// Tencent is pleased to support the open source community by making ncnn available. // // 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. #if NCNN_RUNTIME_CPU && NCNN_MMI && !__mips_msa && !__mips_loongson_mmi void conv3x3s1_winograd43_transform_kernel_int8_loongson_mmi(const Mat& kernel, Mat& kernel_tm_packed, int inch, int outch, const Option& opt); #endif static void conv3x3s1_winograd43_transform_kernel_int8_msa(const Mat& kernel, Mat& kernel_tm_packed, int inch, int outch, const Option& opt) { #if NCNN_RUNTIME_CPU && NCNN_MMI && !__mips_msa && !__mips_loongson_mmi if (ncnn::cpu_support_loongson_mmi()) { conv3x3s1_winograd43_transform_kernel_int8_loongson_mmi(kernel, kernel_tm_packed, inch, outch, opt); return; } #endif // winograd43 transform kernel Mat kernel_tm(6 * 6, inch, outch, (size_t)2u); const short ktm[6][3] = { {6, 0, 0}, {-4, -4, -4}, {-4, 4, -4}, {1, 2, 4}, {1, -2, 4}, {0, 0, 6} }; #pragma omp parallel for num_threads(opt.num_threads) for (int p = 0; p < outch; p++) { for (int q = 0; q < inch; q++) { const signed char* kernel0 = (const signed char*)kernel + p * inch * 9 + q * 9; short* kernel_tm0 = kernel_tm.channel(p).row(q); // transform kernel const signed char* k0 = kernel0; const signed char* k1 = kernel0 + 3; const signed char* k2 = kernel0 + 6; // h short tmp[6][3]; for (int i = 0; i < 6; i++) { tmp[i][0] = k0[0] * ktm[i][0] + k0[1] * ktm[i][1] + k0[2] * ktm[i][2]; tmp[i][1] = k1[0] * ktm[i][0] + k1[1] * ktm[i][1] + k1[2] * ktm[i][2]; tmp[i][2] = k2[0] * ktm[i][0] + k2[1] * ktm[i][1] + k2[2] * ktm[i][2]; } // U for (int j = 0; j < 6; j++) { short* tmpp = &tmp[j][0]; for (int i = 0; i < 6; i++) { kernel_tm0[j * 6 + i] = tmpp[0] * ktm[i][0] + tmpp[1] * ktm[i][1] + tmpp[2] * ktm[i][2]; } } } } // interleave // src = 36-inch-outch // dst = 2b-inch-36-outch/2b #if __mips_msa if (outch >= 4) { if (inch >= 4) kernel_tm_packed.create(inch / 4 + inch % 4, 36, outch / 4 + outch % 4, (size_t)2u * 16, 16); else kernel_tm_packed.create(inch, 36, outch / 4 + outch % 4, (size_t)2u * 4, 4); } #else // __mips_msa if (outch >= 2) { #if __mips_loongson_mmi if (inch >= 4) kernel_tm_packed.create(inch / 4 + inch % 4, 36, outch / 2 + outch % 2, (size_t)2u * 8, 8); else #endif // __mips_loongson_mmi { kernel_tm_packed.create(inch, 36, outch / 2 + outch % 2, (size_t)2u * 2, 2); } } #endif // __mips_msa else { #if __mips_msa || __mips_loongson_mmi if (inch >= 4) kernel_tm_packed.create(inch / 4 + inch % 4, 36, outch, (size_t)2u * 4, 4); else #endif // __mips_msa || __mips_loongson_mmi { kernel_tm_packed.create(inch, 36, outch, (size_t)2u, 1); } } int p = 0; #if __mips_msa for (; p + 3 < outch; p += 4) { const Mat k0 = kernel_tm.channel(p); const Mat k1 = kernel_tm.channel(p + 1); const Mat k2 = kernel_tm.channel(p + 2); const Mat k3 = kernel_tm.channel(p + 3); Mat g0 = kernel_tm_packed.channel(p / 4); for (int k = 0; k < 36; k++) { short* g00 = g0.row(k); int q = 0; for (; q + 3 < inch; q += 4) { g00[0] = k0.row(q)[k]; g00[1] = k0.row(q + 1)[k]; g00[2] = k0.row(q + 2)[k]; g00[3] = k0.row(q + 3)[k]; g00[4] = k1.row(q)[k]; g00[5] = k1.row(q + 1)[k]; g00[6] = k1.row(q + 2)[k]; g00[7] = k1.row(q + 3)[k]; g00[8] = k2.row(q)[k]; g00[9] = k2.row(q + 1)[k]; g00[10] = k2.row(q + 2)[k]; g00[11] = k2.row(q + 3)[k]; g00[12] = k3.row(q)[k]; g00[13] = k3.row(q + 1)[k]; g00[14] = k3.row(q + 2)[k]; g00[15] = k3.row(q + 3)[k]; g00 += 16; } for (; q < inch; q++) { g00[0] = k0.row(q)[k]; g00[1] = k1.row(q)[k]; g00[2] = k2.row(q)[k]; g00[3] = k3.row(q)[k]; g00 += 4; } } } #else // __mips_msa for (; p + 1 < outch; p += 2) { const Mat k0 = kernel_tm.channel(p); const Mat k1 = kernel_tm.channel(p + 1); Mat g0 = kernel_tm_packed.channel(p / 2); for (int k = 0; k < 36; k++) { short* g00 = g0.row(k); int q = 0; #if __mips_loongson_mmi for (; q + 3 < inch; q += 4) { g00[0] = k0.row(q)[k]; g00[1] = k0.row(q + 1)[k]; g00[2] = k1.row(q)[k]; g00[3] = k1.row(q + 1)[k]; g00[4] = k0.row(q + 2)[k]; g00[5] = k0.row(q + 3)[k]; g00[6] = k1.row(q + 2)[k]; g00[7] = k1.row(q + 3)[k]; g00 += 8; } #endif // __mips_loongson_mmi for (; q < inch; q++) { g00[0] = k0.row(q)[k]; g00[1] = k1.row(q)[k]; g00 += 2; } } } #endif // __mips_msa for (; p < outch; p++) { const Mat k0 = kernel_tm.channel(p); #if __mips_msa Mat g0 = kernel_tm_packed.channel(p / 4 + p % 4); #else Mat g0 = kernel_tm_packed.channel(p / 2 + p % 2); #endif for (int k = 0; k < 36; k++) { short* g00 = g0.row(k); int q = 0; #if __mips_msa || __mips_loongson_mmi for (; q + 3 < inch; q += 4) { g00[0] = k0.row(q)[k]; g00[1] = k0.row(q + 1)[k]; g00[2] = k0.row(q + 2)[k]; g00[3] = k0.row(q + 3)[k]; g00 += 4; } #endif // __mips_msa || __mips_loongson_mmi for (; q < inch; q++) { g00[0] = k0.row(q)[k]; g00 += 1; } } } } static void conv3x3s1_winograd43_int8_msa(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel_tm, const Option& opt) { int w = bottom_blob.w; int h = bottom_blob.h; int inch = bottom_blob.c; // size_t elemsize = bottom_blob.elemsize; int elempack = bottom_blob.elempack; int outw = top_blob.w; int outh = top_blob.h; int outch = top_blob.c; // pad to 4n+2 Mat bottom_blob_bordered = bottom_blob; outw = (outw + 3) / 4 * 4; outh = (outh + 3) / 4 * 4; w = outw + 2; h = outh + 2; copy_make_border(bottom_blob, bottom_blob_bordered, 0, h - bottom_blob.h, 0, w - bottom_blob.w, BORDER_CONSTANT, 0.f, opt); // BEGIN transform input Mat bottom_blob_tm; { int w_tiles = outw / 4; int h_tiles = outh / 4; const int tiles = w_tiles * h_tiles; bottom_blob_tm.create(tiles, 36, inch, 2u * elempack, elempack, opt.workspace_allocator); conv3x3s1_winograd43_transform_input_int8_msa(bottom_blob_bordered, bottom_blob_tm, opt); } bottom_blob_bordered = Mat(); // END transform input // BEGIN dot Mat top_blob_tm; convolution_winograd_dot_int8_msa(bottom_blob_tm, outch, kernel_tm, top_blob_tm, opt); // END dot // BEGIN transform output Mat top_blob_bordered; if (outw == top_blob.w && outh == top_blob.h) { top_blob_bordered = top_blob; } else { top_blob_bordered.create(outw, outh, outch, 4u, 1, opt.workspace_allocator); } { conv3x3s1_winograd43_transform_output_int8_msa(top_blob_tm, top_blob_bordered, opt); } // END transform output // cut result pad copy_cut_border(top_blob_bordered, top_blob, 0, top_blob_bordered.h - top_blob.h, 0, top_blob_bordered.w - top_blob.w, opt); }