code: def resnet_group(name, l, block_func, features, count, stride):
      with tfv1.variable_scope(name):
          for i in range(0, count):
              with tfv1.variable_scope("block{}".format(i)):
                  l = block_func(l, features, stride if i == 0 else 1)
      return l
  
imports: import numpy
  import tensorflow
  from contextlib import ExitStack, contextmanager
  from tensorpack import tfv1
  from tensorpack.models import BatchNorm, Conv2D, MaxPooling, layer_register
  from tensorpack.tfutils import argscope
  from tensorpack.tfutils.scope_utils import auto_reuse_variable_scope
  from tensorpack.tfutils.varreplace import custom_getter_scope, freeze_variables
  from config import config
label_desc: Use image node_id 9 for calling a global function with example usage: resnet_group(name, l, block_func, features, count, stride) and returns: l