// 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 {
using npu_preparation = at_npu::native::OpPreparation;
using npu_utils = at_npu::native::NpuUtils;

namespace {
at::SmallVector<int64_t, SIZE> upsample_trilinear3d_infer_size(const at::Tensor &input, at::IntArrayRef output_size,
                                                               c10::optional<double> scales_d,
                                                               c10::optional<double> scales_h,
                                                               c10::optional<double> scales_w)
{
    TORCH_CHECK(input.dim() == 5, "The input should be 5D, but got ", input.dim(), "D" + OPS_ERROR(ErrCode::PARAM));
    TORCH_CHECK(output_size.size() == 3, "The length of output_size should be equal to 3, but got ",
                output_size.size(), OPS_ERROR(ErrCode::PARAM));

    int64_t output_depth = output_size[0];
    int64_t output_height = output_size[1];
    int64_t output_width = output_size[2];

    int64_t nbatch = input.size(0);
    int64_t channels = input.size(1);

    at::SmallVector<int64_t, SIZE> output_sizes = {nbatch, channels, output_depth, output_height, output_width};
    return output_sizes;
}

at::Tensor &upsample_trilinear3d_out_nocheck(at::Tensor &result, const at::Tensor &input, at::IntArrayRef output_size,
                                             bool align_corners, c10::optional<double> scales_d,
                                             c10::optional<double> scales_h, c10::optional<double> scales_w)
{
    at_npu::native::OpCommand cmd;
    cmd.Name("UpsampleTrilinear3d")
        .Input(input)
        .Output(result)
        .Attr("output_size", output_size)
        .Attr("align_corners", align_corners)
        .Run();
    return result;
}
} // namespace

at::Tensor &upsample_trilinear3d_out(const at::Tensor &input, at::IntArrayRef output_size, bool align_corners,
                                     c10::optional<double> scales_d, c10::optional<double> scales_h,
                                     c10::optional<double> scales_w, at::Tensor &result)
{
    auto op_infer_output_size = upsample_trilinear3d_infer_size(input, output_size, scales_d, scales_h, scales_w);
    npu_preparation::CheckOut({input}, result, input, op_infer_output_size);

    if (!npu_utils::check_match(&result)) {
        auto contiguous_out = npu_utils::format_contiguous(result);
        upsample_trilinear3d_out_nocheck(contiguous_out, input, output_size, align_corners, scales_d, scales_h,
                                         scales_w);
        npu_utils::format_fresh_view(result, contiguous_out);
    } else {
        upsample_trilinear3d_out_nocheck(result, input, output_size, align_corners, scales_d, scales_h, scales_w);
    }
    return result;
}

at::Tensor upsample_trilinear3d(const at::Tensor &input, at::IntArrayRef output_size, bool align_corners,
                                c10::optional<double> scales_d, c10::optional<double> scales_h,
                                c10::optional<double> scales_w)
{
    auto op_infer_output_size = upsample_trilinear3d_infer_size(input, output_size, scales_d, scales_h, scales_w);
    at::Tensor result = npu_preparation::apply_tensor(input, op_infer_output_size);
    upsample_trilinear3d_out_nocheck(result, input, output_size, align_corners, scales_d, scales_h, scales_w);
    return result;
}
} // namespace acl_op