docstr: parse paddle predictor config
  args:
      config(paddle.inference.Config): paddle inference config
  return:
      config_status(dict): dict style config info
docstr_tok: ["parse","paddle","predictor","config","args",":","config","(","paddle.inference.Config",")",":","paddle","inference","config","return",":","config_status","(","dict",")",":","dict","style","config","info"]
code: 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
  
file_path: PaddleDetection/deploy/pptracking/python/benchmark_utils.py
imports: import os
  import logging
  import paddle
  import paddle.inference
  from pathlib import Path
label_desc: Use image node_id 3 for calling the PaddleInferBenchmark obj's underlying member method code with example usage: obj.parse_config(config) and returns: config_status