code: def run(FLAGS, cfg):
      # build detector
      trainer = Trainer(cfg, mode="eval")
  
      # load weights
      if cfg.architecture in ["DeepSORT"]:
          if cfg.det_weights != "None":
              trainer.load_weights_sde(
                  cfg.det_weights, cfg.reid_weights
              )
          else:
              trainer.load_weights_sde(None, cfg.reid_weights)
      else:
          trainer.load_weights(cfg.weights)
  
      # post quant model
      trainer.post_quant(FLAGS.output_dir)
  
file_path: PaddleDetection/tools/post_quant.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import sys
  import warnings
  import paddle
  from ppdet.core.workspace import load_config, merge_config
  from ppdet.utils.check import check_gpu, check_version, check_config
  from ppdet.utils.cli import ArgsParser
  from ppdet.engine import Trainer
  from ppdet.slim import build_slim_model
  from ppdet.utils.logger import setup_logger
label_desc: Use image node_id 2 for calling a global function with example usage: run(FLAGS, cfg) without return types