weights = self.optimizer.trainable_params()
        grad_fn = mindspore.value_and_grad(model, grad_position=None, weights=weights, has_aux=True)
        (total_loss, loss_cls, loss_center, loss_triplet, loss_circle, loss_cosface, loss_triplet_add, loss_triplet_mtrain, loss_stc, loss_triplet_mtest, loss_domain_intra, loss_domain_inter, loss_Center), inputs_gradient = grad_fn(images, targets, domainids, epoch, opt)
        sum_num = mindspore.ops.sum(mindspore.ops.stack([mindspore.ops.sum(item) for item in inputs_gradient]))
        print("total_loss, sum_num", total_loss, sum_num)