# Copyright (c) 2024-2024, Huawei Technologies Co., Ltd.
# All rights reserved.
#
# Licensed under the Apache License, Version 2.0  (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import torch


def npu_linear(x, weight, bias):
    output = torch.nn.functional.linear(x, weight, bias)
    return output


def npu_linear_backward(grad, input_data, weight):
    input_grad = torch.matmul(grad, weight)
    weight_grad = torch.matmul(grad.t(), input_data)
    return input_grad.cpu(), weight_grad.cpu()
