void EliminateUnusedResultsForIfCase(Operation *op,
                                     ArrayRef<func::FuncOp> branches) {
  // Clone branch functions if needed since we will be mutating them.
  SmallVector<func::FuncOp, 2> cloned_branches;
  cloned_branches.reserve(branches.size());
  for (func::FuncOp func : branches) {
    func::FuncOp cloned = CloneFunctionIfNeeded(func);
    cloned_branches.push_back(cloned);

def QuantizeWeightPass : Pass<"stablehlo-quantize-weight", "mlir::func::FuncOp"> {
  let summary = "Quantizes the weight component of StableHLO graph.";
  let dependentDialects = ["mlir::stablehlo::StablehloDialect"];
  let constructor = "mlir::quant::stablehlo::CreateQuantizeWeightPass()";
}

def UnfuseMhloBatchNormPass : Pass<"stablehlo-unfuse-mhlo-batch-norm", "mlir::func::FuncOp"> {
  let summary = "Unfuses batch normalization into arithmetic ops.";

  }

  return init_func_ops;
}

func::FuncOp GetInitializerFunction(ModuleOp module_op,
                                    const StringRef initializer_type) {
  SmallVector<func::FuncOp, 2> init_func_ops =
      GetInitializerFunctions(module_op);

  auto init_func_itr = absl::c_find_if(
      init_func_ops, [initializer_type](const func::FuncOp init_func_op) {

                             StringRef(content.data(), content.size()));
}

inline TensorType GetInputType(func::FuncOp func, int idx) {
  return mlir::dyn_cast_or_null<TensorType>(
      func.getFunctionType().getInput(idx));
}

inline TensorType GetResultType(func::FuncOp func, int idx) {
  return mlir::dyn_cast_or_null<TensorType>(
      func.getFunctionType().getResult(idx));
}

  void ConvertTFImplements(func::FuncOp func, StringAttr attr);
  void ConvertTFImplementsWithAttributes(func::FuncOp func, FuncAttr attr);
  void ConvertTFAPIImplements(func::FuncOp func, StringAttr attr,
                              ModuleOp module);
  void runOnOperation() override;
};

LogicalResult CheckFusableLayerNormalizedLstmCellSimple(
    func::FuncOp lstm_func) {
  for (int i = 0; i < 5; ++i) {

  // Converts a given FuncOp to a FunctionDef and adds it to the function
  // definition library
  static Status ConvertLibFunction(
      const GraphExportConfig& configs, const Dialect* tf_dialect,
      const SymbolTable& symbol_table, FuncOp function,
      FunctionLibraryDefinition* flib_def,
      llvm::SmallDenseSet<FuncOp>& visited_functions);

  // Converts a given FuncOp to a FunctionDef and adds it to the function
  // definition library
  static Status ConvertLibFunction(
      const GraphExportConfig& configs, const Dialect* tf_dialect,
      const SymbolTable& symbol_table, FuncOp function,
      FunctionLibraryDefinition* flib_def,
      llvm::SmallDenseSet<FuncOp>& visited_functions);

  FunctionType func_type =
      FunctionType::get(rewriter.getContext(), {create_unknown_input_shape},
                        {create_unknown_output_shape});

  func::FuncOp quantization_func =
      rewriter.create<func::FuncOp>(input_op->getLoc(), func_name, func_type);

  OpBuilder::InsertionGuard guard = OpBuilder::InsertionGuard(rewriter);
  ArrayRef<Type> inputs = quantization_func.getFunctionType().getInputs();

TEST_F(LiftAsFunctionCallTest, LiftedFunctionSucceeds) {
  OwningOpRef<ModuleOp> module_op = ParseModuleOpString(kModuleLifted);
  ASSERT_TRUE(module_op);

  auto composite_dot_general_fn =
      module_op->lookupSymbol<func::FuncOp>("composite_dot_general_fn_1");
  ASSERT_THAT(composite_dot_general_fn, NotNull());

  auto dot_general_op = FindOperationOfType<mlir::stablehlo::DotGeneralOp>(
      composite_dot_general_fn);

  }

  void runOnOperation() override;
};

// Checks if a FuncOp is exported.
bool IsExported(func::FuncOp op) {
  auto exported_names =
      op->getAttrOfType<ArrayAttr>(kTfSavedModelExportedNamesAttr);
  return exported_names && !exported_names.empty();
}

// Check if a function is an entry function.
bool IsEntryFunction(func::FuncOp op) {
  return op->hasAttr(kEntryFunctionAttr);
}