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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 eval_advs(self, x, y, preds_adv, X_test, Y_test, att_type):
 """ Evaluate the accuracy of the model on adversarial examples :param x: symbolic input to model. :param y: symbolic variable for the label. :param preds_adv: symbolic variable for the prediction on an adversarial example. :param X_test: NumPy array of test set inputs. :param Y_test: NumPy array of test set labels. :param att_type: name of the attack. """

    end = (len(X_test) // self.batch_size) * self.batch_size

    if self.hparams.fast_tests:
      end = 10*self.batch_size

    acc = model_eval(self.sess, x, y, preds_adv, X_test[:end],
                     Y_test[:end], args=self.eval_params)
    self.log_value('test_accuracy_%s' % att_type, acc,
                   'Test accuracy on adversarial examples')
    return acc