code: def load_entire_model(model, pretrained):
      if pretrained is not None:
          load_pretrained_model(model, pretrained)
      else:
          logger.warning(
              "Weights are not loaded for {} model since the "
              "path of weights is None".format(model.__class__.__name__)
          )
  
imports: import os
  import contextlib
  import tempfile
  import random
  from urllib.parse import urlparse, unquote
  import yaml
  import numpy
  import paddle
  import cv2
  from paddleseg.utils import logger, seg_env, get_sys_env
  from paddleseg.utils.download import download_file_and_uncompress
label_desc: Use image node_id 8 for calling a global function with example usage: load_entire_model(model, pretrained) without return types