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| // 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. | |
| static void convolution_int8(const Mat& bottom_blob, Mat& top_blob, const Mat& weight_data_int8, 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 channels = bottom_blob.c; | |
| int outw = top_blob.w; | |
| int outh = top_blob.h; | |
| int outch = top_blob.c; | |
| const int maxk = kernel_w * kernel_h; | |
| // kernel offsets | |
| std::vector<int> _space_ofs(maxk); | |
| int* space_ofs = &_space_ofs[0]; | |
| { | |
| int p1 = 0; | |
| int p2 = 0; | |
| int gap = w * dilation_h - kernel_w * dilation_w; | |
| for (int i = 0; i < kernel_h; i++) | |
| { | |
| for (int j = 0; j < kernel_w; j++) | |
| { | |
| space_ofs[p1] = p2; | |
| p1++; | |
| p2 += dilation_w; | |
| } | |
| p2 += gap; | |
| } | |
| } | |
| // num_output | |
| for (int p = 0; p < outch; p++) | |
| { | |
| int* outptr = top_blob.channel(p); | |
| for (int i = 0; i < outh; i++) | |
| { | |
| for (int j = 0; j < outw; j++) | |
| { | |
| int sum = 0; | |
| // const signed char* kptr = weight_data_int8.channel(p); | |
| const signed char* kptr = (const signed char*)weight_data_int8 + maxk * channels * p; | |
| // channels | |
| for (int q = 0; q < channels; q++) | |
| { | |
| const Mat m = bottom_blob.channel(q); | |
| const signed char* sptr = m.row<signed char>(i * stride_h) + j * stride_w; | |
| for (int k = 0; k < maxk; k++) | |
| { | |
| signed char val = sptr[space_ofs[k]]; | |
| signed char w = kptr[k]; | |
| sum += val * w; | |
| } | |
| kptr += maxk; | |
| } | |
| outptr[j] = sum; | |
| } | |
| outptr += outw; | |
| } | |
| } | |
| } | |