ncnn

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// yala is pleased to support the open source community by making ncnn available.
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//
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//
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// Copyright (C) 2022 yala <zhaojunchao@loongson.cn>;<junchao82@qq.com>. All rights reserved.
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// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
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// in compliance with the License. You may obtain a copy of the License at
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//
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// https://opensource.org/licenses/BSD-3-Clause
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//
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// Unless required by applicable law or agreed to in writing, software distributed
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// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
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// CONDITIONS OF ANY KIND, either express or implied. See the License for the
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// specific language governing permissions and limitations under the License.
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#include "dropout_loongarch.h"
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#if __loongarch_sx
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#include <lsxintrin.h>
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#endif // __loongarch_sx
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#include "loongarch_usability.h"
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namespace ncnn {
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Dropout_loongarch::Dropout_loongarch()
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{
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#if __loongarch_sx
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    support_packing = true;
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#endif // __loongarch_sx
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}
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int Dropout_loongarch::forward_inplace(Mat& bottom_top_blob, const Option& opt) const
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{
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    if (scale == 1.f)
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    {
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        return 0;
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    }
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    int w = bottom_top_blob.w;
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    int h = bottom_top_blob.h;
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    int d = bottom_top_blob.d;
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    int channels = bottom_top_blob.c;
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    int elempack = bottom_top_blob.elempack;
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    int size = w * h * d * elempack;
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    #pragma omp parallel for num_threads(opt.num_threads)
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    for (int q = 0; q < channels; q++)
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    {
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        float* ptr = bottom_top_blob.channel(q);
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        int i = 0;
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#if __loongarch_sx
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        __m128 _scale = (__m128)__lsx_vreplfr2vr_s(scale);
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        for (; i + 3 < size; i += 4)
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        {
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            __builtin_prefetch(ptr + 16);
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            __m128 _p = (__m128)__lsx_vld(ptr, 0);
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            _p = __lsx_vfmul_s(_p, _scale);
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            __lsx_vst(_p, ptr, 0);
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            ptr += 4;
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        }
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#endif // __loongarch_sx
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        for (; i < size; i++)
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        {
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            *ptr = *ptr * scale;
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            ptr++;
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        }
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    }
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    return 0;
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}
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} // namespace ncnn
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