7fb43a1170746644db33cb8a5f10fe94298d85da,art/classifiers/keras.py,KerasClassifier,class_gradient,#KerasClassifier#Any#Any#,80

Before Change

        if logits:
            if not hasattr(self, "_class_grads_logits"):
                self._init_class_grads(logits=True)
            return np.swapaxes(np.array(self._class_grads_logits([x])), 0, 1)
        else:
            if not hasattr(self, "_class_grads"):
                self._init_class_grads(logits=False)
            return np.swapaxes(np.array(self._class_grads([x])), 0, 1)

After Change

                 `(batch_size, nb_classes, input_shape)`.
        :rtype: `np.ndarray`
        
        x_ = self._apply_processing(x)
        if logits:
            if not hasattr(self, "_class_grads_logits"):
                self._init_class_grads(logits=True)
            grads = np.swapaxes(np.array(self._class_grads_logits([x_])), 0, 1)
        else:
            if not hasattr(self, "_class_grads"):
                self._init_class_grads(logits=False)
            grads = np.swapaxes(np.array(self._class_grads([x_])), 0, 1)

        grads = self._apply_processing_gradient(grads)
        assert grads.shape == (x_.shape[0], self.nb_classes) + self.input_shape

        return grads

Instances