Make Sub kernel and operator stateless
- Rename NEArithmeticSubstractionKernel to CpuSubKernel and move files appropriately
- Add CpuSub under src/runtime/cpu/operators
Partially resolves: COMPMID-4007
Signed-off-by: Sheri Zhang <sheri.zhang@arm.com>
Change-Id: I4754ca9101d82dccacca744be6d069764a9c6b55
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4868
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/core/NEON/NEKernels.h b/src/core/NEON/NEKernels.h
index f20ecc1..a678a86 100644
--- a/src/core/NEON/NEKernels.h
+++ b/src/core/NEON/NEKernels.h
@@ -27,7 +27,6 @@
/* Header regrouping all the NEON kernels */
#include "src/core/NEON/kernels/NEAbsoluteDifferenceKernel.h"
#include "src/core/NEON/kernels/NEAccumulateKernel.h"
-#include "src/core/NEON/kernels/NEArithmeticSubtractionKernel.h"
#include "src/core/NEON/kernels/NEBatchNormalizationLayerKernel.h"
#include "src/core/NEON/kernels/NEBatchToSpaceLayerKernel.h"
#include "src/core/NEON/kernels/NEBitwiseAndKernel.h"
diff --git a/src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp b/src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp
deleted file mode 100644
index 187e97d..0000000
--- a/src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp
+++ /dev/null
@@ -1,833 +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 "src/core/NEON/kernels/NEArithmeticSubtractionKernel.h"
-
-#include "arm_compute/core/TensorInfo.h"
-#include "arm_compute/core/Validate.h"
-#include "src/core/CPP/Validate.h"
-#include "src/core/NEON/NEAsymm.h"
-#include "src/core/NEON/NESymm.h"
-#include "src/core/NEON/wrapper/wrapper.h"
-#include "src/core/helpers/AutoConfiguration.h"
-#include "src/core/helpers/WindowHelpers.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 = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x();
-
- 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 = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x();
-
- 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 invvscaleo = vdupq_n_f32(1.f / oq_info.scale);
- 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();
- const float32x4_t vscale1 = is_broadcast_input_2 ? vdupq_n_f32(iq1_info.scale) : vdupq_n_f32(iq2_info.scale);
- const float32x4_t vscale2 = is_broadcast_input_2 ? vdupq_n_f32(iq2_info.scale) : vdupq_n_f32(iq1_info.scale);
- const int32x4_t voffset1 = is_broadcast_input_2 ? vdupq_n_s32(iq1_info.offset) : vdupq_n_s32(iq2_info.offset);
- const int32x4_t voffset2 = is_broadcast_input_2 ? vdupq_n_s32(iq2_info.offset) : vdupq_n_s32(iq1_info.offset);
-
- // 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),
- }
- };
-
- // 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;
- const float bfs = static_cast<int32_t>(broadcast_value - broadcast_qinfo.offset) * broadcast_qinfo.scale;
- *(output_ptr + x) = quantize<T>(is_broadcast_input_2 ? afs - bfs : bfs - afs, out->info()->quantization_info());
- }
- },
- broadcast_input, non_broadcast_input, output);
- }
- else
- {
- const float32x4_t vscale1 = vdupq_n_f32(iq1_info.scale);
- const float32x4_t vscale2 = vdupq_n_f32(iq2_info.scale);
- const int32x4_t voffset1 = vdupq_n_s32(iq1_info.offset);
- const int32x4_t voffset2 = vdupq_n_s32(iq2_info.offset);
-
- // 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 = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x();
-
- 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::S32, 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::S32, 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::S32, 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::S32 && input2.data_type() == DataType::S32)
- && !(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 quantized");
-
- // 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::S32 && input2.data_type() == DataType::S32 && output.data_type() == DataType::S32)
- && !(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), _policy(ConvertPolicy::WRAP)
-{
-}
-
-void NEArithmeticSubtractionKernel::configure(const ITensorInfo *input1, const ITensorInfo *input2, ITensorInfo *output, ConvertPolicy policy)
-{
- ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(*input1, *input2, *output, policy));
-
- _policy = policy;
-
- const std::pair<TensorShape, ValidRegion> broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(*input1, *input2);
- 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, out_shape);
-
- switch(input1->data_type())
- {
- case DataType::U8:
- if(input2->data_type() == DataType::U8 && output->data_type() == DataType::U8)
- {
- _func = &sub_same<uint8_t>;
- }
- else if(input2->data_type() == DataType::U8 && output->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, DataType::QASYMM8);
- break;
- case DataType::QASYMM8_SIGNED:
- _func = &sub_quantized<int8_t>;
- set_data_type_if_unknown(*output, DataType::QASYMM8_SIGNED);
- break;
- case DataType::S16:
- if(input2->data_type() == DataType::U8)
- {
- _func = &sub_S16_U8_S16;
- }
- else
- {
- _func = &sub_same<int16_t>;
- }
- set_format_if_unknown(*output, Format::S16);
- break;
- case DataType::QSYMM16:
- _func = &sub_QSYMM16_QSYMM16_QSYMM16;
- set_data_type_if_unknown(*output, DataType::QSYMM16);
- break;
- case DataType::S32:
- _func = &sub_same<int32_t>;
- set_format_if_unknown(*output, Format::S32);
- break;
-#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
- case DataType::F16:
- _func = &sub_same<float16_t>;
- set_format_if_unknown(*output, Format::F16);
- break;
-#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
- case DataType::F32:
- _func = &sub_same<float>;
- set_format_if_unknown(*output, 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->num_dimensions());
- output->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_op(ITensorPack &tensors, 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);
- // Dispatch kernel
- (*_func)(tensors.get_const_tensor(TensorType::ACL_SRC_0),
- tensors.get_const_tensor(TensorType::ACL_SRC_1),
- tensors.get_tensor(TensorType::ACL_DST),
- window,
- (_policy == ConvertPolicy::SATURATE));
-}
-} // namespace arm_compute
diff --git a/src/core/NEON/kernels/NEArithmeticSubtractionKernel.h b/src/core/NEON/kernels/NEArithmeticSubtractionKernel.h
deleted file mode 100644
index 69952d6..0000000
--- a/src/core/NEON/kernels/NEArithmeticSubtractionKernel.h
+++ /dev/null
@@ -1,118 +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.
- */
-#ifndef ARM_COMPUTE_NEARITHMETICSUBTRACTIONKERNEL_H
-#define ARM_COMPUTE_NEARITHMETICSUBTRACTIONKERNEL_H
-
-#include "arm_compute/core/Types.h"
-#include "src/core/NEON/INEKernel.h"
-
-namespace arm_compute
-{
-class ITensor;
-
-/** Interface for the kernel to perform subtraction between two tensors */
-class NEArithmeticSubtractionKernel : public INEKernel
-{
-public:
- const char *name() const override
- {
- return "NEArithmeticSubtractionKernel";
- }
- /** Default constructor */
- NEArithmeticSubtractionKernel();
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- NEArithmeticSubtractionKernel(const NEArithmeticSubtractionKernel &) = delete;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- NEArithmeticSubtractionKernel &operator=(const NEArithmeticSubtractionKernel &) = delete;
- /** Allow instances of this class to be moved */
- NEArithmeticSubtractionKernel(NEArithmeticSubtractionKernel &&) = default;
- /** Allow instances of this class to be moved */
- NEArithmeticSubtractionKernel &operator=(NEArithmeticSubtractionKernel &&) = default;
- /** Default destructor */
- ~NEArithmeticSubtractionKernel() = default;
-
- /** Initialise the kernel's input and output.
- *
- * Valid configurations (Input1,Input2) -> Output :
- *
- * - (U8,U8) -> U8
- * - (U8,U8) -> S16
- * - (QASYMM8, QASYMM8) -> QASYMM8
- * - (QASYMM8_SIGNED, QASYMM8_SIGNED) -> QASYMM8_SIGNED
- * - (S16,U8) -> S16
- * - (U8,S16) -> S16
- * - (S16,S16) -> S16
- * - (S32,S32) -> S32
- * - (F16,F16) -> F16
- * - (F32,F32) -> F32
- *
- * @param[in] input1 An input tensor. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/QSYMM16/S16/S32/F16/F32
- * @param[in] input2 An input tensor. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/QSYMM16/S16/S32/F16/F32
- * @param[out] output The output tensor. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/QSYMM16/S16/S32/F16/F32.
- * @param[in] policy Overflow policy. Convert policy cannot be WRAP if datatype is quantized.
- */
- void configure(const ITensorInfo *input1, const ITensorInfo *input2, ITensorInfo *output, ConvertPolicy policy);
- /** Static function to check if given info will lead to a valid configuration of @ref NEArithmeticSubtractionKernel
- *
- * Valid configurations (Input1,Input2) -> Output :
- *
- * - (U8,U8) -> U8
- * - (U8,U8) -> S16
- * - (QASYMM8, QASYMM8) -> QASYMM8
- * - (QASYMM8_SIGNED, QASYMM8_SIGNED) -> QASYMM8_SIGNED
- * - (S16,U8) -> S16
- * - (U8,S16) -> S16
- * - (S16,S16) -> S16
- * - (S32,S32) -> S32
- * - (F16,F16) -> F16
- * - (F32,F32) -> F32
- *
- * @param[in] input1 An input tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/QSYMM16/S16/S32/F16/F32
- * @param[in] input2 An input tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/QSYMM16/S16/S32/F16/F32
- * @param[in] output The output tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/QSYMM16/S16/S32/F16/F32.
- * @param[in] policy Policy to use to handle overflow. Convert policy cannot be WRAP if datatype is quantized.
- *
- * @return a status
- */
- static Status validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy);
-
- // Inherited methods overridden:
- void run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) override;
-
-private:
- /** Common signature for all the specialised sub functions
- *
- * @param[in] input1 An input tensor. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/QSYMM16/S16/S32/F16/F32
- * @param[in] input2 An input tensor. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/QSYMM16/S16/S32/F16/F32
- * @param[out] output The output tensor. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/QSYMM16/S16/S32/F16/F32.
- * @param[in] window Region on which to execute the kernel.
- * @param[in] is_sat Flag to indicate if the policy is SATURATE.
- */
- using SubFunction = void(const ITensor *input1, const ITensor *input2, ITensor *output, const Window &window, bool is_sat);
- /** Sub function to use for the particular tensor types passed to configure() */
- SubFunction *_func;
- ConvertPolicy _policy;
-};
-} // namespace arm_compute
-#endif /* ARM_COMPUTE_NEARITHMETICSUBTRACTIONKERNEL_H */
diff --git a/src/core/cpu/kernels/CpuSubKernel.cpp b/src/core/cpu/kernels/CpuSubKernel.cpp
new file mode 100644
index 0000000..a03dcf2
--- /dev/null
+++ b/src/core/cpu/kernels/CpuSubKernel.cpp
@@ -0,0 +1,251 @@
+/*
+ * Copyright (c) 2021 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 "src/core/cpu/kernels/CpuSubKernel.h"
+
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Validate.h"
+#include "src/core/CPP/Validate.h"
+#include "src/core/common/Registrars.h"
+#include "src/core/cpu/kernels/sub/neon/list.h"
+#include "src/core/helpers/AutoConfiguration.h"
+#include "src/core/helpers/WindowHelpers.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+namespace kernels
+{
+namespace
+{
+struct SubSelectorData
+{
+ DataType dt1;
+ DataType dt2;
+ DataType dt3;
+};
+
+using SubSelectorPtr = std::add_pointer<bool(const SubSelectorData &data)>::type;
+using SubKernelPtr = std::add_pointer<void(const ITensor *, const ITensor *, ITensor *, const ConvertPolicy &, const Window &)>::type;
+
+struct SubKernel
+{
+ const char *name;
+ const SubSelectorPtr is_selected;
+ SubKernelPtr ukernel;
+};
+
+static const SubKernel available_kernels[] =
+{
+ {
+ "sub_same_neon",
+ [](const SubSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == DataType::F32)); },
+ REGISTER_FP32_NEON(arm_compute::cpu::sub_same_neon<float>)
+ },
+#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC)
+ {
+ "sub_same_neon",
+ [](const SubSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == DataType::F16)); },
+ REGISTER_FP16_NEON(arm_compute::cpu::sub_same_neon<float16_t>)
+ },
+#endif /* defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) */
+ {
+ "sub_same_neon",
+ [](const SubSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == data.dt3) && (data.dt1 == DataType::U8)); },
+ REGISTER_INTEGER_NEON(arm_compute::cpu::sub_same_neon<uint8_t>)
+ },
+ {
+ "sub_same_neon",
+ [](const SubSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == data.dt3) && (data.dt1 == DataType::S16)); },
+ REGISTER_INTEGER_NEON(arm_compute::cpu::sub_same_neon<int16_t>)
+ },
+ {
+ "sub_same_neon",
+ [](const SubSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == data.dt3) && (data.dt1 == DataType::S32)); },
+ REGISTER_INTEGER_NEON(arm_compute::cpu::sub_same_neon<int32_t>)
+ },
+ {
+ "sub_u8_s16_s16_neon",
+ [](const SubSelectorData & data) { return ((data.dt1 == DataType::U8) && (data.dt2 == DataType::S16)); },
+ REGISTER_INTEGER_NEON(arm_compute::cpu::sub_u8_s16_s16_neon)
+ },
+ {
+ "sub_s16_u8_s16_neon",
+ [](const SubSelectorData & data) { return ((data.dt1 == DataType::S16) && (data.dt2 == DataType::U8)); },
+ REGISTER_INTEGER_NEON(arm_compute::cpu::sub_s16_u8_s16_neon)
+ },
+ {
+ "sub_u8_u8_s16_neon",
+ [](const SubSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt3 == DataType::S16)); },
+ REGISTER_INTEGER_NEON(arm_compute::cpu::sub_u8_u8_s16_neon)
+ },
+ {
+ "sub_qasymm8_neon",
+ [](const SubSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == DataType::QASYMM8)); },
+ REGISTER_QASYMM8_NEON(arm_compute::cpu::sub_qasymm8_neon)
+ },
+ {
+ "sub_qasymm8_signed_neon",
+ [](const SubSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == DataType::QASYMM8_SIGNED)); },
+ REGISTER_QASYMM8_SIGNED_NEON(arm_compute::cpu::sub_qasymm8_signed_neon)
+ },
+ {
+ "sub_qsymm16_neon",
+ [](const SubSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == DataType::QSYMM16)); },
+ REGISTER_QSYMM16_NEON(arm_compute::cpu::sub_qsymm16_neon)
+ },
+};
+
+/** Micro-kernel selector
+ *
+ * @param[in] data Selection data passed to help pick the appropriate micro-kernel
+ *
+ * @return A matching micro-kernel else nullptr
+ */
+const SubKernel *get_implementation(DataType dt1, DataType dt2, DataType dt3)
+{
+ for(const auto &uk : available_kernels)
+ {
+ if(uk.is_selected({ dt1, dt2, dt3 }))
+ {
+ return &uk;
+ }
+ }
+ return nullptr;
+}
+
+inline Status validate_arguments(const ITensorInfo &src0, const ITensorInfo &src1, const ITensorInfo &dst, ConvertPolicy policy)
+{
+ ARM_COMPUTE_UNUSED(policy);
+ ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(&src0);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&src0, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QSYMM16, DataType::S16, DataType::S32, DataType::F16,
+ DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&src1, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QSYMM16, DataType::S16, DataType::S32, DataType::F16,
+ DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&dst, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QSYMM16, DataType::S16, DataType::S32, DataType::F16,
+ DataType::F32);
+
+ const auto *uk = get_implementation(src0.data_type(), src1.data_type(), dst.data_type());
+ ARM_COMPUTE_RETURN_ERROR_ON(uk == nullptr || uk->ukernel == nullptr);
+
+ const TensorShape out_shape = TensorShape::broadcast_shape(src0.tensor_shape(), src1.tensor_shape());
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible");
+
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(
+ !(src0.data_type() == DataType::U8 && src1.data_type() == DataType::U8)
+ && !(src0.data_type() == DataType::QASYMM8 && src1.data_type() == DataType::QASYMM8)
+ && !(src0.data_type() == DataType::QASYMM8_SIGNED && src1.data_type() == DataType::QASYMM8_SIGNED)
+ && !(src0.data_type() == DataType::QSYMM16 && src1.data_type() == DataType::QSYMM16)
+ && !(src0.data_type() == DataType::U8 && src1.data_type() == DataType::U8)
+ && !(src0.data_type() == DataType::U8 && src1.data_type() == DataType::S16)
+ && !(src0.data_type() == DataType::S16 && src1.data_type() == DataType::U8)
+ && !(src0.data_type() == DataType::S16 && src1.data_type() == DataType::S16)
+ && !(src0.data_type() == DataType::S32 && src1.data_type() == DataType::S32)
+ && !(src0.data_type() == DataType::F32 && src1.data_type() == DataType::F32)
+ && !(src0.data_type() == DataType::F16 && src1.data_type() == DataType::F16),
+ "You called subtract with the wrong image formats");
+
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(
+ (src0.data_type() == DataType::QASYMM8_SIGNED && src1.data_type() == DataType::QASYMM8_SIGNED && policy == ConvertPolicy::WRAP)
+ || (src0.data_type() == DataType::QASYMM8 && src1.data_type() == DataType::QASYMM8 && policy == ConvertPolicy::WRAP)
+ || (src0.data_type() == DataType::QSYMM16 && src1.data_type() == DataType::QSYMM16 && policy == ConvertPolicy::WRAP),
+ "Convert policy cannot be WRAP if datatype is quantized");
+
+ // Validate in case of configured dst
+ if(dst.total_size() > 0)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(
+ !(src0.data_type() == DataType::U8 && src1.data_type() == DataType::U8 && dst.data_type() == DataType::U8)
+ && !(src0.data_type() == DataType::QASYMM8 && src1.data_type() == DataType::QASYMM8 && dst.data_type() == DataType::QASYMM8)
+ && !(src0.data_type() == DataType::QASYMM8_SIGNED && src1.data_type() == DataType::QASYMM8_SIGNED && dst.data_type() == DataType::QASYMM8_SIGNED)
+ && !(src0.data_type() == DataType::QSYMM16 && src1.data_type() == DataType::QSYMM16 && dst.data_type() == DataType::QSYMM16)
+ && !(src0.data_type() == DataType::U8 && src1.data_type() == DataType::U8 && dst.data_type() == DataType::S16)
+ && !(src0.data_type() == DataType::U8 && src1.data_type() == DataType::S16 && dst.data_type() == DataType::S16)
+ && !(src0.data_type() == DataType::S16 && src1.data_type() == DataType::U8 && dst.data_type() == DataType::S16)
+ && !(src0.data_type() == DataType::S16 && src1.data_type() == DataType::S16 && dst.data_type() == DataType::S16)
+ && !(src0.data_type() == DataType::S32 && src1.data_type() == DataType::S32 && dst.data_type() == DataType::S32)
+ && !(src0.data_type() == DataType::F32 && src1.data_type() == DataType::F32 && dst.data_type() == DataType::F32)
+ && !(src0.data_type() == DataType::F16 && src1.data_type() == DataType::F16 && dst.data_type() == DataType::F16),
+ "You called subtract with the wrong image formats");
+
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, dst.tensor_shape(), 0),
+ "Wrong shape for dst");
+ }
+ return Status{};
+}
+} // namespace
+
+void CpuSubKernel::configure(const ITensorInfo *src0, const ITensorInfo *src1, ITensorInfo *dst, ConvertPolicy policy)
+{
+ ARM_COMPUTE_ERROR_ON_NULLPTR(src0, src1, dst);
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(*src0, *src1, *dst, policy));
+
+ const std::pair<TensorShape, ValidRegion> broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(*src0, *src1);
+ const TensorShape &out_shape = broadcast_pair.first;
+ const ValidRegion &valid_region = broadcast_pair.second;
+
+ // Auto initialize dst if not initialized
+ set_shape_if_empty(*dst, out_shape);
+
+ _policy = policy;
+
+ // CpuSubKernel doesn't need padding so update_window_and_padding() can be skipped
+ Coordinates coord;
+ coord.set_num_dimensions(dst->num_dimensions());
+ dst->set_valid_region(valid_region);
+ Window win = calculate_max_window(valid_region, Steps());
+
+ ICpuKernel::configure(win);
+}
+
+Status CpuSubKernel::validate(const ITensorInfo *src0, const ITensorInfo *src1, const ITensorInfo *dst, ConvertPolicy policy)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src0, src1, dst);
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(*src0, *src1, *dst, policy));
+
+ return Status{};
+}
+
+void CpuSubKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info)
+{
+ ARM_COMPUTE_UNUSED(info);
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICpuKernel::window(), window);
+
+ const ITensor *src0 = tensors.get_const_tensor(TensorType::ACL_SRC_0);
+ const ITensor *src1 = tensors.get_const_tensor(TensorType::ACL_SRC_1);
+ ITensor *dst = tensors.get_tensor(TensorType::ACL_DST);
+
+ // Dispatch kernel
+ const auto *uk = get_implementation(src0->info()->data_type(), src1->info()->data_type(), dst->info()->data_type());
+ uk->ukernel(src0, src1, dst, _policy, window);
+}
+
+const char *CpuSubKernel::name() const
+{
+ return "CpuSubKernel";
+}
+} // namespace kernels
+} // namespace cpu
+} // namespace arm_compute
diff --git a/src/core/cpu/kernels/CpuSubKernel.h b/src/core/cpu/kernels/CpuSubKernel.h
new file mode 100644
index 0000000..da114b6
--- /dev/null
+++ b/src/core/cpu/kernels/CpuSubKernel.h
@@ -0,0 +1,98 @@
+/*
+ * Copyright (c) 2016-2021 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.
+ */
+#ifndef ARM_COMPUTE_CPU_SUB_KERNEL_H
+#define ARM_COMPUTE_CPU_SUB_KERNEL_H
+
+#include "src/core/common/Macros.h"
+#include "src/core/cpu/ICpuKernel.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+namespace kernels
+{
+/** Interface for the kernel to perform subtraction between two tensors */
+class CpuSubKernel : public ICpuKernel
+{
+public:
+ CpuSubKernel() = default;
+ ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(CpuSubKernel);
+
+ /** Initialise the kernel's src and dst.
+ *
+ * Valid configurations (src0,src1) -> dst :
+ *
+ * - (U8,U8) -> U8
+ * - (U8,U8) -> S16
+ * - (QASYMM8, QASYMM8) -> QASYMM8
+ * - (QASYMM8_SIGNED, QASYMM8_SIGNED) -> QASYMM8_SIGNED
+ * - (S16,U8) -> S16
+ * - (U8,S16) -> S16
+ * - (S16,S16) -> S16
+ * - (S32,S32) -> S32
+ * - (F16,F16) -> F16
+ * - (F32,F32) -> F32
+ *
+ * @param[in] src0 An input tensor. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/QSYMM16/S16/S32/F16/F32
+ * @param[in] src1 An input tensor. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/QSYMM16/S16/S32/F16/F32
+ * @param[out] dst The dst tensor. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/QSYMM16/S16/S32/F16/F32.
+ * @param[in] policy Overflow policy. Convert policy cannot be WRAP if datatype is quantized.
+ */
+ void configure(const ITensorInfo *src0, const ITensorInfo *src1, ITensorInfo *dst, ConvertPolicy policy);
+ /** Static function to check if given info will lead to a valid configuration of @ref CpuSubKernel
+ *
+ * Valid configurations (src0,src1) -> dst :
+ *
+ * - (U8,U8) -> U8
+ * - (U8,U8) -> S16
+ * - (QASYMM8, QASYMM8) -> QASYMM8
+ * - (QASYMM8_SIGNED, QASYMM8_SIGNED) -> QASYMM8_SIGNED
+ * - (S16,U8) -> S16
+ * - (U8,S16) -> S16
+ * - (S16,S16) -> S16
+ * - (S32,S32) -> S32
+ * - (F16,F16) -> F16
+ * - (F32,F32) -> F32
+ *
+ * @param[in] src0 An input tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/QSYMM16/S16/S32/F16/F32
+ * @param[in] src1 An input tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/QSYMM16/S16/S32/F16/F32
+ * @param[in] dst The dst tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/QSYMM16/S16/S32/F16/F32.
+ * @param[in] policy Policy to use to handle overflow. Convert policy cannot be WRAP if datatype is quantized.
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *src0, const ITensorInfo *src1, const ITensorInfo *dst, ConvertPolicy policy);
+
+ // Inherited methods overridden:
+ void run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) override;
+ const char *name() const override;
+
+private:
+ ConvertPolicy _policy{};
+};
+} // namespace kernels
+} // namespace cpu
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_CPU_SUB_KERNEL_H */
diff --git a/src/core/cpu/kernels/sub/neon/integer.cpp b/src/core/cpu/kernels/sub/neon/integer.cpp
new file mode 100644
index 0000000..bba73df
--- /dev/null
+++ b/src/core/cpu/kernels/sub/neon/integer.cpp
@@ -0,0 +1,183 @@
+/*
+ * Copyright (c) 2021 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/Helpers.h"
+#include "arm_compute/core/ITensor.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/utils/misc/Traits.h"
+#include "src/core/NEON/wrapper/wrapper.h"
+#include "src/core/helpers/WindowHelpers.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+namespace
+{
+void sub_s16_u8_s16_impl(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window, bool is_swapped)
+{
+ // Create input windows
+ Window win = window;
+ Window input1_win = window.broadcast_if_dimension_le_one(src0->info()->tensor_shape());
+ Window input2_win = window.broadcast_if_dimension_le_one(src1->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(src0, input1_win);
+ Iterator input2(src1, input2_win);
+ Iterator output(dst, 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(policy == ConvertPolicy::WRAP)
+ {
+ // 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_neon(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window)
+{
+ sub_s16_u8_s16_impl(src1, src0, dst, policy, window, false);
+}
+
+void sub_u8_s16_s16_neon(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window)
+{
+ // Swap arguments
+ sub_s16_u8_s16_impl(src1, src0, dst, policy, window, true);
+}
+
+void sub_u8_u8_s16_neon(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window)
+{
+ // Create input windows
+ Window win = window;
+ Window input1_win = window.broadcast_if_dimension_le_one(src0->info()->tensor_shape());
+ Window input2_win = window.broadcast_if_dimension_le_one(src1->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(src0, input1_win);
+ Iterator input2(src1, input2_win);
+ Iterator output(dst, 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(policy == ConvertPolicy::WRAP)
+ {
+ // 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);
+}
+
+} // namespace cpu
+} // namespace arm_compute
\ No newline at end of file
diff --git a/src/core/cpu/kernels/sub/neon/list.h b/src/core/cpu/kernels/sub/neon/list.h
new file mode 100644
index 0000000..d568582
--- /dev/null
+++ b/src/core/cpu/kernels/sub/neon/list.h
@@ -0,0 +1,162 @@
+/*
+ * Copyright (c) 2021 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.
+ */
+#ifndef SRC_CORE_NEON_KERNELS_SUB_LIST_H
+#define SRC_CORE_NEON_KERNELS_SUB_LIST_H
+
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/utils/misc/Traits.h"
+#include "src/core/NEON/wrapper/wrapper.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+#define DECLARE_SUB_KERNEL(func_name) \
+ void func_name(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window)
+
+DECLARE_SUB_KERNEL(sub_qasymm8_neon);
+DECLARE_SUB_KERNEL(sub_qasymm8_signed_neon);
+DECLARE_SUB_KERNEL(sub_qsymm16_neon);
+DECLARE_SUB_KERNEL(sub_s16_u8_s16_neon);
+DECLARE_SUB_KERNEL(sub_u8_s16_s16_neon);
+DECLARE_SUB_KERNEL(sub_u8_u8_s16_neon);
+
+#undef DECLARE_SUB_KERNEL
+
+template <typename T>
+void sub_same_neon(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window)
+{
+ /** NEON vector tag type. */
+ using ExactTagType = typename wrapper::traits::neon_bitvector_tag_t<T, wrapper::traits::BitWidth::W128>;
+
+ bool is_sat = policy == ConvertPolicy::SATURATE;
+
+ // Create input windows
+ Window input1_win = window.broadcast_if_dimension_le_one(src0->info()->tensor_shape());
+ Window input2_win = window.broadcast_if_dimension_le_one(src1->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 = src0->info()->tensor_shape().x() != src1->info()->tensor_shape().x();
+
+ Iterator input1(src0, window.broadcast_if_dimension_le_one(src0->info()->tensor_shape()));
+ Iterator input2(src1, window.broadcast_if_dimension_le_one(src1->info()->tensor_shape()));
+ Iterator output(dst, 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 ? src1 : src0;
+ const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? src1 : src0;
+
+ // 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(dst, 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(src0, input1_win);
+ Iterator input2(src1, input2_win);
+ Iterator output(dst, 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);
+ }
+}
+} // namespace cpu
+} // namespace arm_compute
+#endif // SRC_CORE_NEON_KERNELS_SUB_LIST_H
\ No newline at end of file
diff --git a/src/core/cpu/kernels/sub/neon/qasymm8.cpp b/src/core/cpu/kernels/sub/neon/qasymm8.cpp
new file mode 100644
index 0000000..8f4cd8b
--- /dev/null
+++ b/src/core/cpu/kernels/sub/neon/qasymm8.cpp
@@ -0,0 +1,230 @@
+/*
+ * Copyright (c) 2021 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/Helpers.h"
+#include "arm_compute/core/ITensor.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/utils/misc/Traits.h"
+#include "src/core/NEON/wrapper/intrinsics/intrinsics.h"
+#include "src/core/helpers/WindowHelpers.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+void sub_qasymm8_neon(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window)
+{
+ ARM_COMPUTE_UNUSED(policy);
+
+ // Create input windows
+ Window input1_win = window.broadcast_if_dimension_le_one(src0->info()->tensor_shape());
+ Window input2_win = window.broadcast_if_dimension_le_one(src1->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 = src0->info()->tensor_shape().x() != src1->info()->tensor_shape().x();
+
+ const UniformQuantizationInfo iq1_info = src0->info()->quantization_info().uniform();
+ const UniformQuantizationInfo iq2_info = src1->info()->quantization_info().uniform();
+ const UniformQuantizationInfo oq_info = dst->info()->quantization_info().uniform();
+
+ const float32x4_t invvscaleo = vdupq_n_f32(1.f / oq_info.scale);
+ 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 ? src1 : src0;
+ const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? src1 : src0;
+ const UniformQuantizationInfo broadcast_qinfo = broadcast_tensor->info()->quantization_info().uniform();
+ const UniformQuantizationInfo non_broadcast_qinfo = non_broadcast_tensor->info()->quantization_info().uniform();
+ const float32x4_t vscale1 = is_broadcast_input_2 ? vdupq_n_f32(iq1_info.scale) : vdupq_n_f32(iq2_info.scale);
+ const float32x4_t vscale2 = is_broadcast_input_2 ? vdupq_n_f32(iq2_info.scale) : vdupq_n_f32(iq1_info.scale);
+ const int32x4_t voffset1 = is_broadcast_input_2 ? vdupq_n_s32(iq1_info.offset) : vdupq_n_s32(iq2_info.offset);
+ const int32x4_t voffset2 = is_broadcast_input_2 ? vdupq_n_s32(iq2_info.offset) : vdupq_n_s32(iq1_info.offset);
+
+ // 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(dst, win);
+
+ execute_window_loop(win, [&](const Coordinates &)
+ {
+ const auto non_broadcast_input_ptr = reinterpret_cast<const uint8_t *>(non_broadcast_input.ptr());
+ const auto output_ptr = reinterpret_cast<uint8_t *>(output.ptr());
+
+ const auto broadcast_value = *reinterpret_cast<const uint8_t *>(broadcast_input.ptr());
+ const auto broadcast_value_vec = wrapper::vdup_n(static_cast<uint8_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),
+ }
+ };
+
+ // 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 = vqmovun_s16(vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1])));
+ const auto pb = vqmovun_s16(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;
+ const float bfs = static_cast<int32_t>(broadcast_value - broadcast_qinfo.offset) * broadcast_qinfo.scale;
+ *(output_ptr + x) = quantize_qasymm8(is_broadcast_input_2 ? afs - bfs : bfs - afs, dst->info()->quantization_info());
+ }
+ },
+ broadcast_input, non_broadcast_input, output);
+ }
+ else
+ {
+ const float32x4_t vscale1 = vdupq_n_f32(iq1_info.scale);
+ const float32x4_t vscale2 = vdupq_n_f32(iq2_info.scale);
+ const int32x4_t voffset1 = vdupq_n_s32(iq1_info.offset);
+ const int32x4_t voffset2 = vdupq_n_s32(iq2_info.offset);
+
+ // 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(src0, input1_win);
+ Iterator input2(src1, input2_win);
+ Iterator output(dst, win);
+
+ 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<uint8_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 = vqmovun_s16(vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1])));
+ const auto pb = vqmovun_s16(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_qasymm8((afs - bfs), dst->info()->quantization_info());
+ }
+ },
+ input1, input2, output);
+ }
+}
+
+} // namespace cpu
+} // namespace arm_compute
\ No newline at end of file
diff --git a/src/core/cpu/kernels/sub/neon/qasymm8_signed.cpp b/src/core/cpu/kernels/sub/neon/qasymm8_signed.cpp
new file mode 100644
index 0000000..2c9e411
--- /dev/null
+++ b/src/core/cpu/kernels/sub/neon/qasymm8_signed.cpp
@@ -0,0 +1,229 @@
+/*
+ * Copyright (c) 2021 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/Helpers.h"
+#include "arm_compute/core/ITensor.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/utils/misc/Traits.h"
+#include "src/core/NEON/wrapper/intrinsics/intrinsics.h"
+#include "src/core/helpers/WindowHelpers.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+void sub_qasymm8_signed_neon(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window)
+{
+ ARM_COMPUTE_UNUSED(policy);
+
+ // Create input windows
+ Window input1_win = window.broadcast_if_dimension_le_one(src0->info()->tensor_shape());
+ Window input2_win = window.broadcast_if_dimension_le_one(src1->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 = src0->info()->tensor_shape().x() != src1->info()->tensor_shape().x();
+
+ const UniformQuantizationInfo iq1_info = src0->info()->quantization_info().uniform();
+ const UniformQuantizationInfo iq2_info = src1->info()->quantization_info().uniform();
+ const UniformQuantizationInfo oq_info = dst->info()->quantization_info().uniform();
+
+ const float32x4_t invvscaleo = vdupq_n_f32(1.f / oq_info.scale);
+ 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 ? src1 : src0;
+ const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? src1 : src0;
+ const UniformQuantizationInfo broadcast_qinfo = broadcast_tensor->info()->quantization_info().uniform();
+ const UniformQuantizationInfo non_broadcast_qinfo = non_broadcast_tensor->info()->quantization_info().uniform();
+ const float32x4_t vscale1 = is_broadcast_input_2 ? vdupq_n_f32(iq1_info.scale) : vdupq_n_f32(iq2_info.scale);
+ const float32x4_t vscale2 = is_broadcast_input_2 ? vdupq_n_f32(iq2_info.scale) : vdupq_n_f32(iq1_info.scale);
+ const int32x4_t voffset1 = is_broadcast_input_2 ? vdupq_n_s32(iq1_info.offset) : vdupq_n_s32(iq2_info.offset);
+ const int32x4_t voffset2 = is_broadcast_input_2 ? vdupq_n_s32(iq2_info.offset) : vdupq_n_s32(iq1_info.offset);
+
+ // 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(dst, win);
+
+ execute_window_loop(win, [&](const Coordinates &)
+ {
+ const auto non_broadcast_input_ptr = reinterpret_cast<const int8_t *>(non_broadcast_input.ptr());
+ const auto output_ptr = reinterpret_cast<int8_t *>(output.ptr());
+
+ const auto broadcast_value = *reinterpret_cast<const int8_t *>(broadcast_input.ptr());
+ const auto broadcast_value_vec = wrapper::vdup_n(static_cast<int8_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),
+ }
+ };
+
+ // 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 = vqmovn_s16(vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1])));
+ const auto pb = vqmovn_s16(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;
+ const float bfs = static_cast<int32_t>(broadcast_value - broadcast_qinfo.offset) * broadcast_qinfo.scale;
+ *(output_ptr + x) = quantize_qasymm8_signed(is_broadcast_input_2 ? afs - bfs : bfs - afs, dst->info()->quantization_info());
+ }
+ },
+ broadcast_input, non_broadcast_input, output);
+ }
+ else
+ {
+ const float32x4_t vscale1 = vdupq_n_f32(iq1_info.scale);
+ const float32x4_t vscale2 = vdupq_n_f32(iq2_info.scale);
+ const int32x4_t voffset1 = vdupq_n_s32(iq1_info.offset);
+ const int32x4_t voffset2 = vdupq_n_s32(iq2_info.offset);
+
+ // 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(src0, input1_win);
+ Iterator input2(src1, input2_win);
+ Iterator output(dst, win);
+
+ execute_window_loop(win, [&](const Coordinates &)
+ {
+ const auto input1_ptr = reinterpret_cast<const int8_t *>(input1.ptr());
+ const auto input2_ptr = reinterpret_cast<const int8_t *>(input2.ptr());
+ const auto output_ptr = reinterpret_cast<int8_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 = vqmovn_s16(vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1])));
+ const auto pb = vqmovn_s16(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_qasymm8_signed((afs - bfs), dst->info()->quantization_info());
+ }
+ },
+ input1, input2, output);
+ }
+}
+} // namespace cpu
+} // namespace arm_compute
\ No newline at end of file
diff --git a/src/core/cpu/kernels/sub/neon/qsymm16.cpp b/src/core/cpu/kernels/sub/neon/qsymm16.cpp
new file mode 100644
index 0000000..4dfdc0e
--- /dev/null
+++ b/src/core/cpu/kernels/sub/neon/qsymm16.cpp
@@ -0,0 +1,201 @@
+/*
+ * Copyright (c) 2021 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/Helpers.h"
+#include "arm_compute/core/ITensor.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/utils/misc/Traits.h"
+#include "src/core/NEON/wrapper/intrinsics/intrinsics.h"
+#include "src/core/helpers/WindowHelpers.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+void sub_qsymm16_neon(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window)
+{
+ ARM_COMPUTE_UNUSED(policy);
+
+ // Create input windows
+ Window input1_win = window.broadcast_if_dimension_le_one(src0->info()->tensor_shape());
+ Window input2_win = window.broadcast_if_dimension_le_one(src1->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 = src0->info()->tensor_shape().x() != src1->info()->tensor_shape().x();
+
+ const UniformQuantizationInfo iq1_info = src0->info()->quantization_info().uniform();
+ const UniformQuantizationInfo iq2_info = src1->info()->quantization_info().uniform();
+ const UniformQuantizationInfo oq_info = dst->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 ? src1 : src0;
+ const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? src1 : src0;
+ 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(dst, 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(src0, input1_win);
+ Iterator input2(src1, input2_win);
+ Iterator output(dst, 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), dst->info()->quantization_info());
+ }
+ },
+ input1, input2, output);
+ }
+}
+} // namespace cpu
+} // namespace arm_compute
\ No newline at end of file