code: def _save_recognizer_model(self, dirname):
      place = paddle.CPUPlace()
      exe = paddle.static.Executor(place)
  
      (
          program,
          feeded_var_names,
          target_vars,
      ) = paddle.static.load_inference_model(
          self.rec_pretrained_model_path, executor=exe
      )
      global_block = program.global_block()
      feed_vars = [global_block.var(item) for item in feeded_var_names]
      paddle.static.save_inference_model(
          dirname,
          feed_vars=feed_vars,
          fetch_vars=target_vars,
          executor=exe,
          program=program,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import argparse
  import ast
  import copy
  import math
  import os
  import time
  import cv2
  import numpy
  import paddle
  from chinese_ocr_db_crnn_server.character import CharacterOps
  from chinese_ocr_db_crnn_server.utils import base64_to_cv2
  from chinese_ocr_db_crnn_server.utils import draw_ocr
  from chinese_ocr_db_crnn_server.utils import get_image_ext
  from chinese_ocr_db_crnn_server.utils import sorted_boxes
  from paddle.inference import Config
  from paddle.inference import create_predictor
  from PIL import Image
  import paddlehub
  from paddlehub.module.module import moduleinfo
  from paddlehub.module.module import runnable
  from paddlehub.module.module import serving
  from paddlehub.utils.log import logger
label_desc: Use image node_id 15 for calling the ChineseOCRDBCRNNServer obj's underlying member method code with example usage: obj._save_recognizer_model(dirname) without return types