// Copyright 2019 Tencent
// SPDX-License-Identifier: BSD-3-Clause

#include "tanh_arm.h"

#if __ARM_NEON
#include <arm_neon.h>
#include "neon_mathfun.h"
#endif // __ARM_NEON

#include "arm_usability.h"
#include "cpu.h"

namespace ncnn {

TanH_arm::TanH_arm()
{
#if __ARM_NEON
    support_packing = true;
#if NCNN_ARM82
    support_fp16_storage = cpu_support_arm_asimdhp();
#endif
#endif // __ARM_NEON

#if NCNN_BF16
    support_bf16_storage = true;
#endif
}

int TanH_arm::forward_inplace(Mat& bottom_top_blob, const Option& opt) const
{
    int elembits = bottom_top_blob.elembits();

#if NCNN_ARM82
    if (support_fp16_storage && opt.use_fp16_storage && elembits == 16)
    {
        if (opt.use_fp16_arithmetic)
            return forward_inplace_fp16sa(bottom_top_blob, opt);
        else
            return forward_inplace_fp16s(bottom_top_blob, opt);
    }
#endif

#if NCNN_BF16
    if (opt.use_bf16_storage && elembits == 16)
        return forward_inplace_bf16s(bottom_top_blob, opt);
#endif

    int w = bottom_top_blob.w;
    int h = bottom_top_blob.h;
    int d = bottom_top_blob.d;
    int channels = bottom_top_blob.c;
    int size = w * h * d;
    int elempack = bottom_top_blob.elempack;

#if __ARM_NEON
    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++)
            {
                float32x4_t _p = vld1q_f32(ptr);
                _p = tanh_ps(_p);
                vst1q_f32(ptr, _p);
                ptr += 4;
            }
        }

        return 0;
    }
#endif // __ARM_NEON

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

#if __ARM_NEON
        int nn = size >> 2;
        int remain = size - (nn << 2);
#else
        int remain = size;
#endif // __ARM_NEON

#if __ARM_NEON
        for (; nn > 0; nn--)
        {
            float32x4_t _p = vld1q_f32(ptr);
            _p = tanh_ps(_p);
            vst1q_f32(ptr, _p);
            ptr += 4;
        }
#endif // __ARM_NEON
        for (; remain > 0; remain--)
        {
            *ptr = tanhf(*ptr);
            ptr++;
        }
    }

    return 0;
}

#if NCNN_BF16
int TanH_arm::forward_inplace_bf16s(Mat& bottom_top_blob, const Option& opt) const
{
    int w = bottom_top_blob.w;
    int h = bottom_top_blob.h;
    int d = bottom_top_blob.d;
    int channels = bottom_top_blob.c;
    int size = w * h * d;
    int elempack = bottom_top_blob.elempack;

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

            for (int i = 0; i < size; i++)
            {
                float32x4_t _p = bfloat2float(vld1_u16(ptr));
                _p = tanh_ps(_p);
                vst1_u16(ptr, float2bfloat(_p));
                ptr += 4;
            }
        }

        return 0;
    }
#endif // __ARM_NEON

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

#if __ARM_NEON
        int nn = size >> 2;
        int remain = size - (nn << 2);
#else
        int remain = size;
#endif // __ARM_NEON

#if __ARM_NEON
        for (; nn > 0; nn--)
        {
            float32x4_t _p = bfloat2float(vld1_u16(ptr));
            _p = tanh_ps(_p);
            vst1_u16(ptr, float2bfloat(_p));
            ptr += 4;
        }
#endif // __ARM_NEON
        for (; remain > 0; remain--)
        {
            float v = bfloat16_to_float32(*ptr);
            v = tanhf(v);
            *ptr = float32_to_bfloat16(v);
            ptr++;
        }
    }

    return 0;
}
#endif // NCNN_BF16

} // namespace ncnn
