// Tencent is pleased to support the open source community by making ncnn available. // // Copyright (C) 2017 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. #include "concat.h" namespace ncnn { Concat::Concat() { one_blob_only = false; support_inplace = false; } int Concat::load_param(const ParamDict& pd) { axis = pd.get(0, 0); return 0; } int Concat::forward(const std::vector& bottom_blobs, std::vector& top_blobs, const Option& opt) const { int dims = bottom_blobs[0].dims; size_t elemsize = bottom_blobs[0].elemsize; int positive_axis = axis < 0 ? dims + axis : axis; if (dims == 1) // positive_axis == 0 { // concat vector // total length 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, elemsize, opt.blob_allocator); if (top_blob.empty()) return -100; unsigned char* outptr = top_blob; for (size_t b = 0; b < bottom_blobs.size(); b++) { const Mat& bottom_blob = bottom_blobs[b]; int w = bottom_blob.w; const unsigned char* ptr = bottom_blob; memcpy(outptr, ptr, w * elemsize); outptr += w * elemsize; } } if (dims == 2 && positive_axis == 0) { // concat image int w = bottom_blobs[0].w; // 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, elemsize, opt.blob_allocator); if (top_blob.empty()) return -100; unsigned char* outptr = top_blob; for (size_t b = 0; b < bottom_blobs.size(); b++) { const Mat& bottom_blob = bottom_blobs[b]; int size = w * bottom_blob.h; const unsigned char* ptr = bottom_blob; memcpy(outptr, ptr, size * elemsize); outptr += size * elemsize; } } if (dims == 2 && positive_axis == 1) { // interleave image row int h = bottom_blobs[0].h; // 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, 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++) { unsigned char* outptr = top_blob.row(i); for (size_t b = 0; b < bottom_blobs.size(); b++) { const Mat& bottom_blob = bottom_blobs[b]; const unsigned char* ptr = bottom_blob.row(i); memcpy(outptr, ptr, bottom_blob.w * elemsize); outptr += bottom_blob.w * elemsize; } } } 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 int top_channels = 0; for (size_t b = 0; b < bottom_blobs.size(); b++) { const Mat& bottom_blob = bottom_blobs[b]; top_channels += bottom_blob.c; } Mat& top_blob = top_blobs[0]; top_blob.create(w, h, d, top_channels, elemsize, opt.blob_allocator); if (top_blob.empty()) return -100; top_blob.dims = dims; int q = 0; for (size_t b = 0; b < bottom_blobs.size(); b++) { const Mat& bottom_blob = bottom_blobs[b]; int channels = bottom_blob.c; size_t size = bottom_blob.cstep * channels; const unsigned char* ptr = bottom_blob; unsigned char* outptr = top_blob.channel(q); memcpy(outptr, ptr, size * elemsize); q += channels; } } 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; // 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, 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++) { unsigned char* 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 unsigned char* ptr = bottom_blob.channel(q).depth(i); memcpy(outptr, ptr, size * elemsize); outptr += size * elemsize; } } } } 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; // 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, d, channels, elemsize, 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++) { unsigned char* 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 unsigned char* ptr = bottom_blob.channel(q).depth(i).row(j); memcpy(outptr, ptr, bottom_blob.w * elemsize); outptr += bottom_blob.w * elemsize; } } } } } 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; // 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, 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++) { unsigned char* 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 unsigned char* ptr = bottom_blob.channel(q); memcpy(outptr, ptr, size * elemsize); outptr += size * elemsize; } } } return 0; } } // namespace ncnn