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//
// Copyright (C) 2022 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 conv3x3s1_winograd43_transform_input_rvv(const Mat& bottom_blob, Mat& bottom_blob_tm, const Option& opt)
{
const int w = bottom_blob.w;
const int h = bottom_blob.h;
const int inch = bottom_blob.c;
const int w_tiles = (w - 2) / 4;
const int h_tiles = (h - 2) / 4;
const int tiles = w_tiles * h_tiles;
const float sq2 = 1.41421356237;
const float sq2_d2 = 1.41421356237 / 2;
// const float itm[6][6] = {
// {1.0f, 0.0f, -2.5f, 0.0f, 1.0f, 0.0f},
// {0.0f, -sq2, -2.0f, sq2/2, 1.0f, 0.0f},
// {0.0f, sq2, -2.0f, -sq2/2, 1.0f, 0.0f},
// {0.0f, -sq2/2, -0.5f, sq2, 1.0f, 0.0f},
// {0.0f, sq2/2, -0.5f, -sq2, 1.0f, 0.0f},
// {0.0f, 1.0f, 0.0f, -2.5f, 0.0f, 1.0f}
// };
// 0 = r00 - 2.5f * r02 + r04
// 1 = -(sq2 * r01 - sq2_d2 * r03) + (r04 - 2 * r02)
// 2 = (sq2 * r01 - sq2_d2 * r03) + (r04 - 2 * r02)
// 3 = -(sq2_d2 * r01 - sq2 * r03) + (r04 - 0.5f * r02)
// 4 = (sq2_d2 * r01 - sq2 * r03) + (r04 - 0.5f * r02)
// 5 = r01 - 2.5f * r03 + r05
#pragma omp parallel for num_threads(opt.num_threads)
for (int q = 0; q < inch; q++)
{
const Mat img0 = bottom_blob.channel(q);
Mat img0_tm = bottom_blob_tm.channel(q);
float tmp[6][6];
// tile
for (int i = 0; i < h_tiles; i++)
{
for (int j = 0; j < w_tiles; j++)
{
const float* r0 = img0.row(i * 4) + (j * 4);
for (int m = 0; m < 6; m++)
{
float r00 = r0[0];
float r01 = r0[1];
float r02 = r0[2];
float r03 = r0[3];
float r04 = r0[4];
float r05 = r0[5];
float tmp01a = sq2 * r01 - sq2_d2 * r03;
float tmp01b = r04 - 2 * r02;
float tmp23a = sq2_d2 * r01 - sq2 * r03;
float tmp23b = r04 - 0.5f * r02;
tmp[0][m] = r00 - 2.5f * r02 + r04;
tmp[1][m] = tmp01b - tmp01a;
tmp[2][m] = tmp01b + tmp01a;
tmp[3][m] = tmp23b - tmp23a;
tmp[4][m] = tmp23b + tmp23a;
tmp[5][m] = r01 - 2.5f * r03 + r05;
r0 += w;
}
float* r0_tm_0 = (float*)img0_tm + (i * w_tiles + j);
float* r0_tm_1 = r0_tm_0 + tiles;
float* r0_tm_2 = r0_tm_0 + tiles * 2;
float* r0_tm_3 = r0_tm_0 + tiles * 3;
float* r0_tm_4 = r0_tm_0 + tiles * 4;
float* r0_tm_5 = r0_tm_0 + tiles * 5;
for (int m = 0; m < 6; m++)
{
float r00 = tmp[m][0];
float r01 = tmp[m][1];
float r02 = tmp[m][2];
float r03 = tmp[m][3];
float r04 = tmp[m][4];
float r05 = tmp[m][5];
float tmp01a = sq2 * r01 - sq2_d2 * r03;
float tmp01b = r04 - 2 * r02;
float tmp23a = sq2_d2 * r01 - sq2 * r03;
float tmp23b = r04 - 0.5f * r02;
r0_tm_0[0] = r00 - 2.5f * r02 + r04;
r0_tm_1[0] = tmp01b - tmp01a;
r0_tm_2[0] = tmp01b + tmp01a;
r0_tm_3[0] = tmp23b - tmp23a;
r0_tm_4[0] = tmp23b + tmp23a;
r0_tm_5[0] = r01 - 2.5f * r03 + r05;
r0_tm_0 += tiles * 6;
r0_tm_1 += tiles * 6;
r0_tm_2 += tiles * 6;
r0_tm_3 += tiles * 6;
r0_tm_4 += tiles * 6;
r0_tm_5 += tiles * 6;
}
}
}
}
}
static void conv3x3s1_winograd43_transform_output_rvv(const Mat& top_blob_tm, Mat& top_blob, const Mat& bias, const Option& opt)
{
const int outw = top_blob.w;
const int outh = top_blob.h;
const int outch = top_blob.c;
const int w_tiles = outw / 4;
const int h_tiles = outh / 4;
const int tiles = w_tiles * h_tiles;
const float* biasptr = bias;
const float sq2 = 1.41421356237;
const float sq2_m2 = 1.41421356237 * 2;
const float sq2_d2 = 1.41421356237 / 2;
const float sq2_d4 = 1.41421356237 / 4;
// const float otm[4][6] = {
// {1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 0.0f},
// {0.0f, sq2/2, -sq2/2, sq2, -sq2, 0.0f},
// {0.0f, 0.5f, 0.5f, 2.0f, 2.0f, 0.0f},
// {0.0f, sq2/4, -sq2/4, sq2*2, -sq2*2, 1.0f}
// };
// 0 = r00 + (r01 + r02) + (r03 + r04)
// 1 = (r01 - r02) * sq2_d2 + (r03 - r04) * sq2
// 2 = (r01 + r02) * 0.5f + (r03 + r04) * 2
// 3 = r05 + (r01 - r02) * sq2_d4 + (r03 - r04) * sq2_m2
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < outch; p++)
{
const Mat out0_tm = top_blob_tm.channel(p);
Mat out0 = top_blob.channel(p);
float bias0 = biasptr ? biasptr[p] : 0.f;
float tmp[4][6];
// tile
for (int i = 0; i < h_tiles; i++)
{
for (int j = 0; j < w_tiles; j++)
{
const float* output0_tm_0 = (const float*)out0_tm + (i * w_tiles + j);
const float* output0_tm_1 = output0_tm_0 + tiles;
const float* output0_tm_2 = output0_tm_0 + tiles * 2;
const float* output0_tm_3 = output0_tm_0 + tiles * 3;
const float* output0_tm_4 = output0_tm_0 + tiles * 4;
const float* output0_tm_5 = output0_tm_0 + tiles * 5;
float* output0 = out0.row(i * 4) + (j * 4);
for (int m = 0; m < 6; m++)
{
float r00 = output0_tm_0[0];
float r01 = output0_tm_1[0];
float r02 = output0_tm_2[0];
float r03 = output0_tm_3[0];
float r04 = output0_tm_4[0];
float r05 = output0_tm_5[0];
float tmp02a = r01 + r02;
float tmp02b = r03 + r04;
float tmp13a = r01 - r02;
float tmp13b = r03 - r04;
tmp[0][m] = r00 + tmp02a + tmp02b;
tmp[1][m] = tmp13a * sq2_d2 + tmp13b * sq2;
tmp[2][m] = tmp02a * 0.5f + tmp02b * 2;
tmp[3][m] = r05 + tmp13a * sq2_d4 + tmp13b * sq2_m2;
output0_tm_0 += tiles * 6;
output0_tm_1 += tiles * 6;
output0_tm_2 += tiles * 6;
output0_tm_3 += tiles * 6;
output0_tm_4 += tiles * 6;
output0_tm_5 += tiles * 6;
}
for (int m = 0; m < 4; m++)
{
float r00 = tmp[m][0];
float r01 = tmp[m][1];
float r02 = tmp[m][2];
float r03 = tmp[m][3];
float r04 = tmp[m][4];
float r05 = tmp[m][5];
float tmp02a = r01 + r02;
float tmp02b = r03 + r04;
float tmp13a = r01 - r02;
float tmp13b = r03 - r04;
float out00 = bias0 + r00 + tmp02a + tmp02b;
float out01 = bias0 + tmp13a * sq2_d2 + tmp13b * sq2;
float out02 = bias0 + tmp02a * 0.5f + tmp02b * 2;
float out03 = bias0 + r05 + tmp13a * sq2_d4 + tmp13b * sq2_m2;
output0[0] = out00;
output0[1] = out01;
output0[2] = out02;
output0[3] = out03;
output0 += outw;
}
}
}
}
}
static void conv3x3s1_winograd23_transform_input_rvv(const Mat& bottom_blob, Mat& bottom_blob_tm, const Option& opt)
{
const int w = bottom_blob.w;
const int h = bottom_blob.h;
const int inch = bottom_blob.c;
const int w_tiles = (w - 2) / 2;
const int h_tiles = (h - 2) / 2;
const int tiles = w_tiles * h_tiles;
// const float itm[4][4] = {
// {1.0f, 0.0f, -1.0f, 0.0f},
// {0.0f, 1.0f, 1.00f, 0.0f},
// {0.0f, -1.0f, 1.00f, 0.0f},
// {0.0f, -1.0f, 0.00f, 1.0f}
// };
// 0 = r00 - r02
// 1 = r01 + r02
// 2 = r02 - r01
// 3 = r03 - r01
#pragma omp parallel for num_threads(opt.num_threads)
for (int q = 0; q < inch; q++)
{
const Mat img0 = bottom_blob.channel(q);
Mat img0_tm = bottom_blob_tm.channel(q);
float tmp[4][4];
// tile
for (int i = 0; i < h_tiles; i++)
{
for (int j = 0; j < w_tiles; j++)
{
const float* r0 = img0.row(i * 2) + (j * 2);
for (int m = 0; m < 4; m++)
{
float r00 = r0[0];
float r01 = r0[1];
float r02 = r0[2];
float r03 = r0[3];
float tmp0m = r00 - r02;
float tmp1m = r01 + r02;
float tmp2m = r02 - r01;
float tmp3m = r03 - r01;
tmp[0][m] = tmp0m;
tmp[1][m] = tmp1m;
tmp[2][m] = tmp2m;
tmp[3][m] = tmp3m;
r0 += w;
}
float* r0_tm_0 = (float*)img0_tm + (i * w_tiles + j);
float* r0_tm_1 = r0_tm_0 + tiles;
float* r0_tm_2 = r0_tm_0 + tiles * 2;
float* r0_tm_3 = r0_tm_0 + tiles * 3;
for (int m = 0; m < 4; m++)
{
float tmp00 = tmp[m][0];
float tmp01 = tmp[m][1];
float tmp02 = tmp[m][2];
float tmp03 = tmp[m][3];
float r0tm0 = tmp00 - tmp02;
float r0tm1 = tmp01 + tmp02;
float r0tm2 = tmp02 - tmp01;
float r0tm3 = tmp03 - tmp01;
r0_tm_0[0] = r0tm0;
r0_tm_1[0] = r0tm1;
r0_tm_2[0] = r0tm2;
r0_tm_3[0] = r0tm3;
r0_tm_0 += tiles * 4;
r0_tm_1 += tiles * 4;
r0_tm_2 += tiles * 4;
r0_tm_3 += tiles * 4;
}
}
}
}
}
static void conv3x3s1_winograd23_transform_output_rvv(const Mat& top_blob_tm, Mat& top_blob, const Mat& bias, const Option& opt)
{
const int outw = top_blob.w;
const int outh = top_blob.h;
const int outch = top_blob.c;
const int w_tiles = outw / 2;
const int h_tiles = outh / 2;
const int tiles = w_tiles * h_tiles;
const float* biasptr = bias;
// const float otm[2][4] = {
// {1.0f, 1.0f, 1.0f, 0.0f},
// {0.0f, 1.0f, -1.0f, 1.0f}
// };
// 0 = r00 + r01 + r02
// 1 = r01 - r02 + r03
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < outch; p++)
{
const Mat out0_tm = top_blob_tm.channel(p);
Mat out0 = top_blob.channel(p);
float bias0 = biasptr ? biasptr[p] : 0.f;
float tmp[2][4];
// tile
for (int i = 0; i < h_tiles; i++)
{
for (int j = 0; j < w_tiles; j++)
{
const float* output0_tm_0 = (const float*)out0_tm + (i * w_tiles + j);
const float* output0_tm_1 = output0_tm_0 + tiles;
const float* output0_tm_2 = output0_tm_0 + tiles * 2;
const float* output0_tm_3 = output0_tm_0 + tiles * 3;
float* output0 = out0.row(i * 2) + (j * 2);
for (int m = 0; m < 4; m++)
{
float out0tm0 = output0_tm_0[0];
float out0tm1 = output0_tm_1[0];
float out0tm2 = output0_tm_2[0];
float out0tm3 = output0_tm_3[0];
float tmp0m = out0tm0 + out0tm1 + out0tm2;
float tmp1m = out0tm1 - out0tm2 + out0tm3;
tmp[0][m] = tmp0m;
tmp[1][m] = tmp1m;
output0_tm_0 += tiles * 4;
output0_tm_1 += tiles * 4;
output0_tm_2 += tiles * 4;
output0_tm_3 += tiles * 4;
}
for (int m = 0; m < 2; m++)
{
float tmp00 = tmp[m][0];
float tmp01 = tmp[m][1];
float tmp02 = tmp[m][2];
float tmp03 = tmp[m][3];
float out00 = bias0 + tmp00 + tmp01 + tmp02;
float out01 = bias0 + tmp01 - tmp02 + tmp03;
output0[0] = out00;
output0[1] = out01;
output0 += outw;
}
}
}
}
}
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