// yala is pleased to support the open source community by making ncnn available. // // // Copyright (C) 2022 yala ;. 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_loongarch.h" #include #if __loongarch_sx #include #include "lsx_mathfun.h" #endif // __loongarch_sx namespace ncnn { BinaryOp_loongarch::BinaryOp_loongarch() { #if __loongarch_sx support_packing = true; #endif // __loongarch_sx } template static void binary_op_vector_no_broadcast(const float* ptr, const float* ptr1, float* outptr, int size) { const Op op; int i = 0; #if __loongarch_sx for (; i + 3 < size; i += 4) { __builtin_prefetch(ptr + 16); __builtin_prefetch(ptr1 + 16); __m128 _p = (__m128)__lsx_vld(ptr, 0); __m128 _b = (__m128)__lsx_vld(ptr1, 0); __m128 _outp = op(_p, _b); __lsx_vst(_outp, outptr, 0); ptr += 4; ptr1 += 4; outptr += 4; } #endif // __loongarch_sx for (; i < size; i++) { *outptr = op(*ptr, *ptr1); ptr += 1; ptr1 += 1; outptr += 1; } } template static void binary_op_vector_broadcast_b(const float* ptr, const float* ptr1, float* outptr, int size, int elempack) { const Op op; const float b = *ptr1; #if __loongarch_sx __m128 _b_128 = (elempack == 4) ? (__m128)__lsx_vld(ptr1, 0) : __lsx_vreplfr2vr_s(b); #endif // __loongarch_sx int i = 0; #if __loongarch_sx for (; i + 3 < size; i += 4) { __builtin_prefetch(ptr + 16); __m128 _p = (__m128)__lsx_vld(ptr, 0); __m128 _outp = op(_p, _b_128); __lsx_vst(_outp, outptr, 0); ptr += 4; outptr += 4; } #endif // __loongarch_sx for (; i < size; i++) { *outptr = op(*ptr, b); ptr += 1; outptr += 1; } } template static void binary_op_vector_broadcast_a(const float* ptr, const float* ptr1, float* outptr, int size, int elempack) { const Op op; const float a = *ptr; #if __loongarch_sx __m128 _a_128 = (elempack == 4) ? (__m128)__lsx_vld(ptr, 0) : __lsx_vreplfr2vr_s(a); #endif // __loongarch_sx int i = 0; #if __loongarch_sx for (; i + 3 < size; i += 4) { __builtin_prefetch(ptr1 + 16); __m128 _b = (__m128)__lsx_vld(ptr1, 0); __m128 _outp = op(_a_128, _b); __lsx_vst(_outp, outptr, 0); ptr1 += 4; outptr += 4; } #endif // __loongarch_sx for (; i < size; i++) { *outptr = op(a, *ptr1); ptr1 += 1; outptr += 1; } } template static void binary_op_vector_broadcast_pb(const float* ptr, const float* ptr1, float* outptr, int w, int elempack) { const Op op; #if __loongarch_sx if (elempack == 4) { int i = 0; for (; i < w; i++) { __builtin_prefetch(ptr + 16); __m128 _p = (__m128)__lsx_vld(ptr, 0); __m128 _b = __lsx_vreplfr2vr_s(*ptr1); __m128 _outp = op(_p, _b); __lsx_vst(_outp, outptr, 0); ptr += 4; ptr1 += 1; outptr += 4; } } #endif // __loongarch_sx } template static void binary_op_vector_broadcast_pb_b(const float* ptr, const float* ptr1, float* outptr, int w, int elempack) { const Op op; const int size = w * elempack; int i = 0; #if __loongarch_sx __m128 _b = __lsx_vreplfr2vr_s(*ptr1); for (; i + 3 < size; i += 4) { __builtin_prefetch(ptr + 16); __m128 _p = (__m128)__lsx_vld(ptr, 0); __m128 _outp = op(_p, _b); __lsx_vst(_outp, outptr, 0); ptr += 4; outptr += 4; } #endif // __loongarch_sx } template static void binary_op_vector_broadcast_pb_a(const float* ptr, const float* ptr1, float* outptr, int w, int elempack) { const Op op; #if __loongarch_sx if (elempack == 4) { int i = 0; __m128 _p = (__m128)__lsx_vld(ptr, 0); for (; i < w; i++) { __m128 _b = __lsx_vreplfr2vr_s(*ptr1); __m128 _outp = op(_p, _b); __lsx_vst(_outp, outptr, 0); ptr1 += 1; outptr += 4; } } #endif // __loongarch_sx } template static void binary_op_vector(const float* ptr, const float* ptr1, float* outptr, int aw, int bw, int ap, int bp) { const int w = std::max(aw, bw); const int elempack = std::max(ap, bp); const int size = w * elempack; if (ap == bp) { if (aw == bw) { // no broadcast return binary_op_vector_no_broadcast(ptr, ptr1, outptr, size); } if (bw == 1) { // broadcast single b return binary_op_vector_broadcast_b(ptr, ptr1, outptr, size, elempack); } if (aw == 1) { // broadcast single a return binary_op_vector_broadcast_a(ptr, ptr1, outptr, size, elempack); } } if (bp == 1) { if (aw == bw) { // broadcast pack1 b return binary_op_vector_broadcast_pb(ptr, ptr1, outptr, w, elempack); } if (bw == 1) { // broadcast pack1 single b return binary_op_vector_broadcast_pb_b(ptr, ptr1, outptr, w, elempack); } if (aw == 1) { // broadcast single a and pack1 b return binary_op_vector_broadcast_pb_a(ptr, ptr1, outptr, w, elempack); } } // shall never reach here } template static int binary_op_scalar_inplace(Mat& a, float b, const Option& opt) { Op op; const int channels = a.c; const int size = a.w * a.h * a.d * a.elempack; #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < channels; q++) { float* ptr = a.channel(q); int i = 0; #if __loongarch_sx __m128 _b = __lsx_vreplfr2vr_s(b); for (; i + 3 < size; i += 4) { __builtin_prefetch(ptr + 16); __m128 _p = (__m128)__lsx_vld(ptr, 0); _p = op(_p, _b); __lsx_vst(_p, ptr, 0); ptr += 4; } #endif // __loongarch_sx for (; i < size; i++) { *ptr = op(*ptr, b); ptr++; } } return 0; } namespace BinaryOp_loongarch_functor { #if __loongarch_sx #define MAKE_FUNCTION(NAME, IMPL, IMPL4) \ struct NAME \ { \ float operator()(const float& x, const float& y) const \ { \ return IMPL; \ } \ __m128 operator()(const __m128& x, const __m128& y) const \ { \ return IMPL4; \ } \ }; #else #define MAKE_FUNCTION(NAME, IMPL, IMPL4) \ struct NAME \ { \ float operator()(const float& x, const float& y) const \ { \ return IMPL; \ } \ }; #endif // __loongarch_sx // clang-format off // *INDENT-OFF* MAKE_FUNCTION(binary_op_add, x + y, __lsx_vfadd_s(x, y)) MAKE_FUNCTION(binary_op_sub, x - y, __lsx_vfsub_s(x, y)) MAKE_FUNCTION(binary_op_mul, x * y, __lsx_vfmul_s(x, y)) MAKE_FUNCTION(binary_op_div, x / y, __lsx_vfdiv_s(x, y)) MAKE_FUNCTION(binary_op_max, std::max(x, y), __lsx_vfmax_s(x, y)) MAKE_FUNCTION(binary_op_min, std::min(x, y), __lsx_vfmin_s(x, y)) MAKE_FUNCTION(binary_op_pow, (float)pow(x, y), pow_ps(x, y)) MAKE_FUNCTION(binary_op_rsub, y - x, __lsx_vfsub_s(y, x)) MAKE_FUNCTION(binary_op_rdiv, y / x, __lsx_vfdiv_s(y, x)) MAKE_FUNCTION(binary_op_rpow, (float)pow(y, x), pow_ps(y, x)) MAKE_FUNCTION(binary_op_atan2, (float)atan2(x, y), atan2_ps(x, y)) MAKE_FUNCTION(binary_op_ratan2, (float)atan2(y, x), atan2_ps(y, x)) // *INDENT-ON* // clang-format on #undef MAKE_FUNCTION } // namespace BinaryOp_loongarch_functor static void binary_op_vector(const float* ptr, const float* ptr1, float* outptr, int aw, int bw, int ap, int bp, int op_type) { using namespace BinaryOp_loongarch_functor; if (op_type == BinaryOp::Operation_ADD) return binary_op_vector(ptr, ptr1, outptr, aw, bw, ap, bp); if (op_type == BinaryOp::Operation_SUB) return binary_op_vector(ptr, ptr1, outptr, aw, bw, ap, bp); if (op_type == BinaryOp::Operation_MUL) return binary_op_vector(ptr, ptr1, outptr, aw, bw, ap, bp); if (op_type == BinaryOp::Operation_DIV) return binary_op_vector(ptr, ptr1, outptr, aw, bw, ap, bp); if (op_type == BinaryOp::Operation_MAX) return binary_op_vector(ptr, ptr1, outptr, aw, bw, ap, bp); if (op_type == BinaryOp::Operation_MIN) return binary_op_vector(ptr, ptr1, outptr, aw, bw, ap, bp); if (op_type == BinaryOp::Operation_POW) return binary_op_vector(ptr, ptr1, outptr, aw, bw, ap, bp); if (op_type == BinaryOp::Operation_RSUB) return binary_op_vector(ptr, ptr1, outptr, aw, bw, ap, bp); if (op_type == BinaryOp::Operation_RDIV) return binary_op_vector(ptr, ptr1, outptr, aw, bw, ap, bp); if (op_type == BinaryOp::Operation_RPOW) return binary_op_vector(ptr, ptr1, outptr, aw, bw, ap, bp); if (op_type == BinaryOp::Operation_ATAN2) return binary_op_vector(ptr, ptr1, outptr, aw, bw, ap, bp); if (op_type == BinaryOp::Operation_RATAN2) return binary_op_vector(ptr, ptr1, outptr, aw, bw, ap, bp); // should never reach here } static void binary_op_scalar(const Mat& a, float b, Mat& c, int op_type, const Option& opt) { const int channels = a.c; const int size = a.w * a.h * a.d * a.elempack; #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < channels; q++) { const float* ptr = a.channel(q); float* outptr = c.channel(q); binary_op_vector(ptr, &b, outptr, size, 1, 1, 1, op_type); } } static void binary_op_no_broadcast(const Mat& a, const Mat& b, Mat& c, int op_type, const Option& opt) { const int channels = a.c; const int size = a.w * a.h * a.d * a.elempack; #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < channels; q++) { const float* ptr = a.channel(q); const float* ptr1 = b.channel(q); float* outptr = c.channel(q); binary_op_vector(ptr, ptr1, outptr, size, size, 1, 1, op_type); } } static void binary_op_broadcast(const Mat& a, const Mat& b, Mat& c, int op_type, const Option& opt) { if (b.w * b.h * b.d * b.c * b.elempack == 1) { return binary_op_scalar(a, b[0], c, op_type, opt); } if (a.dims == b.dims && a.w == b.w && a.h == b.h && a.d == b.d && a.c == b.c && a.elempack == b.elempack) { return binary_op_no_broadcast(a, b, c, op_type, opt); } const int dims = c.dims; if (dims == 2) { const int h = c.h; #pragma omp parallel for num_threads(opt.num_threads) for (int y = 0; y < h; y++) { const int y0 = std::min(y, a.h - 1); const int y1 = std::min(y, b.h - 1); const float* ptr = a.row(y0); const float* ptr1 = b.row(y1); float* outptr = c.row(y); binary_op_vector(ptr, ptr1, outptr, a.w, b.w, a.elempack, b.elempack, op_type); } } if (dims == 3 || dims == 4) { const int channels = c.c; #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < channels; q++) { const int q0 = std::min(q, a.c - 1); const int q1 = std::min(q, b.c - 1); if (b.d * b.h * b.w == 1) { const float* ptr = a.channel(q0); const float* ptr1 = b.channel(q1); float* outptr = c.channel(q); binary_op_vector(ptr, ptr1, outptr, a.w * a.h * a.d, 1, a.elempack, b.elempack, op_type); continue; } if (b.h * b.w == 1) { for (int z = 0; z < c.d; z++) { const int z0 = std::min(z, a.d - 1); const int z1 = std::min(z, b.d - 1); const float* ptr = a.channel(q0).depth(z0); const float* ptr1 = b.channel(q1).depth(z1); float* outptr = c.channel(q).depth(z); binary_op_vector(ptr, ptr1, outptr, a.w * a.h, 1, a.elempack, b.elempack, op_type); } continue; } for (int z = 0; z < c.d; z++) { const int z0 = std::min(z, a.d - 1); const int z1 = std::min(z, b.d - 1); for (int y = 0; y < c.h; y++) { const int y0 = std::min(y, a.h - 1); const int y1 = std::min(y, b.h - 1); const float* ptr = a.channel(q0).depth(z0).row(y0); const float* ptr1 = b.channel(q1).depth(z1).row(y1); float* outptr = c.channel(q).depth(z).row(y); binary_op_vector(ptr, ptr1, outptr, a.w, b.w, a.elempack, b.elempack, op_type); } } } } } static void binary_op_scalar_inplace(Mat& a, float b, int op_type, const Option& opt) { const int channels = a.c; const int size = a.w * a.h * a.d * a.elempack; #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < channels; q++) { float* ptr = a.channel(q); binary_op_vector(ptr, &b, ptr, size, 1, 1, 1, op_type); } } static int get_reverse_op_type(int op_type) { if (op_type == BinaryOp::Operation_SUB) return BinaryOp::Operation_RSUB; if (op_type == BinaryOp::Operation_DIV) return BinaryOp::Operation_RDIV; if (op_type == BinaryOp::Operation_POW) return BinaryOp::Operation_RPOW; if (op_type == BinaryOp::Operation_ATAN2) return BinaryOp::Operation_RATAN2; if (op_type == BinaryOp::Operation_RSUB) return BinaryOp::Operation_SUB; if (op_type == BinaryOp::Operation_RDIV) return BinaryOp::Operation_DIV; if (op_type == BinaryOp::Operation_RPOW) return BinaryOp::Operation_POW; if (op_type == BinaryOp::Operation_RATAN2) return BinaryOp::Operation_ATAN2; return op_type; } int BinaryOp_loongarch::forward(const std::vector& bottom_blobs, std::vector& top_blobs, const Option& opt) const { const Mat& A = bottom_blobs[0]; const Mat& B = bottom_blobs[1]; const int outdims = std::max(A.dims, B.dims); Mat A2 = A; Mat B2 = B; if (A.dims < outdims) { // expand inner axes if (outdims == 2) { if (A.w * A.elempack == B.h * B.elempack) A2 = A.reshape(1, A.w, opt.workspace_allocator); else // if (A.w == B.w) { A2.dims = 2; A2.w = A.w * A.elempack; A2.elempack = 1; A2.elemsize = A.elemsize / A.elempack; A2.cstep = A2.w; } } if (outdims == 3 && A.dims == 1) { if (A.w * A.elempack == B.c * B.elempack) A2 = A.reshape(1, 1, A.w, opt.workspace_allocator); else // if (A.w == B.w) { A2.dims = 3; A2.w = A.w * A.elempack; A2.elempack = 1; A2.elemsize = A.elemsize / A.elempack; A2.cstep = A2.w; } } if (outdims == 3 && A.dims == 2) A2 = A.reshape(1, A.w, A.h, opt.workspace_allocator); if (outdims == 4 && A.dims == 1) { if (A.w * A.elempack == B.c * B.elempack) A2 = A.reshape(1, 1, 1, A.w, opt.workspace_allocator); else // if (A.w == B.w) { A2.dims = 4; A2.w = A.w * A.elempack; A2.elempack = 1; A2.elemsize = A.elemsize / A.elempack; A2.cstep = A2.w; } } if (outdims == 4 && A.dims == 2) A2 = A.reshape(1, 1, A.w, A.h, opt.workspace_allocator); if (outdims == 4 && A.dims == 3) A2 = A.reshape(1, A.w, A.h, A.c, opt.workspace_allocator); } if (B.dims < outdims) { // expand inner axes if (outdims == 2) { if (B.w * B.elempack == A.h * A.elempack) B2 = B.reshape(1, B.w, opt.workspace_allocator); else // if (B.w == A.w) { B2.dims = 2; B2.w = B.w * B.elempack; B2.elempack = 1; B2.elemsize = B.elemsize / B.elempack; B2.cstep = B2.w; } } if (outdims == 3 && B.dims == 1) { if (B.w * B.elempack == A.c * A.elempack) B2 = B.reshape(1, 1, B.w, opt.workspace_allocator); else // if (B.w == A.w) { B2.dims = 3; B2.w = B.w * B.elempack; B2.elempack = 1; B2.elemsize = B.elemsize / B.elempack; B2.cstep = B2.w; } } if (outdims == 3 && B.dims == 2) B2 = B.reshape(1, B.w, B.h, opt.workspace_allocator); if (outdims == 4 && B.dims == 1) { if (B.w * B.elempack == A.c * A.elempack) B2 = B.reshape(1, 1, 1, B.w, opt.workspace_allocator); else // if (B.w == A.w) { B2.dims = 4; B2.w = B.w * B.elempack; B2.elempack = 1; B2.elemsize = B.elemsize / B.elempack; B2.cstep = B2.w; } } if (outdims == 4 && B.dims == 2) B2 = B.reshape(1, 1, B.w, B.h, opt.workspace_allocator); if (outdims == 4 && B.dims == 3) B2 = B.reshape(1, B.w, B.h, B.c, opt.workspace_allocator); } const int outw = std::max(A2.w, B2.w); const int outh = std::max(A2.h, B2.h); const int outd = std::max(A2.d, B2.d); const int outc = std::max(A2.c, B2.c); const size_t out_elemsize = std::max(A2.elemsize, B2.elemsize); const int out_elempack = std::max(A2.elempack, B2.elempack); Mat& top_blob = top_blobs[0]; if (outdims == 1) { top_blob.create(outw, out_elemsize, out_elempack, opt.blob_allocator); } if (outdims == 2) { top_blob.create(outw, outh, out_elemsize, out_elempack, opt.blob_allocator); } if (outdims == 3) { top_blob.create(outw, outh, outc, out_elemsize, out_elempack, opt.blob_allocator); } if (outdims == 4) { top_blob.create(outw, outh, outd, outc, out_elemsize, out_elempack, opt.blob_allocator); } if (top_blob.empty()) return -100; const bool a_pack_is_lower = A2.elempack < B2.elempack; const bool a_pack_is_equal = A2.elempack == B2.elempack; const bool a_size_is_lower = A2.w * A2.h * A2.d * A2.c * A2.elempack < B2.w * B2.h * B2.d * B2.c * B2.elempack; if (a_pack_is_lower || (a_pack_is_equal && a_size_is_lower)) { binary_op_broadcast(B2, A2, top_blob, get_reverse_op_type(op_type), opt); } else { binary_op_broadcast(A2, B2, top_blob, op_type, opt); } return 0; } int BinaryOp_loongarch::forward_inplace(Mat& bottom_top_blob, const Option& opt) const { binary_op_scalar_inplace(bottom_top_blob, b, op_type, opt); return 0; } } // namespace ncnn