code: def load_model(self, modelpath, use_gpu, use_mkldnn, combined):
      # 对运行位置进行配置
      if use_gpu:
          try:
              int(os.environ.get("CUDA_VISIBLE_DEVICES"))
          except Exception:
              print(
                  'Error! Unable to use GPU. Please set the environment variables "CUDA_VISIBLE_DEVICES=GPU_id" to use GPU.'
              )
              use_gpu = False
  
      # 加载模型参数
      if combined:
          model = os.path.join(modelpath, "__model__")
          params = os.path.join(modelpath, "__params__")
          config = Config(model, params)
      else:
          config = Config(modelpath)
  
      # 设置参数
      if use_gpu:
          config.enable_use_gpu(100, 0)
      else:
          config.disable_gpu()
          if use_mkldnn:
              config.enable_mkldnn()
      config.disable_glog_info()
      config.switch_ir_optim(True)
      config.enable_memory_optim()
      config.switch_use_feed_fetch_ops(False)
      config.switch_specify_input_names(True)
  
      # 通过参数加载模型预测器
      predictor = create_predictor(config)
  
      # 返回预测器
      return predictor
  
imports: import os
  import numpy
  from paddle.inference import create_predictor, Config
label_desc: Use image node_id 2 for calling the Model obj's underlying member method code with example usage: obj.load_model(modelpath, use_gpu, use_mkldnn, combined) and returns: predictor