0f100b908573bdff46341e3d0766359a72bb0060,art/attacks/evasion/wasserstein.py,Wasserstein,_generate_batch,#Wasserstein#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,210

Before Change

        if targeted:
            err = get_labels_np_array(self.estimator.predict(x, batch_size=batch_size)) == targets
        else:
            err = get_labels_np_array(self.estimator.predict(x, batch_size=batch_size)) != targets

        err_best = err
        eps = np.ones(batch_size) * eps

After Change

                )
            else:
                err = (
                    np.argmax(self.estimator.predict(adv_x, batch_size=batch_size), axis=1)
                    != np.argmax(targets, axis=1)
                )

            if np.mean(err) > np.mean(err_best):

Instances