// Copyright (c) 2023 Huawei Technologies Co., Ltd
// Copyright (c) 2019, Facebook CORPORATION.
// All rights reserved.
//
// Licensed under the BSD 3-Clause License  (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// https://opensource.org/licenses/BSD-3-Clause
//
// 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.

#include "op_plugin/AclOpsInterface.h"
#include "op_plugin/utils/OpAdapter.h"

namespace acl_op {

at::Tensor &replication_pad1d_backward_out(const at::Tensor &grad_output, const at::Tensor &input,
                                           at::IntArrayRef padding, at::Tensor &grad_input)
{
    TORCH_CHECK(padding.size() >= 2, "padding length shoud be at least 2" + OPS_ERROR(ErrCode::PARAM));
    c10::SmallVector<int64_t, N> paddings = {padding[0], padding[1], 0, 0};
    at::Tensor input_cp = input.unsqueeze(0);
    at::Tensor grad_output_cp = grad_output.unsqueeze(0);
    acl_op::replication_pad2d_backward_out(grad_output_cp, input_cp, paddings, grad_input);
    grad_input.squeeze_(0);
    return grad_input;
}

at::Tensor replication_pad1d_backward(const at::Tensor &grad_output, const at::Tensor &input, at::IntArrayRef padding)
{
    TORCH_CHECK(padding.size() >= 2, "padding length shoud be at least 2" + OPS_ERROR(ErrCode::PARAM));
    c10::SmallVector<int64_t, N> paddings = {padding[0], padding[1], 0, 0};
    at::Tensor input_cp = input.unsqueeze(0);
    at::Tensor grad_output_cp = grad_output.unsqueeze(0);
    at::Tensor grad_input = acl_op::replication_pad2d_backward(grad_output_cp, input_cp, paddings);
    grad_input.squeeze_(0);
    return grad_input;
}

} // namespace acl_op