code: def test_adversarial_wrapper_not_affecting_predictions(self):
      # base model: y = x + 2
      base_est = self.build_linear_regressor(weight=[[1.0]], bias=[2.0])
      adv_est = nsl_estimator.add_adversarial_regularization(base_est)
      input_fn = single_batch_input_fn(
          {FEATURE_NAME: np.array([[1.0], [2.0]])}
      )
      predictions = adv_est.predict(input_fn=input_fn)
      predicted_scores = [x["predictions"] for x in predictions]
      self.assertAllClose([[3.0], [4.0]], predicted_scores)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import shutil
  import tempfile
  from absl.testing import parameterized
  import neural_structured_learning.configs
  import neural_structured_learning.estimator
  import numpy
  import tensorflow
  from tensorflow import estimator
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 4 for calling the AdversarialRegularizationTest obj's underlying member method code with example usage: obj.test_adversarial_wrapper_not_affecting_predictions() without return types