code: def test_linf_attack(self, attack_name, random_start):
      num_iter, step_size, epsilon = 4, 0.02, 0.06
      gin.parse_config(
          [
              f"attacks.linf_config.num_iter = {num_iter}",
              f"attacks.linf_config.step_size = {step_size}",
              f"attacks.linf_config.epsilon = {epsilon}",
              "attacks.union_config.restart = 5",
          ]
      )
  
      x = tf.random.uniform(shape=self.batched_input_shape)
      y = tf.random.categorical(
          tf.zeros([self.batch_size, self.num_classes]), 1
      )
      attack = attacks.construct_attack(attack_name)
      adv_x = attack.attack(
          tf.constant(x),
          tf.constant(y),
          self.model,
          self.loss_fn,
          random_start=random_start,
      )
  
      self.assertAllLessEqual(tf.math.abs(adv_x - x), epsilon + 1e-5)
  
file_path: neural-structured-learning/research/multi_representation_adversary/multi_representation_adversary/attacks_test.py
imports: from absl.testing import parameterized
  import gin
  from multi_representation_adversary import attacks
  import numpy
  import tensorflow.compat.v2
label_desc: Use image node_id 2 for calling the AttacksTest obj's underlying member method code with example usage: obj.test_linf_attack(attack_name, random_start) without return types