code: def get_hparams():
      """Returns the hyperparameters with defaults overwritten by flags."""
      hparams = HParams()
      if FLAGS.epochs:
          hparams.epochs = FLAGS.epochs
      if FLAGS.adv_step_size:
          hparams.adv_step_size = FLAGS.adv_step_size
      if FLAGS.steps_per_epoch:
          hparams.steps_per_epoch = FLAGS.steps_per_epoch
      if FLAGS.eval_steps:
          hparams.eval_steps = FLAGS.eval_steps
      return 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 1 for calling a global function with example usage: get_hparams() and returns: hparams