// Copyright (c) 2023 Huawei Technologies Co., Ltd
// 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 {
using npu_preparation = at_npu::native::OpPreparation;

at::Tensor npu_bounding_box_decode(
    const at::Tensor& rois,
    const at::Tensor& deltas,
    double means0,
    double means1,
    double means2,
    double means3,
    double stds0,
    double stds1,
    double stds2,
    double stds3,
    at::IntArrayRef max_shape,
    double wh_ratio_clip)
{
    c10::SmallVector<int64_t, SIZE> output_size = {rois.size(0), 4};
    at::Tensor result = npu_preparation::apply_tensor(rois, output_size);
    c10::SmallVector<float, SIZE> means = {
        static_cast<float>(means0),
        static_cast<float>(means1),
        static_cast<float>(means2),
        static_cast<float>(means3)};
    c10::SmallVector<float, SIZE> stds = {
        static_cast<float>(stds0),
        static_cast<float>(stds1),
        static_cast<float>(stds2),
        static_cast<float>(stds3)};
    at_npu::native::OpCommand cmd;
    cmd.Name("BoundingBoxDecode")
        .Input(rois)
        .Input(deltas)
        .Output(result)
        .Attr("means", means)
        .Attr("stds", stds)
        .Attr("max_shape", max_shape)
        .Attr("wh_ratio_clip", static_cast<float>(wh_ratio_clip))
        .Run();
    return result;
}
} // namespace acl_op