},
      py::arg("input_contents_txt_raw"),
      R"pbdoc(
      Returns a sparsified model.
    )pbdoc");
  m.def(
      "RegisterCustomOpdefs",
      [](py::object custom_opdefs_txt_raw) {
        return tensorflow::PyoOrThrow(
            tflite::RegisterCustomOpdefs(custom_opdefs_txt_raw.ptr()));
      },
      py::arg("custom_opdefs_txt_raw"),
      R"pbdoc(

  return _pywrap_converter_api.ExperimentalMlirSparsifyModel(input_data_str)


def wrapped_register_custom_opdefs(custom_opdefs_list):
  """Wraps RegisterCustomOpdefs with lazy loader."""
  return _pywrap_converter_api.RegisterCustomOpdefs(custom_opdefs_list)


def wrapped_retrieve_collected_errors():
  """Wraps RetrieveCollectedErrors with lazy loader."""
  return _pywrap_converter_api.RetrieveCollectedErrors()

def ExperimentalMlirSparsifyModel(input_contents_txt_raw: object) -> object: ...
def FlatBufferToMlir(arg0: str, arg1: bool) -> str: ...
def RegisterCustomOpdefs(custom_opdefs_txt_raw: object) -> object: ...

// sparsification fails.
PyObject* MlirSparsifyModel(PyObject* data);

// Registers the given custom opdefs to TensorFlow global op registry.
PyObject* RegisterCustomOpdefs(PyObject* list);

// Returns the collected TFLite conversion errors.
std::vector<std::string> RetrieveCollectedErrors();

// Returns MLIR string dump of the given Flatbuffer model.

    return nullptr;
  }
  return tflite::python_utils::ConvertToPyString(
      reinterpret_cast<const char*>(builder.GetCurrentBufferPointer()),
      builder.GetSize());
}

PyObject* RegisterCustomOpdefs(PyObject* list) {
  if (!PyList_Check(list)) {
    PyErr_SetString(PyExc_TypeError, "Expected list in argument");
    return nullptr;
  }

  int64_t size = PyList_Size(list);