def METHOD_NAME(model, args):
    #convert paddle inference model to onnx
    onnx_save_file = os.path.join(args.save_dir, 'paddle2onnx_model.onnx')
    if model.__class__.__name__ == "YOLOv3":
        pdx.converter.export_onnx_model(model, onnx_save_file)
    else:
        pdx.converter.export_onnx_model(model, onnx_save_file, 11)
    #convert onnx to openvino ir
    try:
        import mo.main as mo
        from mo.utils.cli_parser import get_onnx_cli_parser
    except Exception as e:
        print("convert failed! ", e)
        print(
            "if error is 'no module name mo',please init openvino environment first"
        )
        print(
            "see https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/deploy/openvino/faq.md"
        )
    else:
        onnx_parser = get_onnx_cli_parser()
        onnx_parser.add_argument("--model_dir", type=_text_type)
        onnx_parser.add_argument("--save_dir", type=_text_type)
        onnx_parser.add_argument("--fixed_input_shape")
        onnx_parser.set_defaults(input_model=onnx_save_file)
        onnx_parser.set_defaults(output_dir=args.save_dir)
        shape_list = args.fixed_input_shape[1:-1].split(',')
        with open(osp.join(args.model_dir, "model.yml")) as f:
            info = yaml.load(f.read(), Loader=yaml.Loader)
        input_channel = 3
        if 'input_channel' in info['_init_params']:
            input_channel = info['_init_params']['input_channel']
        shape = '[1,{},' + shape_list[1] + ',' + shape_list[0] + ']'
        shape = shape.format(input_channel)
        if model.__class__.__name__ == "YOLOv3":
            shape = shape + ",[1,2]"
            inputs = "image,im_size"
            onnx_parser.set_defaults(input=inputs)
        onnx_parser.set_defaults(input_shape=shape)
        mo.main(onnx_parser, 'onnx')