std::unique_ptr<OperationPass<func::FuncOp>> CreateDefaultQuantParamsPass(
    double default_min, double default_max, bool is_signed) {
  return std::make_unique<DefaultQuantParamsPass>(default_min, default_max,
                                                  is_signed);
}

std::unique_ptr<OperationPass<func::FuncOp>> CreateDefaultQuantParamsPass() {
  return std::make_unique<DefaultQuantParamsPass>();
}

// Creates an instance of the TensorFlow Lite dialect pass to add default
// quantization parameters.
std::unique_ptr<OperationPass<func::FuncOp>> CreateDefaultQuantParamsPass(
    double default_min, double default_max, bool is_signed);

std::unique_ptr<OperationPass<func::FuncOp>> CreateDefaultQuantParamsPass();

// Creates an instance of the IdentifyDilatedConvPass.
std::unique_ptr<OperationPass<func::FuncOp>> CreateIdentifyDilatedConvPass();

  if (quant_specs.default_ranges.first.has_value() ||
      quant_specs.default_ranges.second.has_value()) {
    pass_manager.addNestedPass<mlir::func::FuncOp>(
        mlir::TFL::CreateDefaultQuantParamsPass(
            quant_specs.default_ranges.first.value_or(0.0),
            quant_specs.default_ranges.second.value_or(0.0),
            quant_specs.IsSignedInferenceType()));
  }

}

def DefaultQuantParamsPass : Pass<"tfl-default-quant", "mlir::func::FuncOp"> {
  let summary = "Apply quantization with default quantization parameter";
  let constructor = "CreateDefaultQuantParamsPass()";
  let dependentDialects = ["TFL::TensorFlowLiteDialect"];
  let options = [
    Option<"default_min_", "default-min", "double", "-1.0",
               "Default minimum value for TFLite quantization">,