quantization_py_function_library) {
        return tensorflow::PyoOrThrow(tflite::Convert(
            model_flags_proto_txt_raw.ptr(), toco_flags_proto_txt_raw.ptr(),
            input_contents_txt_raw.ptr(), extended_return,
            debug_info_txt_raw.ptr(), enable_mlir_converter,
            quantization_py_function_library));
      },

def Convert(model_flags_proto_txt_raw: object, toco_flags_proto_txt_raw: object, input_contents_txt_raw: object, extended_return: bool = ..., debug_info_txt_raw: object = ..., enable_mlir_converter: bool = ..., quantization_py_function_library = ...) -> object: ...

                  PyObject* debug_info_txt_raw = nullptr,
                  bool enable_mlir_converter = false,
                  const tensorflow::quantization::PyFunctionLibrary*
                      quantization_py_function_library = nullptr);

// Quantize the model with calibration data. Throw errors if `fully_quantize`
// is specified by the calibration data are not sufficient to quantize the
// model.

                  PyObject* debug_info_txt_raw, bool enable_mlir_converter,
                  const tensorflow::quantization::PyFunctionLibrary*
                      quantization_py_function_library) {
  // Use Python C API to validate and convert arguments. In py3 (bytes),
  // in py2 (str).
  auto ConvertArg = [&](PyObject* obj, bool* error) {
    char* buf;
    Py_ssize_t len;