class_docstr: Uses Adam to minimize the CW L2 objective function
  
  Paper link: https://arxiv.org/abs/1608.04644
class_docstr_tok: ["Uses","Adam","to","minimize","the","CW","L2","objective","function","Paper","link",":","https",":","\/\/arxiv.org\/abs\/1608.04644"]
docstr: model predict
  the image already restore(clip_min, clip_max)
docstr_tok: ["model","predict","the","image","already","restore","(","clip_min",",","clip_max",")"]
code: def _predict_adv(self, img_constrained):
      """
      model predict
      the image already restore(clip_min, clip_max)
      """
      adv_logits = self.model.predict(img_constrained)
      adv_label = np.argmax(adv_logits)
  
      return adv_label, adv_logits[adv_label]
  
file_path: AdvBox/adversarialbox/attacks/cw.py
imports: from __future__ import division
  from __future__ import print_function
  from builtins import range
  import logging
  import numpy
  import paddle.fluid
  from .base import Attack
label_desc: Use image node_id 8 for calling the CW_L2_Attack obj's underlying member method code with example usage: obj._predict_adv(img_constrained) and returns: adv_label,  adv_logits