// 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 "tanh_x86.h"

#include "x86_activation.h"

#include <math.h>

namespace ncnn {

TanH_x86::TanH_x86()
{
#if __SSE2__
    support_packing = true;
#endif // __SSE2__
}

int TanH_x86::forward_inplace(Mat& bottom_top_blob, const Option& opt) const
{
    int w = bottom_top_blob.w;
    int h = bottom_top_blob.h;
    int channels = bottom_top_blob.c;
    int size = w * h;
#if __SSE2__
    int elempack = bottom_top_blob.elempack;

#if __AVX__
#if __AVX512F__
    if (elempack == 16)
    {
        Mat tmp;
        convert_packing(bottom_top_blob, tmp, 8, opt);

        forward_inplace(tmp, opt);

        convert_packing(tmp, bottom_top_blob, 16, opt);

        return 0;
    }
#endif // __AVX512F__

    if (elempack == 8)
    {
        #pragma omp parallel for num_threads(opt.num_threads)
        for (int q = 0; q < channels; q++)
        {
            float* ptr = bottom_top_blob.channel(q);

            for (int i = 0; i < size; i++)
            {
                __m256 _p = _mm256_loadu_ps(ptr);
                _p = tanh_avx(_p);
                _mm256_storeu_ps(ptr, _p);
                ptr += 8;
            }
        }

        return 0;
    }
#endif // __AVX__

    if (elempack == 4)
    {
        #pragma omp parallel for num_threads(opt.num_threads)
        for (int q = 0; q < channels; q++)
        {
            float* ptr = bottom_top_blob.channel(q);

            for (int i = 0; i < size; i++)
            {
                __m128 _p = _mm_loadu_ps(ptr);
                _p = tanh_sse(_p);
                _mm_storeu_ps(ptr, _p);
                ptr += 4;
            }
        }

        return 0;
    }
#endif // __SSE2__

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

        int i = 0;
#if __SSE2__
#if __AVX__
        for (; i + 7 < size; i += 8)
        {
            __m256 _p = _mm256_loadu_ps(ptr);
            _p = tanh_avx(_p);
            _mm256_storeu_ps(ptr, _p);
            ptr += 8;
        }
#endif // __AVX__
        for (; i + 3 < size; i += 4)
        {
            __m128 _p = _mm_loadu_ps(ptr);
            _p = tanh_sse(_p);
            _mm_storeu_ps(ptr, _p);
            ptr += 4;
        }
#endif // __SSE2__
        for (; i < size; i++)
        {
            *ptr = tanh(*ptr);
            ptr++;
        }
    }

    return 0;
}

} // namespace ncnn
