// Tencent is pleased to support the open source community by making ncnn available.
//
// Copyright (C) 2019 THL A29 Limited, a Tencent company. 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 "concat_arm.h"
#include <algorithm>
#include "layer_type.h"

namespace ncnn {

DEFINE_LAYER_CREATOR(Concat_arm)

Concat_arm::Concat_arm()
{
#if __ARM_NEON
    support_packing = true;

    packing_pack4 = 0;
#endif // __ARM_NEON
}

int Concat_arm::create_pipeline(const Option& opt)
{
#if __ARM_NEON
    if (opt.use_packing_layout)
    {

    {
        packing_pack4 = ncnn::create_layer(ncnn::LayerType::Packing);

        ncnn::ParamDict pd;
        pd.set(0, 4);

        packing_pack4->load_param(pd);

        packing_pack4->create_pipeline(opt);
    }

    }
#endif // __ARM_NEON

    return 0;
}

int Concat_arm::destroy_pipeline(const Option& opt)
{
#if __ARM_NEON
    if (opt.use_packing_layout)
    {

    if (packing_pack4)
    {
        packing_pack4->destroy_pipeline(opt);
        delete packing_pack4;
        packing_pack4 = 0;
    }

    }
#endif // __ARM_NEON

    return 0;
}

int Concat_arm::forward(const std::vector<Mat>& bottom_blobs, std::vector<Mat>& top_blobs, const Option& opt) const
{
    int dims = bottom_blobs[0].dims;

#if __ARM_NEON
    if (opt.use_packing_layout)
    {

    if (dims == 1) // axis == 0
    {
        // concat vector
        // total length
        size_t elemsize = bottom_blobs[0].elemsize;
        int elempack = bottom_blobs[0].elempack;
        int top_w = 0;
        for (size_t b=0; b<bottom_blobs.size(); b++)
        {
            const Mat& bottom_blob = bottom_blobs[b];
            top_w += bottom_blob.w * bottom_blob.elempack;
        }

        int out_elempack = top_w % 4 == 0 ? 4 : 1;
        size_t out_elemsize = elemsize / elempack * out_elempack;

        Mat& top_blob = top_blobs[0];
        top_blob.create(top_w / out_elempack, out_elemsize, out_elempack, opt.blob_allocator);
        if (top_blob.empty())
            return -100;

        float* outptr = top_blob;
        for (size_t b=0; b<bottom_blobs.size(); b++)
        {
            const Mat& bottom_blob = bottom_blobs[b];

            const float* ptr = bottom_blob;
            memcpy(outptr, ptr, bottom_blob.w * bottom_blob.elemsize);

            outptr += bottom_blob.w * bottom_blob.elempack;
        }

        return 0;
    }

    if (dims == 2 && axis == 0)
    {
        // concat image
        int w = bottom_blobs[0].w;

        // total height
        size_t elemsize = bottom_blobs[0].elemsize;
        int elempack = bottom_blobs[0].elempack;
        int top_h = 0;
        for (size_t b=0; b<bottom_blobs.size(); b++)
        {
            const Mat& bottom_blob = bottom_blobs[b];
            elemsize = std::min(elemsize, bottom_blob.elemsize);
            elempack = std::min(elempack, bottom_blob.elempack);
            top_h += bottom_blob.h * bottom_blob.elempack;
        }

        int out_elempack = top_h % 4 == 0 ? 4 : 1;
        size_t out_elemsize = elemsize / elempack * out_elempack;

        Mat& top_blob = top_blobs[0];
        top_blob.create(w, top_h / out_elempack, out_elemsize, out_elempack, opt.blob_allocator);
        if (top_blob.empty())
            return -100;

        Mat top_blob_unpacked = top_blob;
        if (elempack == 1 && out_elempack == 4)
        {
            top_blob_unpacked.create(w, top_h / elempack, elemsize, elempack, opt.workspace_allocator);
            if (top_blob_unpacked.empty())
                return -100;
        }

        float* outptr = top_blob_unpacked;
        for (size_t b=0; b<bottom_blobs.size(); b++)
        {
            const Mat& bottom_blob = bottom_blobs[b];

            if (bottom_blob.elempack == 4 && elempack == 1)
            {
                for (int i=0; i<bottom_blob.h; i++)
                {
                    const float* r0 = bottom_blob.row(i);

                    float* outptr0 = outptr;
                    float* outptr1 = outptr + w;
                    float* outptr2 = outptr + w*2;
                    float* outptr3 = outptr + w*3;

                    for (int j=0; j<w; j++)
                    {
                        *outptr0++ = r0[0];
                        *outptr1++ = r0[1];
                        *outptr2++ = r0[2];
                        *outptr3++ = r0[3];

                        r0 += 4;
                    }

                    outptr += w * 4;
                }
            }
            else // if (bottom_blob.elempack == 1 && elempack == 1) if (bottom_blob.elempack == 4 && elempack == 4)
            {
                int size = w * bottom_blob.h;

                const float* ptr = bottom_blob;
                memcpy(outptr, ptr, size * bottom_blob.elemsize);

                outptr += size * bottom_blob.elempack;
            }
        }

        // packing
        if (elempack == 1 && out_elempack == 4)
        {
            packing_pack4->forward(top_blob_unpacked, top_blob, opt);
        }

        return 0;
    }

    if (dims == 2 && axis == 1)
    {
        // interleave image row
        int h = bottom_blobs[0].h;
        size_t elemsize = bottom_blobs[0].elemsize;
        int elempack = bottom_blobs[0].elempack;

        // total width
        int top_w = 0;
        for (size_t b=0; b<bottom_blobs.size(); b++)
        {
            const Mat& bottom_blob = bottom_blobs[b];
            top_w += bottom_blob.w;
        }

        Mat& top_blob = top_blobs[0];
        top_blob.create(top_w, h, elemsize, elempack, opt.blob_allocator);
        if (top_blob.empty())
            return -100;

        #pragma omp parallel for num_threads(opt.num_threads)
        for (int i=0; i<h; i++)
        {
            float* outptr = top_blob.row(i);
            for (size_t b=0; b<bottom_blobs.size(); b++)
            {
                const Mat& bottom_blob = bottom_blobs[b];

                const float* ptr = bottom_blob.row(i);
                memcpy(outptr, ptr, bottom_blob.w * elemsize);

                outptr += bottom_blob.w * elempack;
            }
        }

        return 0;
    }

    if (dims == 3 && axis == 0)
    {
        // concat dim
        int w = bottom_blobs[0].w;
        int h = bottom_blobs[0].h;

        // total channels
        size_t elemsize = bottom_blobs[0].elemsize;
        int elempack = bottom_blobs[0].elempack;
        int top_channels = 0;
        for (size_t b=0; b<bottom_blobs.size(); b++)
        {
            const Mat& bottom_blob = bottom_blobs[b];
            elemsize = std::min(elemsize, bottom_blob.elemsize);
            elempack = std::min(elempack, bottom_blob.elempack);
            top_channels += bottom_blob.c * bottom_blob.elempack;
        }

        int out_elempack = top_channels % 4 == 0 ? 4 : 1;
        size_t out_elemsize = elemsize / elempack * out_elempack;

        Mat& top_blob = top_blobs[0];
        top_blob.create(w, h, top_channels / out_elempack, out_elemsize, out_elempack, opt.blob_allocator);
        if (top_blob.empty())
            return -100;

        Mat top_blob_unpacked = top_blob;
        if (elempack == 1 && out_elempack == 4)
        {
            top_blob_unpacked.create(w, h, top_channels / elempack, elemsize, elempack, opt.workspace_allocator);
            if (top_blob_unpacked.empty())
                return -100;
        }

        int p = 0;
        for (size_t b=0; b<bottom_blobs.size(); b++)
        {
            const Mat& bottom_blob = bottom_blobs[b];

            if (bottom_blob.elempack == 4 && elempack == 1)
            {
                int size = bottom_blob.w * bottom_blob.h;

                for (int q=0; q<bottom_blob.c; q++)
                {
                    const float* r0 = bottom_blob.channel(q);

                    float* outptr0 = top_blob_unpacked.channel(p);
                    float* outptr1 = top_blob_unpacked.channel(p+1);
                    float* outptr2 = top_blob_unpacked.channel(p+2);
                    float* outptr3 = top_blob_unpacked.channel(p+3);

                    for (int i=0; i<size; i++)
                    {
                        *outptr0++ = r0[0];
                        *outptr1++ = r0[1];
                        *outptr2++ = r0[2];
                        *outptr3++ = r0[3];

                        r0 += 4;
                    }

                    p += 4;
                }
            }
            else // if (bottom_blob.elempack == 1 && elempack == 1) if (bottom_blob.elempack == 4 && elempack == 4)
            {
                int size = bottom_blob.total();

                const float* ptr = bottom_blob;
                float* outptr = top_blob_unpacked.channel(p);
                memcpy(outptr, ptr, size * bottom_blob.elemsize);

                p += bottom_blob.c;
            }
        }

        // packing
        if (elempack == 1 && out_elempack == 4)
        {
            packing_pack4->forward(top_blob_unpacked, top_blob, opt);
        }

        return 0;
    }

    if (dims == 3 && axis == 1)
    {
        // interleave dim height
        int w = bottom_blobs[0].w;
        int channels = bottom_blobs[0].c;
        size_t elemsize = bottom_blobs[0].elemsize;
        int elempack = bottom_blobs[0].elempack;

        // total height
        int top_h = 0;
        for (size_t b=0; b<bottom_blobs.size(); b++)
        {
            const Mat& bottom_blob = bottom_blobs[b];
            top_h += bottom_blob.h;
        }

        Mat& top_blob = top_blobs[0];
        top_blob.create(w, top_h, channels, elemsize, elempack, opt.blob_allocator);
        if (top_blob.empty())
            return -100;

        #pragma omp parallel for num_threads(opt.num_threads)
        for (int q=0; q<channels; q++)
        {
            float* outptr = top_blob.channel(q);

            for (size_t b=0; b<bottom_blobs.size(); b++)
            {
                const Mat& bottom_blob = bottom_blobs[b];

                int size = bottom_blob.w * bottom_blob.h;

                const float* ptr = bottom_blob.channel(q);
                memcpy(outptr, ptr, size * elemsize);

                outptr += size * elempack;
            }
        }

        return 0;
    }

    if (dims == 3 && axis == 2)
    {
        // interleave dim width
        int h = bottom_blobs[0].h;
        int channels = bottom_blobs[0].c;
        size_t elemsize = bottom_blobs[0].elemsize;
        int elempack = bottom_blobs[0].elempack;

        // total height
        int top_w = 0;
        for (size_t b=0; b<bottom_blobs.size(); b++)
        {
            const Mat& bottom_blob = bottom_blobs[b];
            top_w += bottom_blob.w;
        }

        Mat& top_blob = top_blobs[0];
        top_blob.create(top_w, h, channels, elemsize, elempack, opt.blob_allocator);
        if (top_blob.empty())
            return -100;

        #pragma omp parallel for num_threads(opt.num_threads)
        for (int q=0; q<channels; q++)
        {
            float* outptr = top_blob.channel(q);

            for (int i=0; i<h; i++)
            {
                for (size_t b=0; b<bottom_blobs.size(); b++)
                {
                    const Mat& bottom_blob = bottom_blobs[b];

                    const float* ptr = bottom_blob.channel(q).row(i);
                    memcpy(outptr, ptr, bottom_blob.w * elemsize);

                    outptr += bottom_blob.w * elempack;
                }
            }
        }

        return 0;
    }

    } // opt.use_packing_layout
#endif // __ARM_NEON

    return Concat::forward(bottom_blobs, top_blobs, opt);
}

} // namespace ncnn