code: def _test_gen_adv_neighbor_for_features_with_different_shapes_setup(
      self,
  ):
      w1 = tf.constant(1.0, shape=(2, 2, 3))
      w2 = tf.constant(1.0, shape=(2, 2))
      f1 = tf.constant(
          [
              [
                  [[0.0, 0.1, 0.2], [0.3, 0.4, 0.5]],
                  [[0.6, 0.7, 0.8], [0.9, 1.0, 1.1]],
              ],
              [
                  [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]],
                  [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]],
              ],
          ]
      )
      f2 = tf.constant(
          [[[1.2, 1.3], [1.4, 1.5]], [[0.0, 0.0], [0.0, 0.0]]]
      )
      x = {"f1": f1, "f2": f2}
      adv_config = configs.AdvNeighborConfig(
          feature_mask=None, adv_step_size=0.1, adv_grad_norm="l2"
      )
      return x, w1, w2, adv_config
  
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 43 for calling the GenAdvNeighborTest obj's underlying member method code with example usage: obj._test_gen_adv_neighbor_for_features_with_different_shapes_setup() and returns: x,  w1,  w2,  adv_config