// * Zero or more row_split tensors.
  constexpr int kValues = 0;
  constexpr int kRowSplits = 1;

  if (func.getFunctionType().getInputs().size() !=
      func.getFunctionType().getResults().size()) {
    return func.emitError() << "Mismatched number of inputs and outputs.";
  }

  int row_splits = func.getFunctionType().getInputs().size() - kRowSplits;
  if (row_splits == 0) {
    auto input_values = GetInputType(func, kValues);

                                   .getValue())
          .getValues<FloatAttr>()[0]
          .getValue()
          .isExactlyValue(0.0f));

  EXPECT_EQ(fused_lstm_func_.getFunctionType().getNumResults(), 1);
  auto output_types = fused_lstm_func_.getFunctionType().getResults();
  SmallVector<int64_t, 2> output_shape{1, mlir::ShapedType::kDynamic};
  EXPECT_EQ(mlir::cast<RankedTensorType>(output_types[0]).getShape().size(),

    // will be the operations inside the function body rather than representing
    // them in the function signature.
    FunctionType func_type = rewriter.getFunctionType({}, {});
    func::FuncOp func = rewriter.create<func::FuncOp>(
        loc, kImportModelDefaultGraphFuncName, func_type);
    rewriter.setInsertionPointToStart(func.addEntryBlock());
    auto executor_graph =

  auto loc = op->getLoc();
  if (use_region_args) {
    auto inputs = func.getFunctionType().getInputs();
    entry->addArguments(inputs, SmallVector<Location>(inputs.size(), loc));
    args = entry->getArguments();
  }
  llvm::SmallVector<Value, 4> casted_args;
  casted_args.reserve(func.getNumArguments());
  for (const auto& ArgAndType : zip(args, func.getFunctionType().getInputs())) {
    Value arg = std::get<0>(ArgAndType);

mlir::LogicalResult PromoteVarHandlesToArguments(
    func::FuncOp function, bool add_validation,
    llvm::SmallVectorImpl<std::string>* var_handle_shared_names) {
  Block& block = function.front();
  auto func_type = function.getFunctionType();

  auto func_arg_types = llvm::to_vector<4>(func_type.getInputs());
  llvm::SmallDenseMap<llvm::StringRef, int> var_arg_index_by_name;
  for (auto var_handle_op :

    llvm::function_ref<std::optional<Type>(int64_t)> arg_to_stack_type,
    llvm::function_ref<void(ArrayRef<BlockArgument>)> handle_new_size_vars =
        nullptr) {
  auto new_input_types = llvm::to_vector<8>(func.getFunctionType().getInputs());
  auto size_var_type = GetSizeVarType(OpBuilder(func));
  int64_t original_arg_count = new_input_types.size();
  for (int64_t i = 0; i < original_arg_count; ++i) {
    auto stack_type = arg_to_stack_type(i);

                                             custom_option_buffer))) {
    return failure();
  }

  auto tfl_fusable_op = builder.create<TFL::CustomOp>(
      func->getLoc(), func.getFunctionType().getResults(), func.getArguments(),
      custom_op_name, CustomOption(&builder, custom_option_buffer));
  builder.create<func::ReturnOp>(func->getLoc(), tfl_fusable_op.getResults());
  return success();
}

    llvm::function_ref<std::optional<Type>(int64_t)> arg_to_buffer_type,
    llvm::function_ref<bool(int64_t)> arg_buffer_size_is_fixed) {
  auto new_input_types = llvm::to_vector<8>(func.getFunctionType().getInputs());
  int64_t original_arg_count = new_input_types.size();
  Location loc = func.getLoc();
  for (int64_t i = 0; i < original_arg_count; ++i) {
    auto buffer_type = arg_to_buffer_type(i);

    SmallVectorImpl<Value>* inputs, NamedAttrList* arg_attrs,
    llvm::StringMap<Attribute>* derived_attrs) const {
  for (const auto& operand :
       llvm::enumerate(signature.getFunctionType().getInputs())) {
    // If the index is larger than the operand number of the call_op, the
    // default value of the operand needs to be used.
    if (operand.index() >= call_op.getNumOperands()) {

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

  OpBuilder::InsertionGuard guard = OpBuilder::InsertionGuard(rewriter);
  ArrayRef<Type> inputs = quantization_func.getFunctionType().getInputs();
  Block* block = rewriter.createBlock(
      &quantization_func.getBody(), quantization_func.begin(), inputs,
      SmallVector<Location>(inputs.size(), quantization_func.getLoc()));