel> ExportDebuggingModel(
    mlir::ModuleOp module_op, mlir::MLIRContext *context,
    const QuantizationOptions &quantization_options,
    const absl::flat_hash_map<std::string, std::string> &function_aliases) {
  // Clone ModuleOp and function aliases so changes in this pipeline won't
  // be reflected in the original values.
  mlir::OwningOpRef<mlir::ModuleOp> cloned_module_ref(module_op.clone());

void MoveFunctions(SymbolTableCollection &symbol_tables, ModuleOp from,
                   ModuleOp to) {
  SymbolTable &to_symbol_table = symbol_tables.getSymbolTable(to);
  for (auto func : llvm::make_early_inc_range(from.getOps<func::FuncOp>())) {
    func->remove();
    func.setPrivate();
    to_symbol_table.insert(func);
  }
}

void CopyStablehloModuleAttrs(ModuleOp stablehlo_module, XlaCallModuleOp op) {

  func.return %arg0 : tensor<i32>
}
)mlir";
  mlir::MLIRContext context;
  context.loadDialect<mlir::func::FuncDialect, mlir::TF::TensorFlowDialect>();
  mlir::OwningOpRef<mlir::ModuleOp> module =
      mlir::parseSourceString<mlir::ModuleOp>(code, &context);
  ASSERT_TRUE(module);
  auto entry_funcs = GetEntryFunctions(*module);
  EXPECT_EQ(entry_funcs.size(), 2);
  EXPECT_EQ(entry_funcs[0].getSymName(), "entry_func_1");

// pass.
std::unique_ptr<OperationPass<ModuleOp>> CreateTrimFunctionsPass();

std::unique_ptr<OperationPass<ModuleOp>> CreateTrimFunctionsPass(
    const std::vector<std::string>& trim_funcs_allowlist);

// Creates an instance of the TensorFlow Lite dialect PrepareCompositeFunctions
// pass.
std::unique_ptr<OperationPass<ModuleOp>> CreatePrepareCompositeFunctionsPass();

std::unique_ptr<OperationPass<ModuleOp>> CreateQuantizeWeightsPass(
    const tensorflow::quantization::QuantizationOptions& quant_options);

// Propagate quantized type through allowed ops.
std::unique_ptr<OperationPass<ModuleOp>> CreatePropagateQuantizeTypePass();

// Create a pass that inserts dump tensor to quantizable layer's output.
std::unique_ptr<OperationPass<ModuleOp>> CreateAddDumpTensorOpPass(

  }];
}

def RestoreFunctionNamePass : Pass<"stablehlo-restore-function-name", "ModuleOp"> {
  let summary = "Restores function name from XlaCallModule op.";
}

def QuantizeCompositeFunctionsPass : Pass<"stablehlo-quantize-composite-functions", "ModuleOp"> {
  let summary = "Quantize composite functions with QDQ input / outputs.";
  let options = [

      return %0 : tensor<1x3xf32>
    }
  }
)mlir";

TEST_F(IsOpQuantizableStableHloTest, ConstantOpQuantizable) {
  OwningOpRef<ModuleOp> module_op = ParseModuleOpString(kModuleConstantAdd);
  ASSERT_TRUE(module_op);

  auto test_func = module_op->lookupSymbol<func::FuncOp>("constant_add");
  ASSERT_THAT(test_func, NotNull());

  auto constant_op =

namespace tensorflow {
namespace {

absl::StatusOr<mlir::OwningOpRef<mlir::ModuleOp>> GetMlirModuleFromString(
    llvm::StringRef string, mlir::MLIRContext* context) {
  mlir::DialectRegistry mlir_registry;
  RegisterAllTensorFlowDialects(mlir_registry);
  context->appendDialectRegistry(mlir_registry);
  mlir::OwningOpRef<mlir::ModuleOp> mlir_module;
  auto status =