diff options
Diffstat (limited to 'src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp')
| -rw-r--r-- | src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp | 817 |
1 files changed, 0 insertions, 817 deletions
diff --git a/src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp b/src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp deleted file mode 100644 index 8bfb37ea18..0000000000 --- a/src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp +++ /dev/null @@ -1,817 +0,0 @@ -/* - * Copyright (c) 2016-2020 ARM Limited. - * - * SPDX-License-Identifier: MIT - * - * Permission is hereby granted, free of charge, to any person obtaining a copy - * of this software and associated documentation files (the "Software"), to - * deal in the Software without restriction, including without limitation the - * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or - * sell copies of the Software, and to permit persons to whom the Software is - * furnished to do so, subject to the following conditions: - * - * The above copyright notice and this permission notice shall be included in all - * copies or substantial portions of the Software. - * - * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR - * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, - * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE - * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER - * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, - * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE - * SOFTWARE. - */ -#include "arm_compute/core/NEON/kernels/NEArithmeticSubtractionKernel.h" - -#include "arm_compute/core/CPP/Validate.h" -#include "arm_compute/core/NEON/NEAsymm.h" -#include "arm_compute/core/NEON/NESymm.h" -#include "arm_compute/core/NEON/wrapper/wrapper.h" -#include "arm_compute/core/TensorInfo.h" -#include "arm_compute/core/Validate.h" - -namespace arm_compute -{ -namespace -{ -template <typename T> -inline typename std::enable_if<std::is_same<T, int8_t>::value, int8_t>::type -quantize(float val, const QuantizationInfo &info) -{ - return quantize_qasymm8_signed(val, info); -} - -template <typename T> -inline typename std::enable_if<std::is_same<T, uint8_t>::value, uint8_t>::type -quantize(float val, const QuantizationInfo &info) -{ - return quantize_qasymm8(val, info); -} - -template <typename T> -void sub_same(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, bool is_sat) -{ - /** NEON vector tag type. */ - using ExactTagType = typename wrapper::traits::neon_bitvector_tag_t<T, wrapper::traits::BitWidth::W128>; - - // Create input windows - Window input1_win = window.broadcast_if_dimension_le_one(in1->info()->tensor_shape()); - Window input2_win = window.broadcast_if_dimension_le_one(in2->info()->tensor_shape()); - - // Clear X Dimension on execution window as we handle manually - Window win = window; - win.set(Window::DimX, Window::Dimension(0, 1, 1)); - - constexpr int window_step_x = 16 / sizeof(T); - const auto window_start_x = static_cast<int>(window.x().start()); - const auto window_end_x = static_cast<int>(window.x().end()); - const bool is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0); - - Iterator input1(in1, window.broadcast_if_dimension_le_one(in1->info()->tensor_shape())); - Iterator input2(in2, window.broadcast_if_dimension_le_one(in2->info()->tensor_shape())); - Iterator output(out, window); - - if(is_broadcast_across_x) - { - const bool is_broadcast_input_2 = input2_win.x().step() == 0; - Window broadcast_win = is_broadcast_input_2 ? input2_win : input1_win; - Window non_broadcast_win = !is_broadcast_input_2 ? input2_win : input1_win; - const ITensor *broadcast_tensor = is_broadcast_input_2 ? in2 : in1; - const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? in2 : in1; - - // Clear X Dimension on execution window as we handle manually - non_broadcast_win.set(Window::DimX, Window::Dimension(0, 1, 1)); - - Iterator broadcast_input(broadcast_tensor, broadcast_win); - Iterator non_broadcast_input(non_broadcast_tensor, non_broadcast_win); - Iterator output(out, win); - - execute_window_loop(win, [&](const Coordinates &) - { - const auto non_broadcast_input_ptr = reinterpret_cast<const T *>(non_broadcast_input.ptr()); - const auto output_ptr = reinterpret_cast<T *>(output.ptr()); - - const T broadcast_value = *reinterpret_cast<const T *>(broadcast_input.ptr()); - const auto broadcast_value_vec = wrapper::vdup_n(broadcast_value, ExactTagType{}); - - // Compute S elements per iteration - int x = window_start_x; - for(; x <= (window_end_x - window_step_x); x += window_step_x) - { - const auto non_broadcast_v = wrapper::vloadq(non_broadcast_input_ptr + x); - auto res = is_sat ? wrapper::vqsub(broadcast_value_vec, non_broadcast_v) : wrapper::vsub(broadcast_value_vec, non_broadcast_v); - if(is_broadcast_input_2) - { - res = wrapper::vmul(res, wrapper::vdup_n(static_cast<T>(-1), ExactTagType{})); - } - wrapper::vstore(output_ptr + x, res); - } - - // Compute left-over elements - for(; x < window_end_x; ++x) - { - const auto non_broadcast_v = *(non_broadcast_input_ptr + x); - auto res = is_sat ? wrapper::sub_sat(broadcast_value, non_broadcast_v) : broadcast_value - non_broadcast_v; - if(is_broadcast_input_2) - { - res = static_cast<T>(-1) * res; - } - - *(output_ptr + x) = res; - } - }, - broadcast_input, non_broadcast_input, output); - } - else - { - // Clear X Dimension on execution window as we handle manually - input1_win.set(Window::DimX, Window::Dimension(0, 1, 1)); - input2_win.set(Window::DimX, Window::Dimension(0, 1, 1)); - - Iterator input1(in1, input1_win); - Iterator input2(in2, input2_win); - Iterator output(out, win); - - execute_window_loop(win, [&](const Coordinates &) - { - const auto input1_ptr = reinterpret_cast<const T *>(input1.ptr()); - const auto input2_ptr = reinterpret_cast<const T *>(input2.ptr()); - const auto output_ptr = reinterpret_cast<T *>(output.ptr()); - - // Compute S elements per iteration - int x = window_start_x; - for(; x <= (window_end_x - window_step_x); x += window_step_x) - { - const auto val1 = wrapper::vloadq(input1_ptr + x); - const auto val2 = wrapper::vloadq(input2_ptr + x); - const auto res = is_sat ? wrapper::vqsub(val1, val2) : wrapper::vsub(val1, val2); - wrapper::vstore(output_ptr + x, res); - } - - // Compute left-over elements - for(; x < window_end_x; ++x) - { - const auto val1 = *(input1_ptr + x); - const auto val2 = *(input2_ptr + x); - *(output_ptr + x) = is_sat ? wrapper::sub_sat(val1, val2) : val1 - val2; - } - }, - input1, input2, output); - } -} - -template <typename T> -void sub_quantized(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, bool is_sat) -{ - ARM_COMPUTE_UNUSED(is_sat); - - // Create input windows - Window input1_win = window.broadcast_if_dimension_le_one(in1->info()->tensor_shape()); - Window input2_win = window.broadcast_if_dimension_le_one(in2->info()->tensor_shape()); - - // Clear X Dimension on execution window as we handle manually - Window win = window; - win.set(Window::DimX, Window::Dimension(0, 1, 1)); - - const int window_step_x = 16; - const auto window_start_x = static_cast<int>(window.x().start()); - const auto window_end_x = static_cast<int>(window.x().end()); - const bool is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0); - - const UniformQuantizationInfo iq1_info = in1->info()->quantization_info().uniform(); - const UniformQuantizationInfo iq2_info = in2->info()->quantization_info().uniform(); - const UniformQuantizationInfo oq_info = out->info()->quantization_info().uniform(); - - const float32x4_t vscale1 = vdupq_n_f32(iq1_info.scale); - const float32x4_t vscale2 = vdupq_n_f32(iq2_info.scale); - const float32x4_t invvscaleo = vdupq_n_f32(1.f / oq_info.scale); - const int32x4_t voffset1 = vdupq_n_s32(iq1_info.offset); - const int32x4_t voffset2 = vdupq_n_s32(iq2_info.offset); - const float32x4_t voffseto = vdupq_n_f32(oq_info.offset); - - if(is_broadcast_across_x) - { - const bool is_broadcast_input_2 = input2_win.x().step() == 0; - Window broadcast_win = is_broadcast_input_2 ? input2_win : input1_win; - Window non_broadcast_win = !is_broadcast_input_2 ? input2_win : input1_win; - const ITensor *broadcast_tensor = is_broadcast_input_2 ? in2 : in1; - const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? in2 : in1; - const UniformQuantizationInfo broadcast_qinfo = broadcast_tensor->info()->quantization_info().uniform(); - const UniformQuantizationInfo non_broadcast_qinfo = non_broadcast_tensor->info()->quantization_info().uniform(); - - // Clear X Dimension on execution window as we handle manually - non_broadcast_win.set(Window::DimX, Window::Dimension(0, 1, 1)); - - Iterator broadcast_input(broadcast_tensor, broadcast_win); - Iterator non_broadcast_input(non_broadcast_tensor, non_broadcast_win); - Iterator output(out, win); - - execute_window_loop(win, [&](const Coordinates &) - { - const auto non_broadcast_input_ptr = reinterpret_cast<const T *>(non_broadcast_input.ptr()); - const auto output_ptr = reinterpret_cast<T *>(output.ptr()); - - const auto broadcast_value = *reinterpret_cast<const T *>(broadcast_input.ptr()); - const auto broadcast_value_vec = wrapper::vdup_n(static_cast<T>(broadcast_value), wrapper::traits::vector_128_tag{}); - - const float32x4x4_t bf = - { - { - vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgetlow(wrapper::vmovl(wrapper::vgetlow(broadcast_value_vec))))), voffset2)), vscale2), - vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgethigh(wrapper::vmovl(wrapper::vgetlow(broadcast_value_vec))))), voffset2)), vscale2), - vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgetlow(wrapper::vmovl(wrapper::vgethigh(broadcast_value_vec))))), voffset2)), vscale2), - vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgethigh(wrapper::vmovl(wrapper::vgethigh(broadcast_value_vec))))), voffset2)), vscale2), - } - }; - const float bfs = static_cast<int32_t>(broadcast_value - broadcast_qinfo.offset) * broadcast_qinfo.scale; - - // Compute S elements per iteration - int x = window_start_x; - for(; x <= (window_end_x - window_step_x); x += window_step_x) - { - const auto a = wrapper::vloadq(non_broadcast_input_ptr + x); - - const float32x4x4_t af = - { - { - vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgetlow(wrapper::vmovl(wrapper::vgetlow(a))))), voffset1)), vscale1), - vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgethigh(wrapper::vmovl(wrapper::vgetlow(a))))), voffset1)), vscale1), - vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgetlow(wrapper::vmovl(wrapper::vgethigh(a))))), voffset1)), vscale1), - vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgethigh(wrapper::vmovl(wrapper::vgethigh(a))))), voffset1)), vscale1), - } - }; - - const int32x4x4_t rf = - { - { -#ifdef __aarch64__ - vcvtnq_s32_f32(vmlaq_f32(voffseto, is_broadcast_input_2 ? vsubq_f32(bf.val[0], af.val[0]) : vsubq_f32(af.val[0], bf.val[0]), invvscaleo)), - vcvtnq_s32_f32(vmlaq_f32(voffseto, is_broadcast_input_2 ? vsubq_f32(bf.val[1], af.val[1]) : vsubq_f32(af.val[1], bf.val[1]), invvscaleo)), - vcvtnq_s32_f32(vmlaq_f32(voffseto, is_broadcast_input_2 ? vsubq_f32(bf.val[2], af.val[2]) : vsubq_f32(af.val[2], bf.val[2]), invvscaleo)), - vcvtnq_s32_f32(vmlaq_f32(voffseto, is_broadcast_input_2 ? vsubq_f32(bf.val[3], af.val[3]) : vsubq_f32(af.val[3], bf.val[3]), invvscaleo)), -#else //__aarch64__ - vcvtq_s32_f32(vmlaq_f32(voffseto, is_broadcast_input_2 ? vsubq_f32(bf.val[0], af.val[0]) : vsubq_f32(af.val[0], bf.val[0]), invvscaleo)), - vcvtq_s32_f32(vmlaq_f32(voffseto, is_broadcast_input_2 ? vsubq_f32(bf.val[1], af.val[1]) : vsubq_f32(af.val[1], bf.val[1]), invvscaleo)), - vcvtq_s32_f32(vmlaq_f32(voffseto, is_broadcast_input_2 ? vsubq_f32(bf.val[2], af.val[2]) : vsubq_f32(af.val[2], bf.val[2]), invvscaleo)), - vcvtq_s32_f32(vmlaq_f32(voffseto, is_broadcast_input_2 ? vsubq_f32(bf.val[3], af.val[3]) : vsubq_f32(af.val[3], bf.val[3]), invvscaleo)), -#endif //__aarch64__ - } - }; - - const auto pa = wrapper::vqmov<T>(vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1]))); - const auto pb = wrapper::vqmov<T>(vcombine_s16(vqmovn_s32(rf.val[2]), vqmovn_s32(rf.val[3]))); - wrapper::vstore(output_ptr + x, wrapper::vcombine(pa, pb)); - } - - // Compute left-over elements - for(; x < window_end_x; ++x) - { - const float afs = static_cast<int32_t>(*(non_broadcast_input_ptr + x) - non_broadcast_qinfo.offset) * non_broadcast_qinfo.scale; - *(output_ptr + x) = quantize<T>((afs - bfs), out->info()->quantization_info()); - } - }, - broadcast_input, non_broadcast_input, output); - } - else - { - // Clear X Dimension on execution window as we handle manually - input1_win.set(Window::DimX, Window::Dimension(0, 1, 1)); - input2_win.set(Window::DimX, Window::Dimension(0, 1, 1)); - - Iterator input1(in1, input1_win); - Iterator input2(in2, input2_win); - Iterator output(out, win); - - execute_window_loop(win, [&](const Coordinates &) - { - const auto input1_ptr = reinterpret_cast<const T *>(input1.ptr()); - const auto input2_ptr = reinterpret_cast<const T *>(input2.ptr()); - const auto output_ptr = reinterpret_cast<T *>(output.ptr()); - - // Compute S elements per iteration - int x = window_start_x; - for(; x <= (window_end_x - window_step_x); x += window_step_x) - { - const auto a = wrapper::vloadq(input1_ptr + x); - const auto b = wrapper::vloadq(input2_ptr + x); - - const float32x4x4_t af = - { - { - vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgetlow(wrapper::vmovl(wrapper::vgetlow(a))))), voffset1)), vscale1), - vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgethigh(wrapper::vmovl(wrapper::vgetlow(a))))), voffset1)), vscale1), - vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgetlow(wrapper::vmovl(wrapper::vgethigh(a))))), voffset1)), vscale1), - vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgethigh(wrapper::vmovl(wrapper::vgethigh(a))))), voffset1)), vscale1), - } - }; - - const float32x4x4_t bf = - { - { - vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgetlow(wrapper::vmovl(wrapper::vgetlow(b))))), voffset2)), vscale2), - vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgethigh(wrapper::vmovl(wrapper::vgetlow(b))))), voffset2)), vscale2), - vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgetlow(wrapper::vmovl(wrapper::vgethigh(b))))), voffset2)), vscale2), - vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgethigh(wrapper::vmovl(wrapper::vgethigh(b))))), voffset2)), vscale2), - } - }; - - const int32x4x4_t rf = - { - { -#ifdef __aarch64__ - vcvtnq_s32_f32(vmlaq_f32(voffseto, vsubq_f32(af.val[0], bf.val[0]), invvscaleo)), - vcvtnq_s32_f32(vmlaq_f32(voffseto, vsubq_f32(af.val[1], bf.val[1]), invvscaleo)), - vcvtnq_s32_f32(vmlaq_f32(voffseto, vsubq_f32(af.val[2], bf.val[2]), invvscaleo)), - vcvtnq_s32_f32(vmlaq_f32(voffseto, vsubq_f32(af.val[3], bf.val[3]), invvscaleo)), -#else //__aarch64__ - vcvtq_s32_f32(vmlaq_f32(voffseto, vsubq_f32(af.val[0], bf.val[0]), invvscaleo)), - vcvtq_s32_f32(vmlaq_f32(voffseto, vsubq_f32(af.val[1], bf.val[1]), invvscaleo)), - vcvtq_s32_f32(vmlaq_f32(voffseto, vsubq_f32(af.val[2], bf.val[2]), invvscaleo)), - vcvtq_s32_f32(vmlaq_f32(voffseto, vsubq_f32(af.val[3], bf.val[3]), invvscaleo)), -#endif //__aarch64__ - } - }; - - const auto pa = wrapper::vqmov<T>(vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1]))); - const auto pb = wrapper::vqmov<T>(vcombine_s16(vqmovn_s32(rf.val[2]), vqmovn_s32(rf.val[3]))); - wrapper::vstore(output_ptr + x, wrapper::vcombine(pa, pb)); - } - - // Compute left-over elements - for(; x < window_end_x; ++x) - { - const float afs = static_cast<int32_t>((*(input1_ptr + x)) - iq1_info.offset) * iq1_info.scale; - const float bfs = static_cast<int32_t>((*(input2_ptr + x)) - iq2_info.offset) * iq2_info.scale; - - *(output_ptr + x) = quantize<T>((afs - bfs), out->info()->quantization_info()); - } - }, - input1, input2, output); - } -} - -void sub_QSYMM16_QSYMM16_QSYMM16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, bool is_sat) -{ - ARM_COMPUTE_UNUSED(is_sat); - - // Create input windows - Window input1_win = window.broadcast_if_dimension_le_one(in1->info()->tensor_shape()); - Window input2_win = window.broadcast_if_dimension_le_one(in2->info()->tensor_shape()); - - // Clear X Dimension on execution window as we handle manually - Window win = window; - win.set(Window::DimX, Window::Dimension(0, 1, 1)); - - const int window_step_x = 8; - const auto window_start_x = static_cast<int>(window.x().start()); - const auto window_end_x = static_cast<int>(window.x().end()); - const bool is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0); - - const UniformQuantizationInfo iq1_info = in1->info()->quantization_info().uniform(); - const UniformQuantizationInfo iq2_info = in2->info()->quantization_info().uniform(); - const UniformQuantizationInfo oq_info = out->info()->quantization_info().uniform(); - - const float32x4_t vscale1 = vdupq_n_f32(iq1_info.scale); - const float32x4_t vscale2 = vdupq_n_f32(iq2_info.scale); - const float32x4_t invvscaleo = vdupq_n_f32(1.f / oq_info.scale); - - if(is_broadcast_across_x) - { - const bool is_broadcast_input_2 = input2_win.x().step() == 0; - Window broadcast_win = is_broadcast_input_2 ? input2_win : input1_win; - Window non_broadcast_win = !is_broadcast_input_2 ? input2_win : input1_win; - const ITensor *broadcast_tensor = is_broadcast_input_2 ? in2 : in1; - const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? in2 : in1; - const UniformQuantizationInfo broadcast_qinfo = broadcast_tensor->info()->quantization_info().uniform(); - const UniformQuantizationInfo non_broadcast_qinfo = non_broadcast_tensor->info()->quantization_info().uniform(); - - // Clear X Dimension on execution window as we handle manually - non_broadcast_win.set(Window::DimX, Window::Dimension(0, 1, 1)); - - Iterator broadcast_input(broadcast_tensor, broadcast_win); - Iterator non_broadcast_input(non_broadcast_tensor, non_broadcast_win); - Iterator output(out, win); - - execute_window_loop(win, [&](const Coordinates &) - { - const auto non_broadcast_input_ptr = reinterpret_cast<const int16_t *>(non_broadcast_input.ptr()); - const auto output_ptr = reinterpret_cast<int16_t *>(output.ptr()); - - const int16_t broadcast_value = *reinterpret_cast<const int16_t *>(broadcast_input.ptr()); - const int16x8_t broadcast_value_vec = vdupq_n_s16(broadcast_value); - - const float32x4x2_t bf = - { - { - vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(broadcast_value_vec))), vscale2), - vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(broadcast_value_vec))), vscale2), - } - }; - const float bfs = static_cast<int32_t>(broadcast_value) * broadcast_qinfo.scale; - - // Compute S elements per iteration - int x = window_start_x; - for(; x <= (window_end_x - window_step_x); x += window_step_x) - { - const int16x8_t a = vld1q_s16(non_broadcast_input_ptr + x); - const float32x4x2_t af = - { - { - vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(a))), vscale1), - vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(a))), vscale1), - } - }; - - const int32x4x4_t rf = - { - { -#ifdef __aarch64__ - vcvtnq_s32_f32(vmulq_f32(is_broadcast_input_2 ? vsubq_f32(bf.val[0], af.val[0]) : vsubq_f32(af.val[0], bf.val[0]), invvscaleo)), - vcvtnq_s32_f32(vmulq_f32(is_broadcast_input_2 ? vsubq_f32(bf.val[1], af.val[1]) : vsubq_f32(af.val[1], bf.val[1]), invvscaleo)), -#else //__aarch64__ - vcvtq_s32_f32(vmulq_f32(is_broadcast_input_2 ? vsubq_f32(bf.val[0], af.val[0]) : vsubq_f32(af.val[0], bf.val[0]), invvscaleo)), - vcvtq_s32_f32(vmulq_f32(is_broadcast_input_2 ? vsubq_f32(bf.val[1], af.val[1]) : vsubq_f32(af.val[1], bf.val[1]), invvscaleo)), -#endif //__aarch64__ - } - }; - - const int16x8_t pa = vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1])); - vst1q_s16(output_ptr + x, pa); - } - - // Compute left-over elements - for(; x < window_end_x; ++x) - { - const float afs = static_cast<int32_t>(*(non_broadcast_input_ptr + x)) * non_broadcast_qinfo.scale; - *(output_ptr + x) = quantize_qsymm16(is_broadcast_input_2 ? (bfs - afs) : (afs - bfs), oq_info); - } - }, - broadcast_input, non_broadcast_input, output); - } - else - { - // Clear X Dimension on execution window as we handle manually - input1_win.set(Window::DimX, Window::Dimension(0, 1, 1)); - input2_win.set(Window::DimX, Window::Dimension(0, 1, 1)); - - Iterator input1(in1, input1_win); - Iterator input2(in2, input2_win); - Iterator output(out, win); - - execute_window_loop(win, [&](const Coordinates &) - { - const auto input1_ptr = reinterpret_cast<const int16_t *>(input1.ptr()); - const auto input2_ptr = reinterpret_cast<const int16_t *>(input2.ptr()); - const auto output_ptr = reinterpret_cast<int16_t *>(output.ptr()); - - // Compute S elements per iteration - int x = window_start_x; - for(; x <= (window_end_x - window_step_x); x += window_step_x) - { - const int16x8_t a = vld1q_s16(input1_ptr + x); - const int16x8_t b = vld1q_s16(input2_ptr + x); - - const float32x4x2_t af = - { - { - vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(a))), vscale1), - vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(a))), vscale1), - } - }; - - const float32x4x2_t bf = - { - { - vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(b))), vscale2), - vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(b))), vscale2), - } - }; - - const int32x4x2_t rf = - { - { -#ifdef __aarch64__ - vcvtnq_s32_f32(vmulq_f32(vsubq_f32(af.val[0], bf.val[0]), invvscaleo)), - vcvtnq_s32_f32(vmulq_f32(vsubq_f32(af.val[1], bf.val[1]), invvscaleo)), -#else //__aarch64__ - vcvtq_s32_f32(vmulq_f32(vsubq_f32(af.val[0], bf.val[0]), invvscaleo)), - vcvtq_s32_f32(vmulq_f32(vsubq_f32(af.val[1], bf.val[1]), invvscaleo)), -#endif //__aarch64__ - } - }; - - const int16x8_t pa = vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1])); - vst1q_s16(output_ptr + x, pa); - } - - // Compute left-over elements - for(; x < window_end_x; ++x) - { - const float afs = static_cast<int32_t>((*(input1_ptr + x))) * iq1_info.scale; - const float bfs = static_cast<int32_t>((*(input2_ptr + x))) * iq2_info.scale; - *(output_ptr + x) = quantize_qsymm16((afs - bfs), out->info()->quantization_info()); - } - }, - input1, input2, output); - } -} - -void sub_S16_U8_S16_impl(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, bool is_sat, bool is_swapped) -{ - // Create input windows - Window win = window; - Window input1_win = window.broadcast_if_dimension_le_one(in1->info()->tensor_shape()); - Window input2_win = window.broadcast_if_dimension_le_one(in2->info()->tensor_shape()); - - // Clear X Dimension on execution window as we handle manually - win.set(Window::DimX, Window::Dimension(0, 1, 1)); - input1_win.set(Window::DimX, Window::Dimension(0, 1, 1)); - input2_win.set(Window::DimX, Window::Dimension(0, 1, 1)); - - Iterator input1(in1, input1_win); - Iterator input2(in2, input2_win); - Iterator output(out, win); - - const int window_step_x = 8; - const auto window_start_x = static_cast<int>(window.x().start()); - const auto window_end_x = static_cast<int>(window.x().end()); - - execute_window_loop(win, [&](const Coordinates &) - { - const auto input1_ptr = reinterpret_cast<const int16_t *>(input1.ptr()); - const auto input2_ptr = reinterpret_cast<const uint8_t *>(input2.ptr()); - const auto output_ptr = reinterpret_cast<int16_t *>(output.ptr()); - - if(!is_sat) - { - // Compute S elements per iteration - int x = window_start_x; - for(; x <= (window_end_x - window_step_x); x += window_step_x) - { - const auto vin1 = wrapper::vloadq(input1_ptr + x); - const auto vin2 = vreinterpretq_s16_u16(wrapper::vmovl(wrapper::vload(input2_ptr + x))); - const auto res = is_swapped ? wrapper::vsub(vin2, vin1) : wrapper::vsub(vin1, vin2); - wrapper::vstore(output_ptr + x, res); - } - - // Compute left-over elements - for(; x < window_end_x; ++x) - { - const auto res = is_swapped ? static_cast<int16_t>(*(input2_ptr + x)) - *(input1_ptr + x) : *(input1_ptr + x) - static_cast<int16_t>(*(input2_ptr + x)); - *(output_ptr + x) = res; - } - } - else - { - // Compute S elements per iteration - int x = window_start_x; - for(; x <= (window_end_x - window_step_x); x += window_step_x) - { - const auto vin1 = wrapper::vloadq(input1_ptr + x); - const auto vin2 = vreinterpretq_s16_u16(wrapper::vmovl(wrapper::vload(input2_ptr + x))); - const auto res = is_swapped ? wrapper::vqsub(vin2, vin1) : wrapper::vqsub(vin1, vin2); - wrapper::vstore(output_ptr + x, res); - } - - // Compute left-over elements - for(; x < window_end_x; ++x) - { - const auto res = is_swapped ? wrapper::sub_sat(static_cast<int16_t>(*(input2_ptr + x)), *(input1_ptr + x)) : wrapper::sub_sat(*(input1_ptr + x), static_cast<int16_t>(*(input2_ptr + x))); - *(output_ptr + x) = res; - } - } - }, - input1, input2, output); -} - -void sub_S16_U8_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, bool is_sat) -{ - sub_S16_U8_S16_impl(in1, in2, out, window, is_sat, false); -} - -void sub_U8_S16_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, bool is_sat) -{ - // Swap arguments - sub_S16_U8_S16_impl(in2, in1, out, window, is_sat, true); -} - -void sub_U8_U8_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, bool is_sat) -{ - // Create input windows - Window win = window; - Window input1_win = window.broadcast_if_dimension_le_one(in1->info()->tensor_shape()); - Window input2_win = window.broadcast_if_dimension_le_one(in2->info()->tensor_shape()); - - // Clear X Dimension on execution window as we handle manually - win.set(Window::DimX, Window::Dimension(0, 1, 1)); - input1_win.set(Window::DimX, Window::Dimension(0, 1, 1)); - input2_win.set(Window::DimX, Window::Dimension(0, 1, 1)); - - Iterator input1(in1, input1_win); - Iterator input2(in2, input2_win); - Iterator output(out, win); - - const int window_step_x = 8; - const auto window_start_x = static_cast<int>(window.x().start()); - const auto window_end_x = static_cast<int>(window.x().end()); - - execute_window_loop(win, [&](const Coordinates &) - { - const auto input1_ptr = reinterpret_cast<const uint8_t *>(input1.ptr()); - const auto input2_ptr = reinterpret_cast<const uint8_t *>(input2.ptr()); - const auto output_ptr = reinterpret_cast<int16_t *>(output.ptr()); - - if(!is_sat) - { - // Compute S elements per iteration - int x = window_start_x; - for(; x <= (window_end_x - window_step_x); x += window_step_x) - { - const auto vin1 = vreinterpretq_s16_u16(wrapper::vmovl(wrapper::vload(input1_ptr + x))); - const auto vin2 = vreinterpretq_s16_u16(wrapper::vmovl(wrapper::vload(input2_ptr + x))); - wrapper::vstore(output_ptr + x, wrapper::vsub(vin1, vin2)); - } - - // Compute left-over elements - for(; x < window_end_x; ++x) - { - *(output_ptr + x) = static_cast<int16_t>(*(input1_ptr + x)) - static_cast<int16_t>(*(input2_ptr + x)); - } - } - else - { - // Compute S elements per iteration - int x = window_start_x; - for(; x <= (window_end_x - window_step_x); x += window_step_x) - { - const auto vin1 = vreinterpretq_s16_u16(wrapper::vmovl(wrapper::vload(input1_ptr + x))); - const auto vin2 = vreinterpretq_s16_u16(wrapper::vmovl(wrapper::vload(input2_ptr + x))); - wrapper::vstore(output_ptr + x, wrapper::vqsub(vin1, vin2)); - } - - // Compute left-over elements - for(; x < window_end_x; ++x) - { - *(output_ptr + x) = wrapper::sub_sat(static_cast<int16_t>(*(input1_ptr + x)), - static_cast<int16_t>(*(input2_ptr + x))); - } - } - }, - input1, input2, output); -} - -inline Status validate_arguments(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output, ConvertPolicy policy) -{ - ARM_COMPUTE_UNUSED(policy); - ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(&input1); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input1, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QSYMM16, DataType::S16, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input2, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QSYMM16, DataType::S16, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&output, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QSYMM16, DataType::S16, DataType::F16, DataType::F32); - - const TensorShape out_shape = TensorShape::broadcast_shape(input1.tensor_shape(), input2.tensor_shape()); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible"); - - ARM_COMPUTE_RETURN_ERROR_ON_MSG( - !(input1.data_type() == DataType::U8 && input2.data_type() == DataType::U8) - && !(input1.data_type() == DataType::QASYMM8 && input2.data_type() == DataType::QASYMM8) - && !(input1.data_type() == DataType::QASYMM8_SIGNED && input2.data_type() == DataType::QASYMM8_SIGNED) - && !(input1.data_type() == DataType::QSYMM16 && input2.data_type() == DataType::QSYMM16) - && !(input1.data_type() == DataType::U8 && input2.data_type() == DataType::U8) - && !(input1.data_type() == DataType::U8 && input2.data_type() == DataType::S16) - && !(input1.data_type() == DataType::S16 && input2.data_type() == DataType::U8) - && !(input1.data_type() == DataType::S16 && input2.data_type() == DataType::S16) - && !(input1.data_type() == DataType::F32 && input2.data_type() == DataType::F32) - && !(input1.data_type() == DataType::F16 && input2.data_type() == DataType::F16), - "You called subtract with the wrong image formats"); - - ARM_COMPUTE_RETURN_ERROR_ON_MSG( - input1.data_type() == DataType::QASYMM8_SIGNED && input2.data_type() == DataType::QASYMM8_SIGNED && policy == ConvertPolicy::WRAP - && input1.data_type() == DataType::QASYMM8 && input2.data_type() == DataType::QASYMM8 && policy == ConvertPolicy::WRAP - && input1.data_type() == DataType::QSYMM16 && input2.data_type() == DataType::QSYMM16 && policy == ConvertPolicy::WRAP, - "Convert policy cannot be WRAP if datatype is QASYMM8 or QASYMM8_SIGNED"); - - // Validate in case of configured output - if(output.total_size() > 0) - { - ARM_COMPUTE_RETURN_ERROR_ON_MSG( - !(input1.data_type() == DataType::U8 && input2.data_type() == DataType::U8 && output.data_type() == DataType::U8) - && !(input1.data_type() == DataType::QASYMM8 && input2.data_type() == DataType::QASYMM8 && output.data_type() == DataType::QASYMM8) - && !(input1.data_type() == DataType::QASYMM8_SIGNED && input2.data_type() == DataType::QASYMM8_SIGNED && output.data_type() == DataType::QASYMM8_SIGNED) - && !(input1.data_type() == DataType::QSYMM16 && input2.data_type() == DataType::QSYMM16 && output.data_type() == DataType::QSYMM16) - && !(input1.data_type() == DataType::U8 && input2.data_type() == DataType::U8 && output.data_type() == DataType::S16) - && !(input1.data_type() == DataType::U8 && input2.data_type() == DataType::S16 && output.data_type() == DataType::S16) - && !(input1.data_type() == DataType::S16 && input2.data_type() == DataType::U8 && output.data_type() == DataType::S16) - && !(input1.data_type() == DataType::S16 && input2.data_type() == DataType::S16 && output.data_type() == DataType::S16) - && !(input1.data_type() == DataType::F32 && input2.data_type() == DataType::F32 && output.data_type() == DataType::F32) - && !(input1.data_type() == DataType::F16 && input2.data_type() == DataType::F16 && output.data_type() == DataType::F16), - "You called subtract with the wrong image formats"); - - ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, output.tensor_shape(), 0), - "Wrong shape for output"); - } - return Status{}; -} -} // namespace - -NEArithmeticSubtractionKernel::NEArithmeticSubtractionKernel() - : _func(nullptr), _input1(nullptr), _input2(nullptr), _output(nullptr), _policy(ConvertPolicy::WRAP) -{ -} - -void NEArithmeticSubtractionKernel::configure(const ITensor *input1, const ITensor *input2, ITensor *output, ConvertPolicy policy) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output); - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(*input1->info(), *input2->info(), *output->info(), policy)); - - _input1 = input1; - _input2 = input2; - _output = output; - _policy = policy; - - const std::pair<TensorShape, ValidRegion> broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(*input1->info(), *input2->info()); - const TensorShape &out_shape = broadcast_pair.first; - const ValidRegion &valid_region = broadcast_pair.second; - - // Auto initialize output if not initialized - set_shape_if_empty(*output->info(), out_shape); - - switch(input1->info()->data_type()) - { - case DataType::U8: - if(input2->info()->data_type() == DataType::U8 && output->info()->data_type() == DataType::U8) - { - _func = &sub_same<uint8_t>; - } - else if(input2->info()->data_type() == DataType::U8 && output->info()->data_type() == DataType::S16) - { - _func = &sub_U8_U8_S16; - } - else - { - _func = &sub_U8_S16_S16; - } - break; - case DataType::QASYMM8: - _func = &sub_quantized<uint8_t>; - set_data_type_if_unknown(*output->info(), DataType::QASYMM8); - break; - case DataType::QASYMM8_SIGNED: - _func = &sub_quantized<int8_t>; - set_data_type_if_unknown(*output->info(), DataType::QASYMM8_SIGNED); - break; - case DataType::S16: - if(input2->info()->data_type() == DataType::U8) - { - _func = &sub_S16_U8_S16; - } - else - { - _func = &sub_same<int16_t>; - } - set_format_if_unknown(*output->info(), Format::S16); - break; - case DataType::QSYMM16: - _func = &sub_QSYMM16_QSYMM16_QSYMM16; - set_data_type_if_unknown(*output->info(), DataType::QSYMM16); - break; -#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC - case DataType::F16: - _func = &sub_same<float16_t>; - set_format_if_unknown(*output->info(), Format::F16); - break; -#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ - case DataType::F32: - _func = &sub_same<float>; - set_format_if_unknown(*output->info(), Format::F32); - break; - default: - _func = nullptr; - } - - // NEArithmeticSubtractionKernel doesn't need padding so update_window_and_padding() can be skipped - Coordinates coord; - coord.set_num_dimensions(output->info()->num_dimensions()); - output->info()->set_valid_region(valid_region); - Window win = calculate_max_window(valid_region, Steps()); - - INEKernel::configure(win); -} - -Status NEArithmeticSubtractionKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy) -{ - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output); - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(*input1, *input2, *output, policy)); - - return Status{}; -} - -void NEArithmeticSubtractionKernel::run(const Window &window, const ThreadInfo &info) -{ - ARM_COMPUTE_UNUSED(info); - ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); - ARM_COMPUTE_ERROR_ON(_func == nullptr); - - (*_func)(_input1, _input2, _output, window, (_policy == ConvertPolicy::SATURATE)); -} -} // namespace arm_compute |