code: def resnet_random():
      aparams = resnet_fgsm()
      aparams.attack = "random"
      aparams.epsilon_name = "eps"
      aparams.add_hparam("num_samples", 10)
      aparams.add_hparam("num_batches", 100)
      return aparams
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from tensor2tensor.layers import common_hparams
  from tensor2tensor.layers import common_layers
  from tensor2tensor.utils import hparam
  from tensor2tensor.utils import registry
  from tensor2tensor.utils import t2t_model
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 30 for calling a global function with example usage: resnet_random() and returns: aparams