File size: 1,869 Bytes
be903e2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 | // yala is pleased to support the open source community by making ncnn available.
//
//
// Copyright (C) 2022 yala <zhaojunchao@loongson.cn>;<junchao82@qq.com>. 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 "absval_loongarch.h"
#if __loongarch_sx
#include <lsxintrin.h>
#endif // __loongarch_sx
namespace ncnn {
AbsVal_loongarch::AbsVal_loongarch()
{
#if __loongarch_sx
support_packing = true;
#endif
}
int AbsVal_loongarch::forward_inplace(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 elempack = bottom_top_blob.elempack;
int size = w * h * d * elempack;
#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 __loongarch_sx
for (; i + 3 < size; i += 4)
{
__builtin_prefetch(ptr + 16);
__m128i _p = __lsx_vld(ptr, 0);
__m128i _outp = __lsx_vbitclri_w(_p, 31);
__lsx_vst(_outp, ptr, 0);
ptr += 4;
}
#endif // __loongarch_sx
for (; i < size; i++)
{
*ptr = *ptr > 0 ? *ptr : -*ptr;
ptr++;
}
}
return 0;
}
} // namespace ncnn
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