class_docstr: Abstract base class for all eager attack classes.
  :param model: An instance of the cleverhans.model.Model class.
  :param back: The backend to use. Inherited from AttackBase class.
  :param dtypestr: datatype of the input data samples and crafted
                   adversarial attacks.
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docstr: Generate adversarial examples and return them as a NumPy array.
  
  :param x_val: A NumPy array with the original inputs.
  :param **kwargs: optional parameters used by child classes.
  :return: A NumPy array holding the adversarial examples.
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code: def generate_np(self, x_val, **kwargs):
      """
      Generate adversarial examples and return them as a NumPy array.
  
      :param x_val: A NumPy array with the original inputs.
      :param **kwargs: optional parameters used by child classes.
      :return: A NumPy array holding the adversarial examples.
      """
      tfe = tf.contrib.eager
      x = tfe.Variable(x_val)
      adv_x = self.generate(x, **kwargs)
      return adv_x.numpy()
  
imports: from distutils.version import LooseVersion
  import numpy
  import tensorflow
  from cleverhans import attacks
  from cleverhans import utils
  from cleverhans.model import CallableModelWrapper, wrapper_warning
  from cleverhans.model import Model
  from cleverhans.loss import LossCrossEntropy
label_desc: Use image node_id 3 for calling the Attack obj's underlying member method code with example usage: obj.generate_np(x_val) and returns: adv_x