code: def build_adv_model(hparams):
      """Builds an adversarial-regularized model from parameters in `hparams`."""
      base_model = build_base_model(hparams)
      return apply_adversarial_regularization(base_model, hparams)
  
file_path: neural-structured-learning/neural_structured_learning/examples/adv_keras_cnn_mnist.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl import app
  from absl import flags
  import attr
  import neural_structured_learning
  import tensorflow
label_desc: Use image node_id 6 for calling a global function with example usage: build_adv_model(hparams) and returns: apply_adversarial_regularization