code: def convnormrelu(x, name, chan):
      x = Conv2D(name, x, chan, 3)
      if args.norm == "bn":
          x = BatchNorm(name + "_bn", x)
      elif args.norm == "gn":
          with tf.variable_scope(name + "_gn"):
              x = GroupNorm(x, 32)
      x = tf.nn.relu(x, name=name + "_relu")
      return x
  
file_path: tensorpack/examples/ImageNetModels/vgg16.py
imports: import argparse
  import os
  from tensorpack import tfv1
  from tensorpack import *
  from tensorpack.tfutils import argscope
  from tensorpack.tfutils.summary import *
  from tensorpack.utils.gpu import get_num_gpu
  from imagenet_utils import ImageNetModel, fbresnet_augmentor, get_imagenet_dataflow
label_desc: Use image node_id 2 for calling a global function with example usage: convnormrelu(x, name, chan) and returns: x