// Tencent is pleased to support the open source community by making ncnn available. // // Copyright (C) 2019 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 "binaryop_arm.h" #include #include #if __ARM_NEON #include #include "neon_mathfun.h" #endif // __ARM_NEON namespace ncnn { DEFINE_LAYER_CREATOR(BinaryOp_arm) BinaryOp_arm::BinaryOp_arm() { #if __ARM_NEON support_packing = true; #endif // __ARM_NEON support_bf16_storage = true; } #if __ARM_NEON // broadcasting rule // https://github.com/Tencent/ncnn/wiki/binaryop-broadcasting template static int binary_op_pack4(const Mat& a, const Mat& b, Mat& c, const Option& opt) { Op op; int w = a.w; int h = a.h; int channels = a.c; int size = w * h; size_t elemsize = a.elemsize; int elempack = a.elempack; int w1 = b.w; int h1 = b.h; int channels1 = b.c; int size1 = w1 * h1; size_t elemsize1 = b.elemsize; int elempack1 = b.elempack; if (a.dims == 3) { if (b.dims == 3) { if (w1 == 1 && h1 == 1 && channels1 == channels) { // special type 1 c.create(w, h, channels, elemsize, elempack, opt.blob_allocator); if (c.empty()) return -100; #pragma omp parallel for num_threads(opt.num_threads) for (int q=0; q static int binary_op_scalar_inplace_pack4(Mat& a, float b, const Option& opt) { Op op; int w = a.w; int h = a.h; int channels = a.c; int size = w * h; float32x4_t _b = vdupq_n_f32(b); #pragma omp parallel for num_threads(opt.num_threads) for (int q=0; q& bottom_blobs, std::vector& top_blobs, const Option& opt) const { if (opt.use_bf16_storage) return forward_bf16s(bottom_blobs, top_blobs, opt); const Mat& bottom_blob = bottom_blobs[0]; const Mat& bottom_blob1 = bottom_blobs[1]; Mat& top_blob = top_blobs[0]; #if __ARM_NEON int elempack = bottom_blob.elempack; int elempack1 = bottom_blob1.elempack; if (elempack == 4 || elempack1 == 4) { if (op_type == Operation_ADD) return binary_op_pack4(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_SUB) return binary_op_pack4(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_MUL) return binary_op_pack4(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_DIV) return binary_op_pack4(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_MAX) return binary_op_pack4(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_MIN) return binary_op_pack4(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_POW) return binary_op_pack4(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_RSUB) return binary_op_pack4(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_RDIV) return binary_op_pack4(bottom_blob, bottom_blob1, top_blob, opt); } #endif // __ARM_NEON return BinaryOp::forward(bottom_blobs, top_blobs, opt); } int BinaryOp_arm::forward_inplace(Mat& bottom_top_blob, const Option& opt) const { if (opt.use_bf16_storage) return forward_inplace_bf16s(bottom_top_blob, opt); #if __ARM_NEON int elempack = bottom_top_blob.elempack; if (elempack == 4) { if (op_type == Operation_ADD) return binary_op_scalar_inplace_pack4(bottom_top_blob, b, opt); if (op_type == Operation_SUB) return binary_op_scalar_inplace_pack4(bottom_top_blob, b, opt); if (op_type == Operation_MUL) return binary_op_scalar_inplace_pack4(bottom_top_blob, b, opt); if (op_type == Operation_DIV) return binary_op_scalar_inplace_pack4(bottom_top_blob, b, opt); if (op_type == Operation_MAX) return binary_op_scalar_inplace_pack4(bottom_top_blob, b, opt); if (op_type == Operation_MIN) return binary_op_scalar_inplace_pack4(bottom_top_blob, b, opt); if (op_type == Operation_POW) return binary_op_scalar_inplace_pack4(bottom_top_blob, b, opt); if (op_type == Operation_RSUB) return binary_op_scalar_inplace_pack4(bottom_top_blob, b, opt); if (op_type == Operation_RDIV) return binary_op_scalar_inplace_pack4(bottom_top_blob, b, opt); } #endif // __ARM_NEON return BinaryOp::forward_inplace(bottom_top_blob, opt); } #if __ARM_NEON template static int binary_op_pack4_bf16s(const Mat& a, const Mat& b, Mat& c, const Option& opt) { Op op; int w = a.w; int h = a.h; int channels = a.c; int size = w * h; size_t elemsize = a.elemsize; int elempack = a.elempack; int w1 = b.w; int h1 = b.h; int channels1 = b.c; int size1 = w1 * h1; size_t elemsize1 = b.elemsize; int elempack1 = b.elempack; if (a.dims == 3) { if (b.dims == 3) { if (w1 == 1 && h1 == 1 && channels1 == channels) { // special type 1 c.create(w, h, channels, elemsize, elempack, opt.blob_allocator); if (c.empty()) return -100; #pragma omp parallel for num_threads(opt.num_threads) for (int q=0; q(q); unsigned short* outptr = c.channel(q); for (int y=0; y(q); const unsigned short* ptr1 = b.channel(q); unsigned short* outptr = c.channel(q); for (int y=0; y static int binary_op_scalar_inplace_pack4_bf16s(Mat& a, float b, const Option& opt) { Op op; int w = a.w; int h = a.h; int channels = a.c; int size = w * h; float32x4_t _b = vdupq_n_f32(b); #pragma omp parallel for num_threads(opt.num_threads) for (int q=0; q static int binary_op_bf16s(const Mat& a, const Mat& b, Mat& c, const Option& opt) { Op op; int w = a.w; int h = a.h; int channels = a.c; int size = w * h; size_t elemsize = a.elemsize; int w1 = b.w; int h1 = b.h; int channels1 = b.c; int size1 = w1 * h1; if (a.dims == 3) { if (b.dims == 3) { if (w1 == 1 && h1 == 1 && channels1 == channels) { // special type 1 c.create(w, h, channels, elemsize, opt.blob_allocator); if (c.empty()) return -100; #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < channels; q++) { const unsigned short* ptr = a.channel(q); const unsigned short* b0 = b.channel(q); unsigned short* outptr = c.channel(q); for (int i = 0; i < size; i++) { outptr[i] = float32_to_bfloat16(op(bfloat16_to_float32(ptr[i]), bfloat16_to_float32(b0[0]))); } } return 0; } if (w1 == w && h1 == h && channels1 == 1) { // special type 2 c.create(w, h, channels, elemsize, opt.blob_allocator); if (c.empty()) return -100; #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < channels; q++) { const unsigned short* ptr = a.channel(q); const unsigned short* ptr1 = b; unsigned short* outptr = c.channel(q); for (int i = 0; i < size; i++) { outptr[i] = float32_to_bfloat16(op(bfloat16_to_float32(ptr[i]), bfloat16_to_float32(ptr1[i]))); } } return 0; } if (w == 1 && h == 1 && channels1 == channels) { // special type 3 c.create(w1, h1, channels1, elemsize, opt.blob_allocator); if (c.empty()) return -100; #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < channels1; q++) { const unsigned short* a0 = a.channel(q); const unsigned short* ptr1 = b.channel(q); unsigned short* outptr = c.channel(q); for (int i = 0; i < size1; i++) { outptr[i] = float32_to_bfloat16(op(bfloat16_to_float32(a0[0]), bfloat16_to_float32(ptr1[i]))); } } return 0; } if (w1 == w && h1 == h && channels == 1) { // special type 4 c.create(w1, h1, channels1, elemsize, opt.blob_allocator); if (c.empty()) return -100; #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < channels1; q++) { const unsigned short* ptr = a; const unsigned short* ptr1 = b.channel(q); unsigned short* outptr = c.channel(q); for (int i = 0; i < size1; i++) { outptr[i] = float32_to_bfloat16(op(bfloat16_to_float32(ptr[i]), bfloat16_to_float32(ptr1[i]))); } } return 0; } // type 19 c.create(w, h, channels, elemsize, opt.blob_allocator); if (c.empty()) return -100; #pragma omp parallel for num_threads(opt.num_threads) for (int q=0; q(q); unsigned short* outptr = c.channel(q); for (int y=0; y(q); const unsigned short* ptr1 = b.channel(q); unsigned short* outptr = c.channel(q); for (int y=0; y static int binary_op_scalar_inplace_bf16s(Mat& a, float b, const Option& opt) { Op op; int w = a.w; int h = a.h; int channels = a.c; int size = w * h; #pragma omp parallel for num_threads(opt.num_threads) for (int q=0; q& bottom_blobs, std::vector& top_blobs, const Option& opt) const { const Mat& bottom_blob = bottom_blobs[0]; const Mat& bottom_blob1 = bottom_blobs[1]; Mat& top_blob = top_blobs[0]; int elempack = bottom_blob.elempack; int elempack1 = bottom_blob1.elempack; #if __ARM_NEON if (elempack == 4 || elempack1 == 4) { if (op_type == Operation_ADD) return binary_op_pack4_bf16s(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_SUB) return binary_op_pack4_bf16s(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_MUL) return binary_op_pack4_bf16s(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_DIV) return binary_op_pack4_bf16s(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_MAX) return binary_op_pack4_bf16s(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_MIN) return binary_op_pack4_bf16s(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_POW) return binary_op_pack4_bf16s(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_RSUB) return binary_op_pack4_bf16s(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_RDIV) return binary_op_pack4_bf16s(bottom_blob, bottom_blob1, top_blob, opt); } #endif // __ARM_NEON if (elempack == 1 && elempack1 == 1) { if (op_type == Operation_ADD) return binary_op_bf16s(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_SUB) return binary_op_bf16s(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_MUL) return binary_op_bf16s(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_DIV) return binary_op_bf16s(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_MAX) return binary_op_bf16s(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_MIN) return binary_op_bf16s(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_POW) return binary_op_bf16s(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_RSUB) return binary_op_bf16s(bottom_blob, bottom_blob1, top_blob, opt); if (op_type == Operation_RDIV) return binary_op_bf16s(bottom_blob, bottom_blob1, top_blob, opt); } return 0; } int BinaryOp_arm::forward_inplace_bf16s(Mat& bottom_top_blob, const Option& opt) const { int elempack = bottom_top_blob.elempack; #if __ARM_NEON if (elempack == 4) { if (op_type == Operation_ADD) return binary_op_scalar_inplace_pack4_bf16s(bottom_top_blob, b, opt); if (op_type == Operation_SUB) return binary_op_scalar_inplace_pack4_bf16s(bottom_top_blob, b, opt); if (op_type == Operation_MUL) return binary_op_scalar_inplace_pack4_bf16s(bottom_top_blob, b, opt); if (op_type == Operation_DIV) return binary_op_scalar_inplace_pack4_bf16s(bottom_top_blob, b, opt); if (op_type == Operation_MAX) return binary_op_scalar_inplace_pack4_bf16s(bottom_top_blob, b, opt); if (op_type == Operation_MIN) return binary_op_scalar_inplace_pack4_bf16s(bottom_top_blob, b, opt); if (op_type == Operation_POW) return binary_op_scalar_inplace_pack4_bf16s(bottom_top_blob, b, opt); if (op_type == Operation_RSUB) return binary_op_scalar_inplace_pack4_bf16s(bottom_top_blob, b, opt); if (op_type == Operation_RDIV) return binary_op_scalar_inplace_pack4_bf16s(bottom_top_blob, b, opt); } #endif // __ARM_NEON if (elempack == 1) { if (op_type == Operation_ADD) return binary_op_scalar_inplace_bf16s(bottom_top_blob, b, opt); if (op_type == Operation_SUB) return binary_op_scalar_inplace_bf16s(bottom_top_blob, b, opt); if (op_type == Operation_MUL) return binary_op_scalar_inplace_bf16s(bottom_top_blob, b, opt); if (op_type == Operation_DIV) return binary_op_scalar_inplace_bf16s(bottom_top_blob, b, opt); if (op_type == Operation_MAX) return binary_op_scalar_inplace_bf16s(bottom_top_blob, b, opt); if (op_type == Operation_MIN) return binary_op_scalar_inplace_bf16s(bottom_top_blob, b, opt); if (op_type == Operation_POW) return binary_op_scalar_inplace_bf16s(bottom_top_blob, b, opt); if (op_type == Operation_RSUB) return binary_op_scalar_inplace_bf16s(bottom_top_blob, b, opt); if (op_type == Operation_RDIV) return binary_op_scalar_inplace_bf16s(bottom_top_blob, b, opt); } return 0; } } // namespace ncnn