// Copyright 2016 SoundAI Technology Co., Ltd. (author: Charles Wang) // // 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 "statisticspooling.h" #include #include namespace ncnn { StatisticsPooling::StatisticsPooling() { one_blob_only = true; support_inplace = false; } int StatisticsPooling::load_param(const ParamDict& pd) { include_stddev = pd.get(0, 0); return 0; } int StatisticsPooling::forward(const Mat& bottom_blob, Mat& top_blob, const Option& opt) const { int w = bottom_blob.w; int h = bottom_blob.h; int channels = bottom_blob.c; int size = w * h; size_t elemsize = bottom_blob.elemsize; int out_channels = channels; if (include_stddev) { out_channels *= 2; } top_blob.create(out_channels, elemsize, opt.blob_allocator); #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < channels; q++) { const float* ptr = bottom_blob.channel(q); float mean = 0.f; for (int i = 0; i < size; i++) { mean += ptr[i]; } top_blob[q] = mean / w / h; } #pragma omp parallel for num_threads(opt.num_threads) for (int q = channels; q < out_channels; q++) { const float* ptr = bottom_blob.channel(q - channels); float std = 0.f; for (int i = 0; i < size; i++) { std += powf((ptr[i] - top_blob[q - channels]), 2); } top_blob[q] = sqrtf(std / w / h); } return 0; } } // namespace ncnn