code: def l2_config(num_iter=1, epsilon=(8 / 255), step_size=(2 / 255)):
      adv_config = nsl.configs.AdvNeighborConfig(
          adv_grad_norm="l2",
          pgd_iterations=num_iter,
          adv_step_size=step_size,
          clip_value_min=None,
          clip_value_max=None,
          pgd_epsilon=epsilon,
      )
      return {"adv_config": adv_config}
  
imports: from absl import logging
  import gin
  import neural_structured_learning
  from multi_representation_adversary.cleverhans_adapter import sparse_l1_descent
  from multi_representation_adversary.cleverhans_adapter import utils_tf
  import numpy
  import tensorflow.compat.v2
label_desc: Use image node_id 2 for calling a global function with example usage: l2_config(num_iter, epsilon, step_size) and returns: dict