def grad(self, pred, target):
        pred = self._softmax(pred)
        target = ca.nnet.one_hot_encode(target, self.n_classes)
        return -(target - pred)
dataset/ETHPy150Open andersbll/deeppy/deeppy/loss.py/SoftmaxCrossEntropy.grad/original