ncnn / src /layer /riscv /convolution_1x1_packn.h
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//
// Copyright (C) 2021 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.
static void conv1x1s1_sgemm_packn_rvv(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Mat& _bias, const Option& opt)
{
int w = bottom_blob.w;
int h = bottom_blob.h;
const int size = w * h;
Mat bottom_im2col = bottom_blob;
bottom_im2col.w = size;
bottom_im2col.h = 1;
im2col_sgemm_packn_rvv(bottom_im2col, top_blob, kernel, _bias, opt);
}
static void conv1x1s2_sgemm_packn_rvv(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Mat& _bias, const Option& opt)
{
const int packn = csrr_vlenb() / 4;
const size_t vl = vsetvl_e32m1(packn);
int w = bottom_blob.w;
int channels = bottom_blob.c;
size_t elemsize = bottom_blob.elemsize;
int elempack = bottom_blob.elempack;
int outw = top_blob.w;
int outh = top_blob.h;
const int tailstep = (w - 2 * outw + w) * packn;
Mat bottom_blob_shrinked;
bottom_blob_shrinked.create(outw, outh, channels, elemsize, elempack, opt.workspace_allocator);
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < channels; p++)
{
const float* r0 = bottom_blob.channel(p);
float* outptr = bottom_blob_shrinked.channel(p);
for (int i = 0; i < outh; i++)
{
for (int j = 0; j < outw; j++)
{
vfloat32m1_t _val = vle32_v_f32m1(r0, vl);
vse32_v_f32m1(outptr, _val, vl);
r0 += packn * 2;
outptr += packn;
}
r0 += tailstep;
}
}
conv1x1s1_sgemm_packn_rvv(bottom_blob_shrinked, top_blob, kernel, _bias, opt);
}