// yala is pleased to support the open source community by making ncnn available. // // // Copyright (C) 2022 yala ;. 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. #include "concat_loongarch.h" namespace ncnn { Concat_loongarch::Concat_loongarch() { #if __loongarch_sx support_packing = true; #endif // __loongarch_sx } int Concat_loongarch::forward(const std::vector& bottom_blobs, std::vector& top_blobs, const Option& opt) const { int dims = bottom_blobs[0].dims; int positive_axis = axis < 0 ? dims + axis : axis; if (dims == 1) // positive_axis == 0 { // concat vector // total length size_t elemsize = bottom_blobs[0].elemsize; int elempack = bottom_blobs[0].elempack; int top_w = 0; for (size_t b = 0; b < bottom_blobs.size(); b++) { const Mat& bottom_blob = bottom_blobs[b]; top_w += bottom_blob.w * bottom_blob.elempack; } int out_elempack = opt.use_packing_layout && top_w % 4 == 0 ? 4 : 1; size_t out_elemsize = elemsize / elempack * out_elempack; Mat& top_blob = top_blobs[0]; top_blob.create(top_w / out_elempack, out_elemsize, out_elempack, opt.blob_allocator); if (top_blob.empty()) return -100; float* outptr = top_blob; for (size_t b = 0; b < bottom_blobs.size(); b++) { const Mat& bottom_blob = bottom_blobs[b]; const float* ptr = bottom_blob; memcpy(outptr, ptr, bottom_blob.w * bottom_blob.elemsize); outptr += bottom_blob.w * bottom_blob.elempack; } } if (dims == 2 && positive_axis == 0) { // concat image int w = bottom_blobs[0].w; // total height size_t elemsize = bottom_blobs[0].elemsize; int elempack = bottom_blobs[0].elempack; int top_h = 0; for (size_t b = 0; b < bottom_blobs.size(); b++) { const Mat& bottom_blob = bottom_blobs[b]; elemsize = std::min(elemsize, bottom_blob.elemsize); elempack = std::min(elempack, bottom_blob.elempack); top_h += bottom_blob.h * bottom_blob.elempack; } int out_elempack = opt.use_packing_layout && top_h % 4 == 0 ? 4 : 1; size_t out_elemsize = elemsize / elempack * out_elempack; Mat& top_blob = top_blobs[0]; top_blob.create(w, top_h / out_elempack, out_elemsize, out_elempack, opt.blob_allocator); if (top_blob.empty()) return -100; Mat top_blob_unpacked = top_blob; if (elempack < out_elempack) { top_blob_unpacked.create(w, top_h / elempack, elemsize, elempack, opt.workspace_allocator); if (top_blob_unpacked.empty()) return -100; } float* outptr = top_blob_unpacked; for (size_t b = 0; b < bottom_blobs.size(); b++) { const Mat& bottom_blob = bottom_blobs[b]; if (bottom_blob.elempack == 4 && elempack == 1) { for (int i = 0; i < bottom_blob.h; i++) { const float* r0 = bottom_blob.row(i); float* outptr0 = outptr; float* outptr1 = outptr + w; float* outptr2 = outptr + w * 2; float* outptr3 = outptr + w * 3; for (int j = 0; j < w; j++) { *outptr0++ = r0[0]; *outptr1++ = r0[1]; *outptr2++ = r0[2]; *outptr3++ = r0[3]; r0 += 4; } outptr += w * 4; } } else // if (bottom_blob.elempack == 1 && elempack == 1) if (bottom_blob.elempack == 4 && elempack == 4) { int size = w * bottom_blob.h; const float* ptr = bottom_blob; memcpy(outptr, ptr, size * bottom_blob.elemsize); outptr += size * bottom_blob.elempack; } } // packing if (elempack < out_elempack) { convert_packing(top_blob_unpacked, top_blob, out_elempack, opt); } } if (dims == 2 && positive_axis == 1) { // interleave image row int h = bottom_blobs[0].h; size_t elemsize = bottom_blobs[0].elemsize; int elempack = bottom_blobs[0].elempack; // total width int top_w = 0; for (size_t b = 0; b < bottom_blobs.size(); b++) { const Mat& bottom_blob = bottom_blobs[b]; top_w += bottom_blob.w; } Mat& top_blob = top_blobs[0]; top_blob.create(top_w, h, elemsize, elempack, opt.blob_allocator); if (top_blob.empty()) return -100; #pragma omp parallel for num_threads(opt.num_threads) for (int i = 0; i < h; i++) { float* outptr = top_blob.row(i); for (size_t b = 0; b < bottom_blobs.size(); b++) { const Mat& bottom_blob = bottom_blobs[b]; const float* ptr = bottom_blob.row(i); memcpy(outptr, ptr, bottom_blob.w * elemsize); outptr += bottom_blob.w * elempack; } } } if ((dims == 3 || dims == 4) && positive_axis == 0) { // concat dim int w = bottom_blobs[0].w; int h = bottom_blobs[0].h; int d = bottom_blobs[0].d; // total channels size_t elemsize = bottom_blobs[0].elemsize; int elempack = bottom_blobs[0].elempack; int top_channels = 0; for (size_t b = 0; b < bottom_blobs.size(); b++) { const Mat& bottom_blob = bottom_blobs[b]; elemsize = std::min(elemsize, bottom_blob.elemsize); elempack = std::min(elempack, bottom_blob.elempack); top_channels += bottom_blob.c * bottom_blob.elempack; } int out_elempack = opt.use_packing_layout && top_channels % 4 == 0 ? 4 : 1; size_t out_elemsize = elemsize / elempack * out_elempack; Mat& top_blob = top_blobs[0]; top_blob.create(w, h, d, top_channels / out_elempack, out_elemsize, out_elempack, opt.blob_allocator); if (top_blob.empty()) return -100; top_blob.dims = dims; Mat top_blob_unpacked = top_blob; if (elempack < out_elempack) { top_blob_unpacked.create(w, h, d, top_channels / elempack, elemsize, elempack, opt.workspace_allocator); if (top_blob_unpacked.empty()) return -100; top_blob_unpacked.dims = dims; } int p = 0; for (size_t b = 0; b < bottom_blobs.size(); b++) { const Mat& bottom_blob = bottom_blobs[b]; if (bottom_blob.elempack == 4 && elempack == 1) { int size = bottom_blob.w * bottom_blob.h * bottom_blob.d; for (int q = 0; q < bottom_blob.c; q++) { const float* r0 = bottom_blob.channel(q); float* outptr0 = top_blob_unpacked.channel(p); float* outptr1 = top_blob_unpacked.channel(p + 1); float* outptr2 = top_blob_unpacked.channel(p + 2); float* outptr3 = top_blob_unpacked.channel(p + 3); for (int i = 0; i < size; i++) { *outptr0++ = r0[0]; *outptr1++ = r0[1]; *outptr2++ = r0[2]; *outptr3++ = r0[3]; r0 += 4; } p += 4; } } else // if (bottom_blob.elempack == 1 && elempack == 1) if (bottom_blob.elempack == 4 && elempack == 4) { int size = bottom_blob.total(); const float* ptr = bottom_blob; float* outptr = top_blob_unpacked.channel(p); memcpy(outptr, ptr, size * bottom_blob.elemsize); p += bottom_blob.c; } } // packing if (elempack < out_elempack) { convert_packing(top_blob_unpacked, top_blob, out_elempack, opt); } } if ((dims == 3 && positive_axis == 1) || (dims == 4 && positive_axis == 2)) { // interleave dim height int w = bottom_blobs[0].w; int d = bottom_blobs[0].d; int channels = bottom_blobs[0].c; size_t elemsize = bottom_blobs[0].elemsize; int elempack = bottom_blobs[0].elempack; // total height int top_h = 0; for (size_t b = 0; b < bottom_blobs.size(); b++) { const Mat& bottom_blob = bottom_blobs[b]; top_h += bottom_blob.h; } Mat& top_blob = top_blobs[0]; top_blob.create(w, top_h, d, channels, elemsize, elempack, opt.blob_allocator); if (top_blob.empty()) return -100; top_blob.dims = dims; #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < channels; q++) { float* outptr = top_blob.channel(q); for (int i = 0; i < d; i++) { for (size_t b = 0; b < bottom_blobs.size(); b++) { const Mat& bottom_blob = bottom_blobs[b]; int size = bottom_blob.w * bottom_blob.h; const float* ptr = bottom_blob.channel(q).depth(i); memcpy(outptr, ptr, size * elemsize); outptr += size * elempack; } } } } if ((dims == 3 && positive_axis == 2) || (dims == 4 && positive_axis == 3)) { // interleave dim width int h = bottom_blobs[0].h; int d = bottom_blobs[0].d; int channels = bottom_blobs[0].c; size_t elemsize = bottom_blobs[0].elemsize; int elempack = bottom_blobs[0].elempack; // total height int top_w = 0; for (size_t b = 0; b < bottom_blobs.size(); b++) { const Mat& bottom_blob = bottom_blobs[b]; top_w += bottom_blob.w; } Mat& top_blob = top_blobs[0]; top_blob.create(top_w, h, d, channels, elemsize, elempack, opt.blob_allocator); if (top_blob.empty()) return -100; top_blob.dims = dims; #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < channels; q++) { float* outptr = top_blob.channel(q); for (int i = 0; i < d; i++) { for (int j = 0; j < h; j++) { for (size_t b = 0; b < bottom_blobs.size(); b++) { const Mat& bottom_blob = bottom_blobs[b]; const float* ptr = bottom_blob.channel(q).depth(i).row(j); memcpy(outptr, ptr, bottom_blob.w * elemsize); outptr += bottom_blob.w * elempack; } } } } } if (dims == 4 && positive_axis == 1) { // interleave dim depth int w = bottom_blobs[0].w; int h = bottom_blobs[0].h; int channels = bottom_blobs[0].c; size_t elemsize = bottom_blobs[0].elemsize; int elempack = bottom_blobs[0].elempack; // total depth int top_d = 0; for (size_t b = 0; b < bottom_blobs.size(); b++) { const Mat& bottom_blob = bottom_blobs[b]; top_d += bottom_blob.d; } Mat& top_blob = top_blobs[0]; top_blob.create(w, h, top_d, channels, elemsize, elempack, opt.blob_allocator); if (top_blob.empty()) return -100; #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < channels; q++) { float* outptr = top_blob.channel(q); for (size_t b = 0; b < bottom_blobs.size(); b++) { const Mat& bottom_blob = bottom_blobs[b]; int size = bottom_blob.w * bottom_blob.h * bottom_blob.d; const float* ptr = bottom_blob.channel(q); memcpy(outptr, ptr, size * elemsize); outptr += size * elempack; } } } return 0; } } // namespace ncnn