f9dd2e3636db61ee1b4d32ee4f494fd9e71adc12,cleverhans/attacks.py,FastGradientMethod,generate_np,#FastGradientMethod#Any#Any#,159

Before Change

        if params["Y"] is None:
            X_adv, = batch_eval_com([self.x], [self.default_graph], [X])
        else:
            X_adv, = batch_eval_com([self.x, self.y], [self.default_graph],
                                    [X, params["Y"]])

        return X_adv

After Change

        import tensorflow as tf

        // Generate this attack"s graph if it hasn"t been done previously
        if not hasattr(self, "_x"):
            input_shape = list(X.shape)
            input_shape[0] = None
            self._x = tf.placeholder(tf.float32, shape=input_shape)
            self._x_adv = self.generate(self._x)

        // Run symbolic graph without or with true labels
        if params["Y"] is None:
            feed_dict = {self._x: X}
        else:
            feed_dict = {self._x: X, self.y: params["Y"]}
        return self.sess.run(self._x_adv, feed_dict=feed_dict)

Instances