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"]
code: def __init__(self, model):
      super(CW_L2_Attack, self).__init__(model)
  
      self._model = model._model
      mean, std = model._preprocess
      self.mean = torch.from_numpy(mean)
      self.std = torch.from_numpy(std)
  
imports: from __future__ import division
  from __future__ import print_function
  from builtins import range
  import logging
  import numpy
  import torch
  import torchvision
  from torchvision import datasets, transforms
  from torch.autograd import Variable
  from torch.autograd.gradcheck import zero_gradients
  import torch.utils.data.dataloader
  import torch.nn
  from torchvision import models
  import torch.nn.functional
  import numpy
  from .base import Attack
label_desc: Use image node_id 1 to create a new CW_L2_Attack object from inherited base classes: Attack with example: obj = CW_L2_Attack(model)