def check_and_save_model()

in optimum/onnx/graph_transformations.py [0:0]

• 35 lines of code
• 12 McCabe index (conditional complexity)

def check_and_save_model(model: onnx.ModelProto, save_path: Optional[Union[str, Path]]):
    # We can check ModelProtos that are smaller than 2GB before saving them.
    # For larger models, we need to save them first and then check their save path.
    # https://github.com/onnx/onnx/blob/main/docs/PythonAPIOverview.md#checking-a-large-onnx-model-2gb

    if model.ByteSize() < onnx.checker.MAXIMUM_PROTOBUF:
        # For the try catch, refer to https://github.com/microsoft/onnxruntime/issues/14768
        try:
            onnx.checker.check_model(model)
        except Exception as e:
            if "No Op registered for" in str(e):
                pass
            else:
                raise e

    save_path = Path(save_path).as_posix()
    external_file_name = os.path.basename(save_path) + "_data"
    external_file_path = os.path.join(os.path.dirname(save_path), external_file_name)

    if save_path.endswith(".onnx") and os.path.isfile(save_path):
        os.remove(save_path)

    model_uses_external_data = False
    if os.path.isfile(external_file_path):
        model_uses_external_data = True
        os.remove(external_file_path)

    FORCE_ONNX_EXTERNAL_DATA = os.getenv("FORCE_ONNX_EXTERNAL_DATA", "0") == "1"

    onnx.save(
        model,
        save_path,
        save_as_external_data=model_uses_external_data or FORCE_ONNX_EXTERNAL_DATA,
        all_tensors_to_one_file=True,
        location=external_file_name,
        convert_attribute=True,
        size_threshold=1024 if not FORCE_ONNX_EXTERNAL_DATA else 100,
    )

    try:
        onnx.checker.check_model(save_path)
    except Exception as e:
        if "No Op registered for" in str(e):
            pass
        else:
            raise e