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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 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()