e6a1a4bb326d673a029ca05f90d9e3930a89333b,cleverhans/attacks.py,CarliniWagnerL2,generate,#CarliniWagnerL2#Any#,618

Before Change

            labels = kwargs["y_target"]
        else:
            preds = self.model.get_probs(x)
            preds_max = tf.reduce_max(preds, 1, keep_dims=True)
            original_predictions = tf.to_float(tf.equal(preds,
                                                        preds_max))
            labels = original_predictions

        def cw_wrap(x_val, y_val):
            return np.array(attack.attack(x_val, y_val), dtype=np.float32)
        wrap = tf.py_func(cw_wrap, [x, labels], tf.float32)

After Change

        from .attacks_tf import CarliniWagnerL2 as CWL2
        self.parse_params(**kwargs)

        labels, nb_classes = self.get_labels(x, kwargs)

        attack = CWL2(self.sess, self.model, self.batch_size,
                      self.confidence, "y_target" in kwargs,

Instances