code: def _predictor(self, args, exe, place):
      predictor_scope = fluid.Scope()
      with fluid.scope_guard(predictor_scope):
          predictor_startup_prog = fluid.default_startup_program()
          predictor_main_prog = fluid.default_main_program()
          with fluid.program_guard(
              predictor_main_prog, predictor_startup_prog
          ):
              # parse config
              predictor_config = parse_config(args.predictor_config)
              predictor_infer_config = merge_configs(
                  predictor_config, "infer", vars(args)
              )
  
              predictor_model = models.get_model(
                  "AttentionLSTM", predictor_infer_config, mode="infer"
              )
              predictor_model.build_input(use_dataloader=False)
              predictor_model.build_model()
              predictor_feeds = predictor_model.feeds()
              predictor_outputs = predictor_model.outputs()
  
              exe.run(predictor_startup_prog)
  
              logger.info(
                  "load lstm weights from {}".format(
                      args.predictor_weights
                  )
              )
              predictor_model.load_test_weights(
                  exe, args.predictor_weights, predictor_main_prog
              )
  
              predictor_feeder = fluid.DataFeeder(
                  place=place, feed_list=predictor_feeds
              )
              predictor_fetch_list = predictor_model.fetches()
      return (
          predictor_main_prog,
          predictor_fetch_list,
          predictor_feeder,
          predictor_scope,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import argparse
  import ast
  import os
  import paddle.fluid
  import paddlehub
  from paddlehub.module.module import moduleinfo, runnable
  from paddlehub.common.logger import logger
  from videotag_tsn_lstm.resource.utils.config_utils import *
  import videotag_tsn_lstm.resource.models
  from videotag_tsn_lstm.resource.reader import get_reader
  from videotag_tsn_lstm.resource.metrics import get_metrics
  from videotag_tsn_lstm.resource.utils.utility import check_cuda
  from videotag_tsn_lstm.resource.utils.utility import check_version
label_desc: Use image node_id 3 for calling the VideoTag obj's underlying member method code with example usage: obj._predictor(args, exe, place) and returns: predictor_main_prog,  predictor_fetch_list,  predictor_feeder,  predictor_scope