docstr: predictor config path
docstr_tok: ["predictor","config","path"]
code: def _set_config(self, pretrained_model_path):
      """
      predictor config path
      """
      model_file_path = pretrained_model_path + ".pdmodel"
      params_file_path = pretrained_model_path + ".pdiparams"
  
      config = Config(model_file_path, params_file_path)
      try:
          _places = os.environ["CUDA_VISIBLE_DEVICES"]
          int(_places[0])
          use_gpu = True
      except:
          use_gpu = False
  
      if use_gpu:
          config.enable_use_gpu(8000, 0)
      else:
          config.disable_gpu()
          if self.enable_mkldnn:
              # cache 10 different shapes for mkldnn to avoid memory leak
              config.set_mkldnn_cache_capacity(10)
              config.enable_mkldnn()
  
      config.disable_glog_info()
      config.delete_pass("conv_transpose_eltwiseadd_bn_fuse_pass")
      config.switch_use_feed_fetch_ops(False)
  
      predictor = create_predictor(config)
  
      input_names = predictor.get_input_names()
      input_tensor = predictor.get_input_handle(input_names[0])
      output_names = predictor.get_output_names()
      output_tensors = []
      for output_name in output_names:
          output_tensor = predictor.get_output_handle(output_name)
          output_tensors.append(output_tensor)
  
      return predictor, input_tensor, output_tensors
  
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 2 for calling the ChineseOCRDBCRNNServer obj's underlying member method code with example usage: obj._set_config(pretrained_model_path) and returns: predictor,  input_tensor,  output_tensors