code: def __init__(self):
      self.default_pretrained_model_path = os.path.join(
          self.directory, "efficientnetb3_imagenet_infer_model", "model"
      )
      label_file = os.path.join(self.directory, "label_list.txt")
      with open(label_file, "r", encoding="utf-8") as file:
          self.label_list = file.read().split("\n")[:-1]
      self._set_config()
  
imports: from __future__ import absolute_import
  from __future__ import division
  import argparse
  import ast
  import os
  import numpy
  from paddle.inference import Config
  from paddle.inference import create_predictor
  from .data_feed import reader
  from .processor import base64_to_cv2
  from .processor import postprocess
  from paddlehub.module.module import moduleinfo
  from paddlehub.module.module import runnable
  from paddlehub.module.module import serving
label_desc: Use image node_id 1 to create a new EfficientNetB3ImageNet object  with example: obj = EfficientNetB3ImageNet()