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| | static void im2col_sgemm_packnto1_rvv(const Mat& bottom_im2col, 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); |
| |
|
| | |
| |
|
| | const int size = bottom_im2col.w; |
| | const int maxk = bottom_im2col.h; |
| | const int inch = bottom_im2col.c; |
| |
|
| | const int outch = top_blob.c; |
| |
|
| | const float* bias = _bias; |
| |
|
| | Mat tmp; |
| | if (size >= 8) |
| | tmp.create(8 * maxk, inch, size / 8 + (size % 8) / 4 + (size % 4) / 2 + size % 2, 4u * packn, packn, opt.workspace_allocator); |
| | else if (size >= 4) |
| | tmp.create(4 * maxk, inch, size / 4 + (size % 4) / 2 + size % 2, 4u * packn, packn, opt.workspace_allocator); |
| | else if (size >= 2) |
| | tmp.create(2 * maxk, inch, size / 2 + size % 2, 4u * packn, packn, opt.workspace_allocator); |
| | else |
| | tmp.create(maxk, inch, size, 4u * packn, packn, opt.workspace_allocator); |
| | { |
| | int remain_size_start = 0; |
| | int nn_size = size >> 3; |
| |
|
| | #pragma omp parallel for num_threads(opt.num_threads) |
| | for (int ii = 0; ii < nn_size; ii++) |
| | { |
| | int i = remain_size_start + ii * 8; |
| |
|
| | float* tmpptr = tmp.channel(i / 8); |
| |
|
| | for (int q = 0; q < inch; q++) |
| | { |
| | const float* img0 = (const float*)bottom_im2col.channel(q) + i * packn; |
| |
|
| | for (int k = 0; k < maxk; k++) |
| | { |
| | #if C906 |
| | for (int l = 0; l < packn; l++) |
| | { |
| | tmpptr[0] = img0[l]; |
| | tmpptr[1] = img0[l + packn]; |
| | tmpptr[2] = img0[l + packn * 2]; |
| | tmpptr[3] = img0[l + packn * 3]; |
| | tmpptr[4] = img0[l + packn * 4]; |
| | tmpptr[5] = img0[l + packn * 5]; |
| | tmpptr[6] = img0[l + packn * 6]; |
| | tmpptr[7] = img0[l + packn * 7]; |
| | tmpptr += 8; |
| | } |
| |
|
| | img0 += size * packn; |
| | #else |
| | vfloat32m1_t _val0 = vle32_v_f32m1(img0, vl); |
| | vfloat32m1_t _val1 = vle32_v_f32m1(img0 + packn, vl); |
| | vfloat32m1_t _val2 = vle32_v_f32m1(img0 + packn * 2, vl); |
| | vfloat32m1_t _val3 = vle32_v_f32m1(img0 + packn * 3, vl); |
| | vfloat32m1_t _val4 = vle32_v_f32m1(img0 + packn * 4, vl); |
| | vfloat32m1_t _val5 = vle32_v_f32m1(img0 + packn * 5, vl); |
| | vfloat32m1_t _val6 = vle32_v_f32m1(img0 + packn * 6, vl); |
| | vfloat32m1_t _val7 = vle32_v_f32m1(img0 + packn * 7, vl); |
| | vsseg8e32_v_f32m1(tmpptr, _val0, _val1, _val2, _val3, _val4, _val5, _val6, _val7, vl); |
| |
|
| | img0 += size * packn; |
| | tmpptr += packn * 8; |
| | #endif |
| | } |
| | } |
| | } |
| |
|
| | remain_size_start += nn_size << 3; |
| | nn_size = (size - remain_size_start) >> 2; |
| |
|
| | #pragma omp parallel for num_threads(opt.num_threads) |
| | for (int ii = 0; ii < nn_size; ii++) |
| | { |
| | int i = remain_size_start + ii * 4; |
| |
|
| | float* tmpptr = tmp.channel(i / 8 + (i % 8) / 4); |
| |
|
| | for (int q = 0; q < inch; q++) |
| | { |
| | const float* img0 = (const float*)bottom_im2col.channel(q) + i * packn; |
| |
|
| | for (int k = 0; k < maxk; k++) |
| | { |
| | #if C906 |
| | for (int l = 0; l < packn; l++) |
| | { |
| | tmpptr[0] = img0[l]; |
| | tmpptr[1] = img0[l + packn]; |
| | tmpptr[2] = img0[l + packn * 2]; |
| | tmpptr[3] = img0[l + packn * 3]; |
| | tmpptr += 4; |
| | } |
| |
|
| | img0 += size * packn; |
| | #else |
| | vfloat32m1_t _val0 = vle32_v_f32m1(img0, vl); |
| | vfloat32m1_t _val1 = vle32_v_f32m1(img0 + packn, vl); |
| | vfloat32m1_t _val2 = vle32_v_f32m1(img0 + packn * 2, vl); |
| | vfloat32m1_t _val3 = vle32_v_f32m1(img0 + packn * 3, vl); |
| | vsseg4e32_v_f32m1(tmpptr, _val0, _val1, _val2, _val3, vl); |
| |
|
| | img0 += size * packn; |
| | tmpptr += packn * 4; |
| | #endif |
| | } |
| | } |
| | } |
| |
|
| | remain_size_start += nn_size << 2; |
| | nn_size = (size - remain_size_start) >> 1; |
| |
|
| | #pragma omp parallel for num_threads(opt.num_threads) |
| | for (int ii = 0; ii < nn_size; ii++) |
| | { |
| | int i = remain_size_start + ii * 2; |
| |
|
| | float* tmpptr = tmp.channel(i / 8 + (i % 8) / 4 + (i % 4) / 2); |
| |
|
| | for (int q = 0; q < inch; q++) |
| | { |
| | const float* img0 = (const float*)bottom_im2col.channel(q) + i * packn; |
| |
|
| | for (int k = 0; k < maxk; k++) |
| | { |
| | #if C906 |
| | for (int l = 0; l < packn; l++) |
| | { |
| | tmpptr[0] = img0[l]; |
| | tmpptr[1] = img0[l + packn]; |
| | tmpptr += 2; |
| | } |
| |
|
| | img0 += size * packn; |
| | #else |
| | vfloat32m1_t _val0 = vle32_v_f32m1(img0, vl); |
| | vfloat32m1_t _val1 = vle32_v_f32m1(img0 + packn, vl); |
| | vsseg2e32_v_f32m1(tmpptr, _val0, _val1, vl); |
| |
|
| | img0 += size * packn; |
| | tmpptr += packn * 2; |
| | #endif |
| | } |
| | } |
| | } |
| |
|
| | remain_size_start += nn_size << 1; |
| |
|
| | #pragma omp parallel for num_threads(opt.num_threads) |
| | for (int i = remain_size_start; i < size; i++) |
| | { |
| | float* tmpptr = tmp.channel(i / 8 + (i % 8) / 4 + (i % 4) / 2 + i % 2); |
| |
|
| | for (int q = 0; q < inch; q++) |
| | { |
| | const float* img0 = (const float*)bottom_im2col.channel(q) + i * packn; |
| |
|
| | for (int k = 0; k < maxk; k++) |
| | { |
| | vfloat32m1_t _val = vle32_v_f32m1(img0, vl); |
| | vse32_v_f32m1(tmpptr, _val, vl); |
| |
|
| | img0 += size * packn; |
| | tmpptr += packn; |
| | } |
| | } |
| | } |
| | } |
| |
|
| | int nn_outch = outch / packn; |
| | int remain_outch_start = nn_outch * packn; |
| |
|
| | #ifdef __clang__ |
| | |
| | float* _zero_tmp = new float[packn](); |
| | for (int _zero_clean_idx = 0; _zero_clean_idx < packn; _zero_clean_idx++) |
| | { |
| | _zero_tmp[_zero_clean_idx] = 0.f; |
| | } |
| | #endif |
| | #pragma omp parallel for num_threads(opt.num_threads) |
| | for (int pp = 0; pp < nn_outch; pp++) |
| | { |
| | int p = pp * packn; |
| |
|
| | float* outptr0 = top_blob.channel(p); |
| |
|
| | #ifdef __clang__ |
| | const float* zeros = _zero_tmp; |
| | #else |
| | const float zeros[packn] = {0.f}; |
| | #endif |
| | const float* biasptr = bias ? bias + p : zeros; |
| |
|
| | int i = 0; |
| | for (; i + 7 < size; i += 8) |
| | { |
| | const float* tmpptr = tmp.channel(i / 8); |
| | const float* kptr0 = kernel.channel(p / packn); |
| |
|
| | int nn = inch * maxk * packn; |
| |
|
| | vfloat32m1_t _sum0 = vle32_v_f32m1(biasptr, vl); |
| | vfloat32m1_t _sum1 = vle32_v_f32m1(biasptr, vl); |
| | vfloat32m1_t _sum2 = vle32_v_f32m1(biasptr, vl); |
| | vfloat32m1_t _sum3 = vle32_v_f32m1(biasptr, vl); |
| | vfloat32m1_t _sum4 = vle32_v_f32m1(biasptr, vl); |
| | vfloat32m1_t _sum5 = vle32_v_f32m1(biasptr, vl); |
| | vfloat32m1_t _sum6 = vle32_v_f32m1(biasptr, vl); |
| | vfloat32m1_t _sum7 = vle32_v_f32m1(biasptr, vl); |
| |
|
| | for (int j = 0; j < nn; j++) |
| | { |
| | float val0 = *tmpptr++; |
| | float val1 = *tmpptr++; |
| | float val2 = *tmpptr++; |
| | float val3 = *tmpptr++; |
| | float val4 = *tmpptr++; |
| | float val5 = *tmpptr++; |
| | float val6 = *tmpptr++; |
| | float val7 = *tmpptr++; |
| | vfloat32m1_t _w0 = vle32_v_f32m1(kptr0, vl); |
| | _sum0 = vfmacc_vf_f32m1(_sum0, val0, _w0, vl); |
| | _sum1 = vfmacc_vf_f32m1(_sum1, val1, _w0, vl); |
| | _sum2 = vfmacc_vf_f32m1(_sum2, val2, _w0, vl); |
| | _sum3 = vfmacc_vf_f32m1(_sum3, val3, _w0, vl); |
| | _sum4 = vfmacc_vf_f32m1(_sum4, val4, _w0, vl); |
| | _sum5 = vfmacc_vf_f32m1(_sum5, val5, _w0, vl); |
| | _sum6 = vfmacc_vf_f32m1(_sum6, val6, _w0, vl); |
| | _sum7 = vfmacc_vf_f32m1(_sum7, val7, _w0, vl); |
| |
|
| | kptr0 += packn; |
| | } |
| |
|
| | #if C906 |
| | vsse32_v_f32m1(outptr0, top_blob.cstep * sizeof(float), _sum0, vl); |
| | vsse32_v_f32m1(outptr0 + 1, top_blob.cstep * sizeof(float), _sum1, vl); |
| | vsse32_v_f32m1(outptr0 + 2, top_blob.cstep * sizeof(float), _sum2, vl); |
| | vsse32_v_f32m1(outptr0 + 3, top_blob.cstep * sizeof(float), _sum3, vl); |
| | vsse32_v_f32m1(outptr0 + 4, top_blob.cstep * sizeof(float), _sum4, vl); |
| | vsse32_v_f32m1(outptr0 + 5, top_blob.cstep * sizeof(float), _sum5, vl); |
| | vsse32_v_f32m1(outptr0 + 6, top_blob.cstep * sizeof(float), _sum6, vl); |
| | vsse32_v_f32m1(outptr0 + 7, top_blob.cstep * sizeof(float), _sum7, vl); |
| | #else |
| | vssseg8e32_v_f32m1(outptr0, top_blob.cstep * sizeof(float), _sum0, _sum1, _sum2, _sum3, _sum4, _sum5, _sum6, _sum7, vl); |
| | #endif |
| | outptr0 += 8; |
| | } |
| | for (; i + 3 < size; i += 4) |
| | { |
| | const float* tmpptr = tmp.channel(i / 8 + (i % 8) / 4); |
| | const float* kptr0 = kernel.channel(p / packn); |
| |
|
| | int nn = inch * maxk * packn; |
| |
|
| | vfloat32m1_t _sum0 = vle32_v_f32m1(biasptr, vl); |
| | vfloat32m1_t _sum1 = vle32_v_f32m1(biasptr, vl); |
| | vfloat32m1_t _sum2 = vle32_v_f32m1(biasptr, vl); |
| | vfloat32m1_t _sum3 = vle32_v_f32m1(biasptr, vl); |
| |
|
| | for (int j = 0; j < nn; j++) |
| | { |
| | float val0 = *tmpptr++; |
| | float val1 = *tmpptr++; |
| | float val2 = *tmpptr++; |
| | float val3 = *tmpptr++; |
| | vfloat32m1_t _w0 = vle32_v_f32m1(kptr0, vl); |
| | _sum0 = vfmacc_vf_f32m1(_sum0, val0, _w0, vl); |
| | _sum1 = vfmacc_vf_f32m1(_sum1, val1, _w0, vl); |
| | _sum2 = vfmacc_vf_f32m1(_sum2, val2, _w0, vl); |
| | _sum3 = vfmacc_vf_f32m1(_sum3, val3, _w0, vl); |
| |
|
| | kptr0 += packn; |
| | } |
| |
|
| | #if C906 |
| | vsse32_v_f32m1(outptr0, top_blob.cstep * sizeof(float), _sum0, vl); |
| | vsse32_v_f32m1(outptr0 + 1, top_blob.cstep * sizeof(float), _sum1, vl); |
| | vsse32_v_f32m1(outptr0 + 2, top_blob.cstep * sizeof(float), _sum2, vl); |
| | vsse32_v_f32m1(outptr0 + 3, top_blob.cstep * sizeof(float), _sum3, vl); |
| | #else |
| | vssseg4e32_v_f32m1(outptr0, top_blob.cstep * sizeof(float), _sum0, _sum1, _sum2, _sum3, vl); |
| | #endif |
| | outptr0 += 4; |
| | } |
| | for (; i + 1 < size; i += 2) |
| | { |
| | const float* tmpptr = tmp.channel(i / 8 + (i % 8) / 4 + (i % 4) / 2); |
| | const float* kptr0 = kernel.channel(p / packn); |
| |
|
| | int nn = inch * maxk * packn; |
| |
|
| | vfloat32m1_t _sum0 = vle32_v_f32m1(biasptr, vl); |
| | vfloat32m1_t _sum1 = vle32_v_f32m1(biasptr, vl); |
| |
|
| | for (int j = 0; j < nn; j++) |
| | { |
| | float val0 = *tmpptr++; |
| | float val1 = *tmpptr++; |
| | vfloat32m1_t _w0 = vle32_v_f32m1(kptr0, vl); |
| | _sum0 = vfmacc_vf_f32m1(_sum0, val0, _w0, vl); |
| | _sum1 = vfmacc_vf_f32m1(_sum1, val1, _w0, vl); |
| |
|
| | kptr0 += packn; |
| | } |
| |
|
| | #if C906 |
| | vsse32_v_f32m1(outptr0, top_blob.cstep * sizeof(float), _sum0, vl); |
| | vsse32_v_f32m1(outptr0 + 1, top_blob.cstep * sizeof(float), _sum1, vl); |
| | #else |
| | vssseg2e32_v_f32m1(outptr0, top_blob.cstep * sizeof(float), _sum0, _sum1, vl); |
| | #endif |
| | outptr0 += 2; |
| | } |
| | for (; i < size; i++) |
| | { |
| | const float* tmpptr = tmp.channel(i / 8 + (i % 8) / 4 + (i % 4) / 2 + i % 2); |
| | const float* kptr0 = kernel.channel(p / packn); |
| |
|
| | int nn = inch * maxk * packn; |
| |
|
| | vfloat32m1_t _sum = vle32_v_f32m1(biasptr, vl); |
| |
|
| | for (int j = 0; j < nn; j++) |
| | { |
| | float val = *tmpptr++; |
| | vfloat32m1_t _w0 = vle32_v_f32m1(kptr0, vl); |
| | _sum = vfmacc_vf_f32m1(_sum, val, _w0, vl); |
| |
|
| | kptr0 += packn; |
| | } |
| |
|
| | vsse32_v_f32m1(outptr0, top_blob.cstep * sizeof(float), _sum, vl); |
| |
|
| | outptr0 += 1; |
| | } |
| | } |
| | #ifdef __clang__ |
| | delete[] _zero_tmp; |
| | #endif |
| |
|
| | #pragma omp parallel for num_threads(opt.num_threads) |
| | for (int p = remain_outch_start; p < outch; p++) |
| | { |
| | float* outptr0 = top_blob.channel(p); |
| |
|
| | const float bias0 = bias ? bias[p] : 0.f; |
| |
|
| | int i = 0; |
| | for (; i + 7 < size; i += 8) |
| | { |
| | const float* tmpptr = tmp.channel(i / 8); |
| | const float* kptr0 = kernel.channel(p / packn + p % packn); |
| |
|
| | int nn = inch * maxk; |
| |
|
| | float sum0 = bias0; |
| | float sum1 = bias0; |
| | float sum2 = bias0; |
| | float sum3 = bias0; |
| | float sum4 = bias0; |
| | float sum5 = bias0; |
| | float sum6 = bias0; |
| | float sum7 = bias0; |
| |
|
| | vfloat32m1_t _sum0 = vfmv_v_f_f32m1(0.f, vl); |
| | vfloat32m1_t _sum1 = vfmv_v_f_f32m1(0.f, vl); |
| | vfloat32m1_t _sum2 = vfmv_v_f_f32m1(0.f, vl); |
| | vfloat32m1_t _sum3 = vfmv_v_f_f32m1(0.f, vl); |
| | vfloat32m1_t _sum4 = vfmv_v_f_f32m1(0.f, vl); |
| | vfloat32m1_t _sum5 = vfmv_v_f_f32m1(0.f, vl); |
| | vfloat32m1_t _sum6 = vfmv_v_f_f32m1(0.f, vl); |
| | vfloat32m1_t _sum7 = vfmv_v_f_f32m1(0.f, vl); |
| |
|
| | for (int j = 0; j < nn; j++) |
| | { |
| | vfloat32m1_t _val0; |
| | vfloat32m1_t _val1; |
| | vfloat32m1_t _val2; |
| | vfloat32m1_t _val3; |
| | vfloat32m1_t _val4; |
| | vfloat32m1_t _val5; |
| | vfloat32m1_t _val6; |
| | vfloat32m1_t _val7; |
| | vlseg8e32_v_f32m1(&_val0, &_val1, &_val2, &_val3, &_val4, &_val5, &_val6, &_val7, tmpptr, vl); |
| | vfloat32m1_t _w0 = vle32_v_f32m1(kptr0, vl); |
| | _sum0 = vfmacc_vv_f32m1(_sum0, _val0, _w0, vl); |
| | _sum1 = vfmacc_vv_f32m1(_sum1, _val1, _w0, vl); |
| | _sum2 = vfmacc_vv_f32m1(_sum2, _val2, _w0, vl); |
| | _sum3 = vfmacc_vv_f32m1(_sum3, _val3, _w0, vl); |
| | _sum4 = vfmacc_vv_f32m1(_sum4, _val4, _w0, vl); |
| | _sum5 = vfmacc_vv_f32m1(_sum5, _val5, _w0, vl); |
| | _sum6 = vfmacc_vv_f32m1(_sum6, _val6, _w0, vl); |
| | _sum7 = vfmacc_vv_f32m1(_sum7, _val7, _w0, vl); |
| | tmpptr += packn * 8; |
| | kptr0 += packn; |
| | } |
| |
|
| | #if C906 |
| | |
| | std::vector<float> ss0(packn); |
| | std::vector<float> ss1(packn); |
| | std::vector<float> ss2(packn); |
| | std::vector<float> ss3(packn); |
| | std::vector<float> ss4(packn); |
| | std::vector<float> ss5(packn); |
| | std::vector<float> ss6(packn); |
| | std::vector<float> ss7(packn); |
| | vse32_v_f32m1((float*)ss0.data(), _sum0, vl); |
| | vse32_v_f32m1((float*)ss1.data(), _sum1, vl); |
| | vse32_v_f32m1((float*)ss2.data(), _sum2, vl); |
| | vse32_v_f32m1((float*)ss3.data(), _sum3, vl); |
| | vse32_v_f32m1((float*)ss4.data(), _sum4, vl); |
| | vse32_v_f32m1((float*)ss5.data(), _sum5, vl); |
| | vse32_v_f32m1((float*)ss6.data(), _sum6, vl); |
| | vse32_v_f32m1((float*)ss7.data(), _sum7, vl); |
| | for (int i = 0; i < packn; i++) |
| | { |
| | sum0 += ss0[i]; |
| | sum1 += ss1[i]; |
| | sum2 += ss2[i]; |
| | sum3 += ss3[i]; |
| | sum4 += ss4[i]; |
| | sum5 += ss5[i]; |
| | sum6 += ss6[i]; |
| | sum7 += ss7[i]; |
| | } |
| | #else |
| | sum0 = vfmv_f_s_f32m1_f32(vfredusum_vs_f32m1_f32m1(vfloat32m1_t(), _sum0, vfmv_s_f_f32m1(vfloat32m1_t(), sum0, vl), vl)); |
| | sum1 = vfmv_f_s_f32m1_f32(vfredusum_vs_f32m1_f32m1(vfloat32m1_t(), _sum1, vfmv_s_f_f32m1(vfloat32m1_t(), sum1, vl), vl)); |
| | sum2 = vfmv_f_s_f32m1_f32(vfredusum_vs_f32m1_f32m1(vfloat32m1_t(), _sum2, vfmv_s_f_f32m1(vfloat32m1_t(), sum2, vl), vl)); |
| | sum3 = vfmv_f_s_f32m1_f32(vfredusum_vs_f32m1_f32m1(vfloat32m1_t(), _sum3, vfmv_s_f_f32m1(vfloat32m1_t(), sum3, vl), vl)); |
| | sum4 = vfmv_f_s_f32m1_f32(vfredusum_vs_f32m1_f32m1(vfloat32m1_t(), _sum4, vfmv_s_f_f32m1(vfloat32m1_t(), sum4, vl), vl)); |
| | sum5 = vfmv_f_s_f32m1_f32(vfredusum_vs_f32m1_f32m1(vfloat32m1_t(), _sum5, vfmv_s_f_f32m1(vfloat32m1_t(), sum5, vl), vl)); |
| | sum6 = vfmv_f_s_f32m1_f32(vfredusum_vs_f32m1_f32m1(vfloat32m1_t(), _sum6, vfmv_s_f_f32m1(vfloat32m1_t(), sum6, vl), vl)); |
| | sum7 = vfmv_f_s_f32m1_f32(vfredusum_vs_f32m1_f32m1(vfloat32m1_t(), _sum7, vfmv_s_f_f32m1(vfloat32m1_t(), sum7, vl), vl)); |
| | #endif |
| |
|
| | outptr0[0] = sum0; |
| | outptr0[1] = sum1; |
| | outptr0[2] = sum2; |
| | outptr0[3] = sum3; |
| | outptr0[4] = sum4; |
| | outptr0[5] = sum5; |
| | outptr0[6] = sum6; |
| | outptr0[7] = sum7; |
| |
|
| | outptr0 += 8; |
| | } |
| | for (; i + 3 < size; i += 4) |
| | { |
| | const float* tmpptr = tmp.channel(i / 8 + (i % 8) / 4); |
| | const float* kptr0 = kernel.channel(p / packn + p % packn); |
| |
|
| | int nn = inch * maxk; |
| |
|
| | float sum0 = bias0; |
| | float sum1 = bias0; |
| | float sum2 = bias0; |
| | float sum3 = bias0; |
| |
|
| | vfloat32m1_t _sum0 = vfmv_v_f_f32m1(0.f, vl); |
| | vfloat32m1_t _sum1 = vfmv_v_f_f32m1(0.f, vl); |
| | vfloat32m1_t _sum2 = vfmv_v_f_f32m1(0.f, vl); |
| | vfloat32m1_t _sum3 = vfmv_v_f_f32m1(0.f, vl); |
| |
|
| | for (int j = 0; j < nn; j++) |
| | { |
| | vfloat32m1_t _val0; |
| | vfloat32m1_t _val1; |
| | vfloat32m1_t _val2; |
| | vfloat32m1_t _val3; |
| | vlseg4e32_v_f32m1(&_val0, &_val1, &_val2, &_val3, tmpptr, vl); |
| | vfloat32m1_t _w0 = vle32_v_f32m1(kptr0, vl); |
| | _sum0 = vfmacc_vv_f32m1(_sum0, _val0, _w0, vl); |
| | _sum1 = vfmacc_vv_f32m1(_sum1, _val1, _w0, vl); |
| | _sum2 = vfmacc_vv_f32m1(_sum2, _val2, _w0, vl); |
| | _sum3 = vfmacc_vv_f32m1(_sum3, _val3, _w0, vl); |
| | tmpptr += packn * 4; |
| | kptr0 += packn; |
| | } |
| |
|
| | #if C906 |
| | |
| | std::vector<float> ss0(packn); |
| | std::vector<float> ss1(packn); |
| | std::vector<float> ss2(packn); |
| | std::vector<float> ss3(packn); |
| | vse32_v_f32m1((float*)ss0.data(), _sum0, vl); |
| | vse32_v_f32m1((float*)ss1.data(), _sum1, vl); |
| | vse32_v_f32m1((float*)ss2.data(), _sum2, vl); |
| | vse32_v_f32m1((float*)ss3.data(), _sum3, vl); |
| | for (int i = 0; i < packn; i++) |
| | { |
| | sum0 += ss0[i]; |
| | sum1 += ss1[i]; |
| | sum2 += ss2[i]; |
| | sum3 += ss3[i]; |
| | } |
| | #else |
| | sum0 = vfmv_f_s_f32m1_f32(vfredusum_vs_f32m1_f32m1(vfloat32m1_t(), _sum0, vfmv_s_f_f32m1(vfloat32m1_t(), sum0, vl), vl)); |
| | sum1 = vfmv_f_s_f32m1_f32(vfredusum_vs_f32m1_f32m1(vfloat32m1_t(), _sum1, vfmv_s_f_f32m1(vfloat32m1_t(), sum1, vl), vl)); |
| | sum2 = vfmv_f_s_f32m1_f32(vfredusum_vs_f32m1_f32m1(vfloat32m1_t(), _sum2, vfmv_s_f_f32m1(vfloat32m1_t(), sum2, vl), vl)); |
| | sum3 = vfmv_f_s_f32m1_f32(vfredusum_vs_f32m1_f32m1(vfloat32m1_t(), _sum3, vfmv_s_f_f32m1(vfloat32m1_t(), sum3, vl), vl)); |
| | #endif |
| |
|
| | outptr0[0] = sum0; |
| | outptr0[1] = sum1; |
| | outptr0[2] = sum2; |
| | outptr0[3] = sum3; |
| |
|
| | outptr0 += 4; |
| | } |
| | for (; i + 1 < size; i += 2) |
| | { |
| | const float* tmpptr = tmp.channel(i / 8 + (i % 8) / 4 + (i % 4) / 2); |
| | const float* kptr0 = kernel.channel(p / packn + p % packn); |
| |
|
| | int nn = inch * maxk; |
| |
|
| | float sum0 = bias0; |
| | float sum1 = bias0; |
| |
|
| | vfloat32m1_t _sum0 = vfmv_v_f_f32m1(0.f, vl); |
| | vfloat32m1_t _sum1 = vfmv_v_f_f32m1(0.f, vl); |
| |
|
| | for (int j = 0; j < nn; j++) |
| | { |
| | vfloat32m1_t _val0; |
| | vfloat32m1_t _val1; |
| | vlseg2e32_v_f32m1(&_val0, &_val1, tmpptr, vl); |
| | vfloat32m1_t _w0 = vle32_v_f32m1(kptr0, vl); |
| | _sum0 = vfmacc_vv_f32m1(_sum0, _val0, _w0, vl); |
| | _sum1 = vfmacc_vv_f32m1(_sum1, _val1, _w0, vl); |
| | tmpptr += packn * 2; |
| | kptr0 += packn; |
| | } |
| |
|
| | #if C906 |
| | |
| | std::vector<float> ss0(packn); |
| | std::vector<float> ss1(packn); |
| | vse32_v_f32m1((float*)ss0.data(), _sum0, vl); |
| | vse32_v_f32m1((float*)ss1.data(), _sum1, vl); |
| | for (int i = 0; i < packn; i++) |
| | { |
| | sum0 += ss0[i]; |
| | sum1 += ss1[i]; |
| | } |
| | #else |
| | sum0 = vfmv_f_s_f32m1_f32(vfredusum_vs_f32m1_f32m1(vfloat32m1_t(), _sum0, vfmv_s_f_f32m1(vfloat32m1_t(), sum0, vl), vl)); |
| | sum1 = vfmv_f_s_f32m1_f32(vfredusum_vs_f32m1_f32m1(vfloat32m1_t(), _sum1, vfmv_s_f_f32m1(vfloat32m1_t(), sum1, vl), vl)); |
| | #endif |
| |
|
| | outptr0[0] = sum0; |
| | outptr0[1] = sum1; |
| |
|
| | outptr0 += 2; |
| | } |
| | for (; i < size; i++) |
| | { |
| | const float* tmpptr = tmp.channel(i / 8 + (i % 8) / 4 + (i % 4) / 2 + i % 2); |
| | const float* kptr0 = kernel.channel(p / packn + p % packn); |
| |
|
| | int nn = inch * maxk; |
| |
|
| | float sum0 = bias0; |
| |
|
| | vfloat32m1_t _sum0 = vfmv_v_f_f32m1(0.f, vl); |
| |
|
| | for (int j = 0; j < nn; j++) |
| | { |
| | vfloat32m1_t _val0 = vle32_v_f32m1(tmpptr, vl); |
| | vfloat32m1_t _w0 = vle32_v_f32m1(kptr0, vl); |
| | _sum0 = vfmacc_vv_f32m1(_sum0, _val0, _w0, vl); |
| | tmpptr += packn; |
| | kptr0 += packn; |
| | } |
| |
|
| | #if C906 |
| | |
| | std::vector<float> ss0(packn); |
| | vse32_v_f32m1((float*)ss0.data(), _sum0, vl); |
| | for (int i = 0; i < packn; i++) |
| | { |
| | sum0 += ss0[i]; |
| | } |
| | #else |
| | sum0 = vfmv_f_s_f32m1_f32(vfredusum_vs_f32m1_f32m1(vfloat32m1_t(), _sum0, vfmv_s_f_f32m1(vfloat32m1_t(), sum0, vl), vl)); |
| | #endif |
| |
|
| | outptr0[0] = sum0; |
| |
|
| | outptr0 += 1; |
| | } |
| | } |
| | } |
| |
|
| | static void convolution_im2col_sgemm_transform_kernel_packnto1_rvv(const Mat& _kernel, Mat& kernel_tm, int inch, int outch, int kernel_w, int kernel_h) |
| | { |
| | const int packn = csrr_vlenb() / 4; |
| |
|
| | const int maxk = kernel_w * kernel_h; |
| |
|
| | |
| | |
| | |
| | Mat kernel = _kernel.reshape(maxk, inch, outch); |
| | kernel_tm.create(packn * packn * maxk, inch / packn, outch / packn + outch % packn); |
| |
|
| | int q = 0; |
| | for (; q + (packn - 1) < outch; q += packn) |
| | { |
| | float* g00 = kernel_tm.channel(q / packn); |
| |
|
| | for (int p = 0; p + (packn - 1) < inch; p += packn) |
| | { |
| | for (int k = 0; k < maxk; k++) |
| | { |
| | for (int i = 0; i < packn; i++) |
| | { |
| | for (int j = 0; j < packn; j++) |
| | { |
| | const float* k00 = kernel.channel(q + j).row(p + i); |
| |
|
| | g00[0] = k00[k]; |
| |
|
| | g00++; |
| | } |
| | } |
| | } |
| | } |
| | } |
| | for (; q < outch; q++) |
| | { |
| | const Mat k0 = kernel.channel(q); |
| |
|
| | float* g00 = kernel_tm.channel(q / packn + q % packn); |
| |
|
| | for (int p = 0; p + (packn - 1) < inch; p += packn) |
| | { |
| | for (int k = 0; k < maxk; k++) |
| | { |
| | for (int j = 0; j < packn; j++) |
| | { |
| | const float* k00 = k0.row(p + j); |
| |
|
| | g00[0] = k00[k]; |
| |
|
| | g00++; |
| | } |
| | } |
| | } |
| | } |
| | } |
| |
|
| | static void convolution_im2col_sgemm_packnto1_rvv(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Mat& _bias, int kernel_w, int kernel_h, int dilation_w, int dilation_h, int stride_w, int stride_h, const Option& opt) |
| | { |
| | const int packn = csrr_vlenb() / 4; |
| | const size_t vl = vsetvl_e32m1(packn); |
| |
|
| | int w = bottom_blob.w; |
| | int inch = bottom_blob.c; |
| |
|
| | int outw = top_blob.w; |
| | int outh = top_blob.h; |
| | const int size = outw * outh; |
| |
|
| | const int maxk = kernel_w * kernel_h; |
| |
|
| | |
| | Mat bottom_im2col(size, maxk, inch, 4u * packn, packn, opt.workspace_allocator); |
| | { |
| | const int gap = (w * stride_h - outw * stride_w) * packn; |
| |
|
| | #pragma omp parallel for num_threads(opt.num_threads) |
| | for (int p = 0; p < inch; p++) |
| | { |
| | const Mat img = bottom_blob.channel(p); |
| | float* ptr = bottom_im2col.channel(p); |
| |
|
| | for (int u = 0; u < kernel_h; u++) |
| | { |
| | for (int v = 0; v < kernel_w; v++) |
| | { |
| | const float* sptr = img.row(dilation_h * u) + dilation_w * v * packn; |
| |
|
| | for (int i = 0; i < outh; i++) |
| | { |
| | int j = 0; |
| | for (; j < outw; j++) |
| | { |
| | vfloat32m1_t _val = vle32_v_f32m1(sptr, vl); |
| | vse32_v_f32m1(ptr, _val, vl); |
| |
|
| | sptr += stride_w * packn; |
| | ptr += packn; |
| | } |
| |
|
| | sptr += gap; |
| | } |
| | } |
| | } |
| | } |
| | } |
| |
|
| | im2col_sgemm_packnto1_rvv(bottom_im2col, top_blob, kernel, _bias, opt); |
| | } |
| |
|