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

      debug_options_str,
  )


def wrapped_experimental_mlir_sparsify(input_data_str):
  """Wraps experimental mlir sparsify model."""
  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)

      py::arg("disable_per_channel_for_dense_layers") = false,
      py::arg("debug_options_proto_txt_raw") = nullptr,
      R"pbdoc(
      Returns a quantized model.
    )pbdoc");
  m.def(
      "ExperimentalMlirSparsifyModel",
      [](py::object input_contents_txt_raw) {
        return tensorflow::PyoOrThrow(
            tflite::MlirSparsifyModel(input_contents_txt_raw.ptr()));
      },
      py::arg("input_contents_txt_raw"),