code: def test_gen_adv_neighbor_for_features_with_different_shapes_v2(self):
      (
          x,
          w1,
          w2,
          adv_config,
      ) = (
          self._test_gen_adv_neighbor_for_features_with_different_shapes_setup()
      )
      with tf.GradientTape() as tape:
          tape.watch(list(x.values()))
          loss = tf.reduce_sum(
              input_tensor=w1 * x["f1"]
          ) + tf.reduce_sum(input_tensor=w2 * x["f2"])
  
      adv_neighbor, _ = adv_lib.gen_adv_neighbor(
          x, loss, adv_config, gradient_tape=tape
      )
      actual_neighbor = self.evaluate(adv_neighbor)
  
      # gradient = w
      # perturbation = adv_step_size * normalize(gradient) = 0.05 in each dim
      perturbation = 0.025
      self.assertAllClose(x["f1"] + perturbation, actual_neighbor["f1"])
      self.assertAllClose(x["f2"] + perturbation, actual_neighbor["f2"])
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import neural_structured_learning.configs
  from neural_structured_learning.lib import adversarial_neighbor
  import numpy
  import tensorflow
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 45 for calling the GenAdvNeighborTest obj's underlying member method code with example usage: obj.test_gen_adv_neighbor_for_features_with_different_shapes_v2() without return types