code: def convert_to_adversarial_training_dataset(dataset):
      def to_dict(x, y):
          return {FEATURE_INPUT_NAME: x, LABEL_INPUT_NAME: y}
  
      return dataset.map(to_dict)
  
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 3 for calling a global function with example usage: convert_to_adversarial_training_dataset(dataset) and returns: dataset, dict