ncnn / src /layer /mips /convolution_sgemm_pack1to4_int8.h
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//
// 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 im2col_sgemm_pack1to4_int8_msa(const Mat& bottom_im2col, Mat& top_blob, const Mat& kernel, const Option& opt)
{
// Mat bottom_im2col(size, maxk, inch, 8u, 8, opt.workspace_allocator);
const int size = bottom_im2col.w;
const int maxk = bottom_im2col.h;
const int inch = bottom_im2col.c;
const int outch = top_blob.c;
// permute
Mat tmp;
if (inch >= 4)
{
if (size >= 2)
tmp.create(2 * maxk, inch / 4 + inch % 4, size / 2 + size % 2, 4u, 4, opt.workspace_allocator);
else
tmp.create(maxk, inch / 4 + inch % 4, size, 4u, 4, opt.workspace_allocator);
}
else
{
if (size >= 2)
tmp.create(2 * maxk, inch, size / 2 + size % 2, 1u, 1, opt.workspace_allocator);
else
tmp.create(maxk, inch, size, 1u, 1, opt.workspace_allocator);
}
{
int remain_size_start = 0;
int 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;
signed char* tmpptr = tmp.channel(i / 2);
int q = 0;
for (; q + 3 < inch; q += 4)
{
const signed char* img0 = (const signed char*)bottom_im2col.channel(q) + i;
const signed char* img1 = (const signed char*)bottom_im2col.channel(q + 1) + i;
const signed char* img2 = (const signed char*)bottom_im2col.channel(q + 2) + i;
const signed char* img3 = (const signed char*)bottom_im2col.channel(q + 3) + i;
for (int k = 0; k < maxk; k++)
{
tmpptr[0] = img0[0];
tmpptr[1] = img1[0];
tmpptr[2] = img2[0];
tmpptr[3] = img3[0];
tmpptr[4] = img0[1];
tmpptr[5] = img1[1];
tmpptr[6] = img2[1];
tmpptr[7] = img3[1];
tmpptr += 8;
img0 += size;
img1 += size;
img2 += size;
img3 += size;
}
}
for (; q < inch; q++)
{
const signed char* img0 = (const signed char*)bottom_im2col.channel(q) + i;
for (int k = 0; k < maxk; k++)
{
tmpptr[0] = img0[0];
tmpptr[1] = img0[1];
tmpptr += 2;
img0 += size;
}
}
}
remain_size_start += nn_size << 1;
#pragma omp parallel for num_threads(opt.num_threads)
for (int i = remain_size_start; i < size; i++)
{
signed char* tmpptr = tmp.channel(i / 2 + i % 2);
int q = 0;
for (; q + 3 < inch; q += 4)
{
const signed char* img0 = (const signed char*)bottom_im2col.channel(q) + i;
const signed char* img1 = (const signed char*)bottom_im2col.channel(q + 1) + i;
const signed char* img2 = (const signed char*)bottom_im2col.channel(q + 2) + i;
const signed char* img3 = (const signed char*)bottom_im2col.channel(q + 3) + i;
for (int k = 0; k < maxk; k++)
{
tmpptr[0] = img0[0];
tmpptr[1] = img1[0];
tmpptr[2] = img2[0];
tmpptr[3] = img3[0];
tmpptr += 4;
img0 += size;
img1 += size;
img2 += size;
img3 += size;
}
}
for (; q < inch; q++)
{
const signed char* img0 = (const signed char*)bottom_im2col.channel(q) + i;
for (int k = 0; k < maxk; k++)
{
tmpptr[0] = img0[0];
tmpptr += 1;
img0 += size;
}
}
}
}
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < outch; p++)
{
int* outptr0 = top_blob.channel(p);
int i = 0;
for (; i + 1 < size; i += 2)
{
const signed char* tmpptr = tmp.channel(i / 2);
const signed char* kptr = kernel.channel(p);
int nn4 = (inch / 4) * maxk;
int nn1 = (inch % 4) * maxk;
v4i32 _sum00 = __msa_fill_w(0);
v4i32 _sum10 = __msa_fill_w(0);
if (nn4 > 0)
{
v4i32 _sum01 = __msa_fill_w(0);
v4i32 _sum02 = __msa_fill_w(0);
v4i32 _sum03 = __msa_fill_w(0);
v4i32 _sum11 = __msa_fill_w(0);
v4i32 _sum12 = __msa_fill_w(0);
v4i32 _sum13 = __msa_fill_w(0);
int j = 0;
for (; j < nn4; j++)
{
__builtin_prefetch(tmpptr + 32);
__builtin_prefetch(kptr + 64);
v16i8 _val = __msa_ld_b(tmpptr, 0);
v8i16 _val01 = (v8i16)__msa_ilvr_b(__msa_clti_s_b(_val, 0), _val);
v8i16 _val0 = (v8i16)__msa_ilvr_d((v2i64)_val01, (v2i64)_val01);
v8i16 _val1 = (v8i16)__msa_ilvl_d((v2i64)_val01, (v2i64)_val01);
v16i8 _w01 = __msa_ld_b(kptr, 0);
v16i8 _extw01 = __msa_clti_s_b(_w01, 0);
v8i16 _w0 = (v8i16)__msa_ilvr_b(_extw01, _w01);
v8i16 _w1 = (v8i16)__msa_ilvl_b(_extw01, _w01);
v8i16 _s00 = __msa_mulv_h(_val0, _w0);
v8i16 _s01 = __msa_mulv_h(_val0, _w1);
v8i16 _s10 = __msa_mulv_h(_val1, _w0);
v8i16 _s11 = __msa_mulv_h(_val1, _w1);
v8i16 _exts00 = __msa_clti_s_h(_s00, 0);
v8i16 _exts01 = __msa_clti_s_h(_s01, 0);
v8i16 _exts10 = __msa_clti_s_h(_s10, 0);
v8i16 _exts11 = __msa_clti_s_h(_s11, 0);
v4i32 _s00l = (v4i32)__msa_ilvr_h(_exts00, _s00);
v4i32 _s00h = (v4i32)__msa_ilvl_h(_exts00, _s00);
v4i32 _s01l = (v4i32)__msa_ilvr_h(_exts01, _s01);
v4i32 _s01h = (v4i32)__msa_ilvl_h(_exts01, _s01);
v4i32 _s10l = (v4i32)__msa_ilvr_h(_exts10, _s10);
v4i32 _s10h = (v4i32)__msa_ilvl_h(_exts10, _s10);
v4i32 _s11l = (v4i32)__msa_ilvr_h(_exts11, _s11);
v4i32 _s11h = (v4i32)__msa_ilvl_h(_exts11, _s11);
_sum00 = __msa_addv_w(_sum00, _s00l);
_sum01 = __msa_addv_w(_sum01, _s00h);
_sum02 = __msa_addv_w(_sum02, _s01l);
_sum03 = __msa_addv_w(_sum03, _s01h);
_sum10 = __msa_addv_w(_sum10, _s10l);
_sum11 = __msa_addv_w(_sum11, _s10h);
_sum12 = __msa_addv_w(_sum12, _s11l);
_sum13 = __msa_addv_w(_sum13, _s11h);
tmpptr += 8;
kptr += 16;
}
// transpose 4x4
{
v4i32 _tmp0, _tmp1, _tmp2, _tmp3;
_tmp0 = __msa_ilvr_w(_sum01, _sum00);
_tmp1 = __msa_ilvr_w(_sum03, _sum02);
_tmp2 = __msa_ilvl_w(_sum01, _sum00);
_tmp3 = __msa_ilvl_w(_sum03, _sum02);
_sum00 = (v4i32)__msa_ilvr_d((v2i64)_tmp1, (v2i64)_tmp0);
_sum01 = (v4i32)__msa_ilvl_d((v2i64)_tmp1, (v2i64)_tmp0);
_sum02 = (v4i32)__msa_ilvr_d((v2i64)_tmp3, (v2i64)_tmp2);
_sum03 = (v4i32)__msa_ilvl_d((v2i64)_tmp3, (v2i64)_tmp2);
}
{
v4i32 _tmp0, _tmp1, _tmp2, _tmp3;
_tmp0 = __msa_ilvr_w(_sum11, _sum10);
_tmp1 = __msa_ilvr_w(_sum13, _sum12);
_tmp2 = __msa_ilvl_w(_sum11, _sum10);
_tmp3 = __msa_ilvl_w(_sum13, _sum12);
_sum10 = (v4i32)__msa_ilvr_d((v2i64)_tmp1, (v2i64)_tmp0);
_sum11 = (v4i32)__msa_ilvl_d((v2i64)_tmp1, (v2i64)_tmp0);
_sum12 = (v4i32)__msa_ilvr_d((v2i64)_tmp3, (v2i64)_tmp2);
_sum13 = (v4i32)__msa_ilvl_d((v2i64)_tmp3, (v2i64)_tmp2);
}
_sum00 = __msa_addv_w(_sum00, _sum01);
_sum02 = __msa_addv_w(_sum02, _sum03);
_sum10 = __msa_addv_w(_sum10, _sum11);
_sum12 = __msa_addv_w(_sum12, _sum13);
_sum00 = __msa_addv_w(_sum00, _sum02);
_sum10 = __msa_addv_w(_sum10, _sum12);
}
int j = 0;
for (; j < nn1; j++)
{
v8i16 _val0 = __msa_fill_h(tmpptr[0]);
v8i16 _val1 = __msa_fill_h(tmpptr[1]);
v8i16 _val = (v8i16)__msa_ilvr_d((v2i64)_val1, (v2i64)_val0);
v16i8 _w = __msa_ld_b(kptr, 0);
v8i16 _w16 = (v8i16)__msa_ilvr_b(__msa_clti_s_b(_w, 0), _w);
_w16 = (v8i16)__msa_ilvr_d((v2i64)_w16, (v2i64)_w16);
v8i16 _s0 = __msa_mulv_h(_val, _w16);
v8i16 _exts0 = __msa_clti_s_h(_s0, 0);
v4i32 _s0l = (v4i32)__msa_ilvr_h(_exts0, _s0);
v4i32 _s0h = (v4i32)__msa_ilvl_h(_exts0, _s0);
_sum00 = __msa_addv_w(_sum00, _s0l);
_sum10 = __msa_addv_w(_sum10, _s0h);
tmpptr += 2;
kptr += 4;
}
__msa_st_w(_sum00, outptr0, 0);
__msa_st_w(_sum10, outptr0 + 4, 0);
outptr0 += 8;
}
for (; i < size; i++)
{
const signed char* tmpptr = tmp.channel(i / 2 + i % 2);
const signed char* kptr = kernel.channel(p);
int nn4 = (inch / 4) * maxk;
int nn1 = (inch % 4) * maxk;
v4i32 _sum0 = __msa_fill_w(0);
if (nn4 > 0)
{
v4i32 _sum1 = __msa_fill_w(0);
v4i32 _sum2 = __msa_fill_w(0);
v4i32 _sum3 = __msa_fill_w(0);
int j = 0;
for (; j < nn4; j++)
{
__builtin_prefetch(tmpptr + 16);
__builtin_prefetch(kptr + 64);
v16i8 _val = __msa_ld_b(tmpptr, 0);
v8i16 _val16 = (v8i16)__msa_ilvr_b(__msa_clti_s_b(_val, 0), _val);
_val16 = (v8i16)__msa_ilvr_d((v2i64)_val16, (v2i64)_val16);
v16i8 _w01 = __msa_ld_b(kptr, 0);
v16i8 _extw01 = __msa_clti_s_b(_w01, 0);
v8i16 _w0 = (v8i16)__msa_ilvr_b(_extw01, _w01);
v8i16 _w1 = (v8i16)__msa_ilvl_b(_extw01, _w01);
v8i16 _s0 = __msa_mulv_h(_val16, _w0);
v8i16 _s1 = __msa_mulv_h(_val16, _w1);
v8i16 _exts0 = __msa_clti_s_h(_s0, 0);
v8i16 _exts1 = __msa_clti_s_h(_s1, 0);
v4i32 _s0l = (v4i32)__msa_ilvr_h(_exts0, _s0);
v4i32 _s0h = (v4i32)__msa_ilvl_h(_exts0, _s0);
v4i32 _s1l = (v4i32)__msa_ilvr_h(_exts1, _s1);
v4i32 _s1h = (v4i32)__msa_ilvl_h(_exts1, _s1);
_sum0 = __msa_addv_w(_sum0, _s0l);
_sum1 = __msa_addv_w(_sum1, _s0h);
_sum2 = __msa_addv_w(_sum2, _s1l);
_sum3 = __msa_addv_w(_sum3, _s1h);
tmpptr += 4;
kptr += 16;
}
// transpose 4x4
{
v4i32 _tmp0, _tmp1, _tmp2, _tmp3;
_tmp0 = __msa_ilvr_w(_sum1, _sum0);
_tmp1 = __msa_ilvr_w(_sum3, _sum2);
_tmp2 = __msa_ilvl_w(_sum1, _sum0);
_tmp3 = __msa_ilvl_w(_sum3, _sum2);
_sum0 = (v4i32)__msa_ilvr_d((v2i64)_tmp1, (v2i64)_tmp0);
_sum1 = (v4i32)__msa_ilvl_d((v2i64)_tmp1, (v2i64)_tmp0);
_sum2 = (v4i32)__msa_ilvr_d((v2i64)_tmp3, (v2i64)_tmp2);
_sum3 = (v4i32)__msa_ilvl_d((v2i64)_tmp3, (v2i64)_tmp2);
}
_sum0 = __msa_addv_w(_sum0, _sum1);
_sum2 = __msa_addv_w(_sum2, _sum3);
_sum0 = __msa_addv_w(_sum0, _sum2);
}
int j = 0;
for (; j < nn1; j++)
{
v8i16 _val = __msa_fill_h(tmpptr[0]);
v16i8 _w = __msa_ld_b(kptr, 0);
v8i16 _w16 = (v8i16)__msa_ilvr_b(__msa_clti_s_b(_w, 0), _w);
v8i16 _s0 = __msa_mulv_h(_val, _w16);
v4i32 _s032 = (v4i32)__msa_ilvr_h(__msa_clti_s_h(_s0, 0), _s0);
_sum0 = __msa_addv_w(_sum0, _s032);
tmpptr += 1;
kptr += 4;
}
__msa_st_w(_sum0, outptr0, 0);
outptr0 += 4;
}
}
}
static void convolution_im2col_sgemm_transform_kernel_pack1to4_int8_msa(const Mat& _kernel, Mat& kernel_tm, int inch, int outch, int kernel_w, int kernel_h)
{
const int maxk = kernel_w * kernel_h;
// interleave
// src = maxk-inch-outch
// dst = 4a-4b-maxk-inch/4a-outch/4b
Mat kernel = _kernel.reshape(maxk, inch, outch);
if (inch >= 4)
kernel_tm.create(16 * maxk, inch / 4 + inch % 4, outch / 4, (size_t)1u);
else
kernel_tm.create(4 * maxk, inch, outch / 4, (size_t)1u);
for (int q = 0; q + 3 < outch; q += 4)
{
signed char* g00 = kernel_tm.channel(q / 4);
int p = 0;
for (; p + 3 < inch; p += 4)
{
for (int k = 0; k < maxk; k++)
{
for (int i = 0; i < 4; i++)
{
for (int j = 0; j < 4; j++)
{
const signed char* k00 = kernel.channel(q + i).row<const signed char>(p + j);
g00[0] = k00[k];
g00++;
}
}
}
}
for (; p < inch; p++)
{
for (int k = 0; k < maxk; k++)
{
for (int i = 0; i < 4; i++)
{
const signed char* k00 = kernel.channel(q + i).row<const signed char>(p);
g00[0] = k00[k];
g00++;
}
}
}
}
}
static void convolution_im2col_sgemm_pack1to4_int8_msa(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, int kernel_w, int kernel_h, int dilation_w, int dilation_h, int stride_w, int stride_h, const Option& opt)
{
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;
// im2col
Mat bottom_im2col(size, maxk, inch, 1u, 1, opt.workspace_allocator);
{
const int gap = w * stride_h - outw * stride_w;
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < inch; p++)
{
const Mat img = bottom_blob.channel(p);
signed char* ptr = bottom_im2col.channel(p);
for (int u = 0; u < kernel_h; u++)
{
for (int v = 0; v < kernel_w; v++)
{
const signed char* sptr = img.row<const signed char>(dilation_h * u) + dilation_w * v;
for (int i = 0; i < outh; i++)
{
int j = 0;
for (; j + 3 < outw; j += 4)
{
ptr[0] = sptr[0];
ptr[1] = sptr[stride_w];
ptr[2] = sptr[stride_w * 2];
ptr[3] = sptr[stride_w * 3];
sptr += stride_w * 4;
ptr += 4;
}
for (; j + 1 < outw; j += 2)
{
ptr[0] = sptr[0];
ptr[1] = sptr[stride_w];
sptr += stride_w * 2;
ptr += 2;
}
for (; j < outw; j++)
{
ptr[0] = sptr[0];
sptr += stride_w;
ptr += 1;
}
sptr += gap;
}
}
}
}
}
im2col_sgemm_pack1to4_int8_msa(bottom_im2col, top_blob, kernel, opt);
}