// 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. #include "batchnorm_mips.h" #if __mips_msa #include #endif // __mips_msa #include "mips_usability.h" namespace ncnn { BatchNorm_mips::BatchNorm_mips() { #if __mips_msa support_packing = true; #endif // __mips_msa } int BatchNorm_mips::forward_inplace(Mat& bottom_top_blob, const Option& opt) const { int dims = bottom_top_blob.dims; int elempack = bottom_top_blob.elempack; if (dims == 1) { int w = bottom_top_blob.w * elempack; #if __mips_msa int nn_w = w / 4; int remain_w_start = nn_w * 4; #else int remain_w_start = 0; #endif // __mips_msa float* ptr = bottom_top_blob; #if __mips_msa #pragma omp parallel for num_threads(opt.num_threads) for (int i = 0; i < nn_w; i++) { float* ptr0 = ptr + i * 4; v4f32 _p = (v4f32)__msa_ld_w(ptr0, 0); v4f32 _a = (v4f32)__msa_ld_w((const float*)a_data + i * 4, 0); v4f32 _b = (v4f32)__msa_ld_w((const float*)b_data + i * 4, 0); _p = __msa_fmadd_w(_a, _p, _b); __msa_st_w((v4i32)_p, ptr0, 0); } #endif // __mips_msa #pragma omp parallel for num_threads(opt.num_threads) for (int i = remain_w_start; i < w; i++) { ptr[i] = b_data[i] * ptr[i] + a_data[i]; } } if (dims == 2) { int w = bottom_top_blob.w * elempack; int h = bottom_top_blob.h; #pragma omp parallel for num_threads(opt.num_threads) for (int i = 0; i < h; i++) { float* ptr = bottom_top_blob.row(i); float a = a_data[i]; float b = b_data[i]; int j = 0; #if __mips_msa v4f32 _a = elempack == 4 ? (v4f32)__msa_ld_w((const float*)a_data + i * 4, 0) : (v4f32)__msa_fill_w_f32(a); v4f32 _b = elempack == 4 ? (v4f32)__msa_ld_w((const float*)b_data + i * 4, 0) : (v4f32)__msa_fill_w_f32(b); for (; j + 3 < w; j += 4) { __builtin_prefetch(ptr + 16); v4f32 _p = (v4f32)__msa_ld_w(ptr, 0); _p = __msa_fmadd_w(_a, _p, _b); __msa_st_w((v4i32)_p, ptr, 0); ptr += 4; } #endif // __mips_msa for (; j < w; j++) { *ptr = b * *ptr + a; ptr++; } } } if (dims == 3 || dims == 4) { int w = bottom_top_blob.w; int h = bottom_top_blob.h; int d = bottom_top_blob.d; int c = bottom_top_blob.c; int size = w * h * d * elempack; #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < c; q++) { float* ptr = bottom_top_blob.channel(q); float a = a_data[q]; float b = b_data[q]; int i = 0; #if __mips_msa v4f32 _a = elempack == 4 ? (v4f32)__msa_ld_w((const float*)a_data + q * 4, 0) : (v4f32)__msa_fill_w_f32(a); v4f32 _b = elempack == 4 ? (v4f32)__msa_ld_w((const float*)b_data + q * 4, 0) : (v4f32)__msa_fill_w_f32(b); for (; i + 3 < size; i += 4) { __builtin_prefetch(ptr + 16); v4f32 _p = (v4f32)__msa_ld_w(ptr, 0); _p = __msa_fmadd_w(_a, _p, _b); __msa_st_w((v4i32)_p, ptr, 0); ptr += 4; } #endif // __mips_msa for (; i < size; i++) { *ptr = b * *ptr + a; ptr++; } } } return 0; } } // namespace ncnn