tensorflow::string* g_test_model_dir = nullptr;
}  // namespace

namespace tflite {
namespace optimize {
namespace {

using mlir::lite::BufferType;
using mlir::lite::CustomOpMap;
using mlir::lite::QuantizeWeights;
constexpr bool kUseUpdatedHybridSchemeDefault = true;

std::unique_ptr<ModelT> CreateMutableModelFromFile(const Model* input_model) {
  auto copied_model = std::make_unique<ModelT>();
  input_model->UnPackTo(copied_model.get(), nullptr);

    }

    private fun getExpectedTypeByTypeCast(expression: PsiElement): KaType? {
        val typeCastExpression =
            expression.unwrapQualified<KtBinaryExpressionWithTypeRHS> { castExpr, expr -> castExpr.left == expr } ?: return null
        return getKtExpressionType(typeCastExpression)
    }

    private fun getExpectedTypeOfFunctionParameter(expression: PsiElement): KaType? {

// reference of a func. If so, it returns referenced Func; otherwise nil.
//
// This is only usable before walk.walkConvertInterface, which converts to an
// OMAKEFACE.
func IsIfaceOfFunc(n Node) *Func {
	if n, ok := n.(*ConvExpr); ok && n.Op() == OCONVIFACE {
		if name, ok := n.X.(*Name); ok && name.Op() == ONAME && name.Class == PFUNC {
			return name.Func
		}
	}
	return nil
}