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| 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; |
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| const int w_tiles = (w - 2) / 4; |
| const int h_tiles = (h - 2) / 4; |
| const int tiles = w_tiles * h_tiles; |
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| const float sq2 = 1.41421356237; |
| const float sq2_d2 = 1.41421356237 / 2; |
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| #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); |
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| float tmp[6][6]; |
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| 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); |
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| 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]; |
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| 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; |
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| 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; |
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| r0 += w; |
| } |
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| 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; |
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| 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]; |
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| 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; |
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| 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; |
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| 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; |
| } |
| } |
| } |
| } |
| } |
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| 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; |
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| const int w_tiles = outw / 4; |
| const int h_tiles = outh / 4; |
| const int tiles = w_tiles * h_tiles; |
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| const float* biasptr = bias; |
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| 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; |
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| #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); |
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| float bias0 = biasptr ? biasptr[p] : 0.f; |
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| float tmp[4][6]; |
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| |
| 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; |
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| float* output0 = out0.row(i * 4) + (j * 4); |
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| 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]; |
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| float tmp02a = r01 + r02; |
| float tmp02b = r03 + r04; |
| float tmp13a = r01 - r02; |
| float tmp13b = r03 - r04; |
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| 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; |
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| 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; |
| } |
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| 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]; |
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| float tmp02a = r01 + r02; |
| float tmp02b = r03 + r04; |
| float tmp13a = r01 - r02; |
| float tmp13b = r03 - r04; |
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| 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; |
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| output0[0] = out00; |
| output0[1] = out01; |
| output0[2] = out02; |
| output0[3] = out03; |
|
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| output0 += outw; |
| } |
| } |
| } |
| } |
| } |
|
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| 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; |
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| const int w_tiles = (w - 2) / 2; |
| const int h_tiles = (h - 2) / 2; |
| const int tiles = w_tiles * h_tiles; |
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| #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); |
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| float tmp[4][4]; |
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| 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); |
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| for (int m = 0; m < 4; m++) |
| { |
| float r00 = r0[0]; |
| float r01 = r0[1]; |
| float r02 = r0[2]; |
| float r03 = r0[3]; |
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| float tmp0m = r00 - r02; |
| float tmp1m = r01 + r02; |
| float tmp2m = r02 - r01; |
| float tmp3m = r03 - r01; |
|
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| tmp[0][m] = tmp0m; |
| tmp[1][m] = tmp1m; |
| tmp[2][m] = tmp2m; |
| tmp[3][m] = tmp3m; |
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| r0 += w; |
| } |
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| 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; |
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| 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]; |
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| float r0tm0 = tmp00 - tmp02; |
| float r0tm1 = tmp01 + tmp02; |
| float r0tm2 = tmp02 - tmp01; |
| float r0tm3 = tmp03 - tmp01; |
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| r0_tm_0[0] = r0tm0; |
| r0_tm_1[0] = r0tm1; |
| r0_tm_2[0] = r0tm2; |
| r0_tm_3[0] = r0tm3; |
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| r0_tm_0 += tiles * 4; |
| r0_tm_1 += tiles * 4; |
| r0_tm_2 += tiles * 4; |
| r0_tm_3 += tiles * 4; |
| } |
| } |
| } |
| } |
| } |
|
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| 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; |
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| const int w_tiles = outw / 2; |
| const int h_tiles = outh / 2; |
| const int tiles = w_tiles * h_tiles; |
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| const float* biasptr = bias; |
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| #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); |
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| float bias0 = biasptr ? biasptr[p] : 0.f; |
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| float tmp[2][4]; |
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| 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; |
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| float* output0 = out0.row(i * 2) + (j * 2); |
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| 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]; |
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| float tmp0m = out0tm0 + out0tm1 + out0tm2; |
| float tmp1m = out0tm1 - out0tm2 + out0tm3; |
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| tmp[0][m] = tmp0m; |
| tmp[1][m] = tmp1m; |
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| output0_tm_0 += tiles * 4; |
| output0_tm_1 += tiles * 4; |
| output0_tm_2 += tiles * 4; |
| output0_tm_3 += tiles * 4; |
| } |
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| 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]; |
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| float out00 = bias0 + tmp00 + tmp01 + tmp02; |
| float out01 = bias0 + tmp01 - tmp02 + tmp03; |
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| output0[0] = out00; |
| output0[1] = out01; |
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| output0 += outw; |
| } |
| } |
| } |
| } |
| } |
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