code: def _test_gen_adv_neighbor_for_feature_columns_setup(self):
      # For linear regression
      x = {
          "fc1": tf.constant([[-1.0]]),
          "fc2": tf.constant([[1.0]]),
      }
      y = tf.constant([0.0])
      w = tf.constant([[3.0], [4.0]])
  
      # gradient = [[6, 8]], normalized gradient = [[0.6, 0.8]]
      expected_neighbor_fc1 = [[-1.0 + 0.1 * 0.6]]
      expected_neighbor_fc2 = [[1.0 + 0.1 * 0.8]]
      adv_config = configs.AdvNeighborConfig(
          feature_mask={}, adv_step_size=0.1, adv_grad_norm="l2"
      )
      return (
          x,
          y,
          w,
          expected_neighbor_fc1,
          expected_neighbor_fc2,
          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 7 for calling the GenAdvNeighborTest obj's underlying member method code with example usage: obj._test_gen_adv_neighbor_for_feature_columns_setup() and returns: x,  y,  w,  expected_neighbor_fc1,  expected_neighbor_fc2,  adv_config