def parse_config(self, config) -> dict:
        """
        parse paddle predictor config
        args:
            config(paddle.inference.Config): paddle inference config
        return:
            config_status(dict): dict style config info
        """
        if isinstance(config, paddle_infer.Config):
            config_status = {}
            config_status['runtime_device'] = "gpu" if config.use_gpu(
            ) else "cpu"
            config_status['ir_optim'] = config.ir_optim()
            config_status['enable_tensorrt'] = config.tensorrt_engine_enabled()
            config_status['precision'] = self.precision
            config_status['enable_mkldnn'] = config.mkldnn_enabled()
            config_status[
                'cpu_math_library_num_threads'] = config.cpu_math_library_num_threads(
                )
        elif isinstance(config, dict):
            config_status['runtime_device'] = config.get('runtime_device', "")
            config_status['ir_optim'] = config.get('ir_optim', "")
            config_status['enable_tensorrt'] = config.get('enable_tensorrt', "")
            config_status['precision'] = config.get('precision', "")
            config_status['enable_mkldnn'] = config.get('enable_mkldnn', "")
            config_status['cpu_math_library_num_threads'] = config.get(
                'cpu_math_library_num_threads', "")
        else:
            self.print_help()
            raise ValueError(
                "Set argument config wrong, please check input argument and its type"
            )
        return config_status

        parse paddle predictor config
        args:
            config(paddle.inference.Config): paddle inference config
        return:
            config_status(dict): dict style config info
        
deploy/python/benchmark_utils.py