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- // 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 "softmax_loongarch.h"
-
- #include <float.h>
-
- #if __loongarch_sx
- #include <lsxintrin.h>
- #include "lsx_mathfun.h"
- #endif // __loongarch_sx
-
- namespace ncnn {
-
- int Softmax_loongarch::forward_inplace(Mat& bottom_top_blob, const Option& opt) const
- {
- int dims = bottom_top_blob.dims;
- size_t elemsize = bottom_top_blob.elemsize;
- int positive_axis = axis < 0 ? dims + axis : axis;
-
- if (dims != 3 || positive_axis != 0)
- return Softmax::forward_inplace(bottom_top_blob, opt);
-
- // value = exp( value - global max value )
- // sum all value
- // value = value / sum
-
- int w = bottom_top_blob.w;
- int h = bottom_top_blob.h;
- int channels = bottom_top_blob.c;
- int size = w * h;
-
- Mat max;
- max.create(w, h, elemsize, opt.workspace_allocator);
- if (max.empty())
- return -100;
- max.fill(-FLT_MAX);
- for (int q = 0; q < channels; q++)
- {
- float* ptr = bottom_top_blob.channel(q);
- float* maxptr = max;
-
- for (int i = 0; i < size; i++)
- {
- maxptr[i] = std::max(maxptr[i], ptr[i]);
- }
- }
-
- #pragma omp parallel for num_threads(opt.num_threads)
- for (int q = 0; q < channels; q++)
- {
- float* ptr = bottom_top_blob.channel(q);
- float* maxptr = max;
-
- #if __loongarch_sx
- int nn = size >> 2;
- int remain = size - (nn << 2);
- #else
- int remain = size;
- #endif // __loongarch_sx
-
- #if __loongarch_sx
- for (; nn > 0; nn--)
- {
- __m128 _p = (__m128)__lsx_vld(ptr, 0);
- __m128 _max = (__m128)__lsx_vld(maxptr, 0);
-
- _p = exp_ps(__lsx_vfsub_s(_p, _max));
-
- __lsx_vst(_p, ptr, 0);
-
- ptr += 4;
- maxptr += 4;
- }
- #endif // __loongarch_sx
-
- for (; remain > 0; remain--)
- {
- *ptr = exp(*ptr - *maxptr);
-
- ptr++;
- maxptr++;
- }
- }
-
- Mat sum;
- sum.create(w, h, elemsize, opt.workspace_allocator);
- if (sum.empty())
- return -100;
- sum.fill(0.f);
- for (int q = 0; q < channels; q++)
- {
- float* ptr = bottom_top_blob.channel(q);
- float* sumptr = sum;
-
- #if __loongarch_sx
- int nn = size >> 2;
- int remain = size - (nn << 2);
- #else
- int remain = size;
- #endif // __loongarch_sx
-
- #if __loongarch_sx
- for (; nn > 0; nn--)
- {
- __m128 _p = (__m128)__lsx_vld(ptr, 0);
- __m128 _sum = (__m128)__lsx_vld(sumptr, 0);
- _sum = __lsx_vfadd_s(_sum, _p);
- __lsx_vst(_sum, sumptr, 0);
-
- ptr += 4;
- sumptr += 4;
- }
- #endif // __loongarch_sx
-
- for (; remain > 0; remain--)
- {
- *sumptr += *ptr;
-
- ptr++;
- sumptr++;
- }
- }
-
- #pragma omp parallel for num_threads(opt.num_threads)
- for (int q = 0; q < channels; q++)
- {
- float* ptr = bottom_top_blob.channel(q);
- float* sumptr = sum;
-
- #if __loongarch_sx
- int nn = size >> 2;
- int remain = size - (nn << 2);
- #else
- int remain = size;
- #endif // __loongarch_sx
-
- #if __loongarch_sx
- for (; nn > 0; nn--)
- {
- __m128 _p = (__m128)__lsx_vld(ptr, 0);
- __m128 _sum = (__m128)__lsx_vld(sumptr, 0);
- _p = __lsx_vfdiv_s(_p, _sum);
- __lsx_vst(_p, ptr, 0);
-
- ptr += 4;
- sumptr += 4;
- }
- #endif // __loongarch_sx
-
- for (; remain > 0; remain--)
- {
- *ptr /= *sumptr;
-
- ptr++;
- sumptr++;
- }
- }
-
- return 0;
- }
-
- } // namespace ncnn
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