code: def convert_param_name(param):
      resnet_param = {}
      for k, v in six.iteritems(param):
          try:
              newname = name_conversion(k)
          except Exception:
              logger.error(
                  "Exception when processing caffe layer {}".format(k)
              )
              raise
          logger.info("Name Transform: " + k + " --> " + newname)
          resnet_param[newname] = v
      return resnet_param
  
file_path: tensorpack/examples/ResNet/load-resnet.py
imports: import argparse
  import functools
  import numpy
  import re
  import cv2
  import six
  import tensorflow
  from tensorpack import *
  from tensorpack.dataflow.dataset import ILSVRCMeta
  from tensorpack.utils import logger
  from imagenet_utils import ImageNetModel, eval_classification, get_imagenet_dataflow
  from resnet_model import resnet_bottleneck, resnet_group
label_desc: Use image node_id 4 for calling a global function with example usage: convert_param_name(param) and returns: resnet_param