COMPMID-3874: Create ArithmeticAddition SVE/SVE2
Change-Id: I4ec7561a7f6a42a22b8187968ae302dbe75023bc
Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4753
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/core/NEON/SVEMath.h b/src/core/NEON/SVEMath.h
index 490759c..2b30e20 100644
--- a/src/core/NEON/SVEMath.h
+++ b/src/core/NEON/SVEMath.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2020 Arm Limited.
+ * Copyright (c) 2020-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -36,7 +36,7 @@
{
/** Calculate exponent.
*
- * @param[in] pg Input reciprocal.
+ * @param[in] pg Input predicate.
* @param[in] val Input vector value in F32 format.
*
* @return The calculated exponent.
@@ -45,7 +45,7 @@
/** Calculate reciprocal.
*
- * @param[in] pg Input reciprocal.
+ * @param[in] pg Input predicate.
* @param[in] x Input value.
*
* @return The calculated reciprocal.
@@ -54,7 +54,7 @@
/** Calculate logarithm
*
- * @param[in] pg Input reciprocal.
+ * @param[in] pg Input predicate.
* @param[in] x Input vector value in F32 format.
*
* @return The calculated logarithm.
@@ -67,7 +67,7 @@
*
* @note We clamp x to [-5,5] to avoid overflowing issues.
*
- * @param[in] pg Input reciprocal.
+ * @param[in] pg Input predicate.
* @param[in] val Input vector value in F32 format.
*
* @return The calculated Hyperbolic Tangent.
@@ -80,7 +80,7 @@
*
* @note We clamp x to [-5,5] to avoid overflowing issues.
*
- * @param[in] pg Input reciprocal.
+ * @param[in] pg Input predicate.
* @param[in] val Input vector value in F16 format.
*
* @return The calculated Hyperbolic Tangent.
@@ -89,7 +89,7 @@
/** Calculate exponential
*
- * @param[in] pg Input reciprocal.
+ * @param[in] pg Input predicate.
* @param[in] x Input vector value in F16 format.
*
* @return The calculated exponent.
@@ -98,7 +98,7 @@
/** Calculate reciprocal.
*
- * @param[in] pg Input reciprocal.
+ * @param[in] pg Input predicate.
* @param[in] x Input value.
*
* @return The calculated reciprocal.
@@ -107,7 +107,7 @@
/** Calculate logarithm
*
- * @param[in] pg Input reciprocal.
+ * @param[in] pg Input predicate.
* @param[in] x Input vector value in F32 format.
*
* @return The calculated logarithm.
@@ -116,7 +116,7 @@
/** Calculate inverse square root.
*
- * @param[in] pg Input reciprocal.
+ * @param[in] pg Input predicate.
* @param[in] val Input value.
*
* @return The calculated inverse square root.
@@ -132,7 +132,7 @@
/** Calculate sine.
*
- * @param[in] pg Input reciprocal.
+ * @param[in] pg Input predicate.
* @param[in] val Input vector value in radians, F32 format.
*
* @return The calculated sine.
@@ -141,7 +141,7 @@
/** Calculate sine.
*
- * @param[in] pg Input reciprocal.
+ * @param[in] pg Input predicate.
* @param[in] val Input vector value in radians, F16 format.
*
* @return The calculated sine.
@@ -152,7 +152,7 @@
*
* pow(x,n) = e^(n*log(x))
*
- * @param[in] pg Input reciprocal.
+ * @param[in] pg Input predicate.
* @param[in] a Input vector value in F32 format.
* @param[in] b Powers to raise the input to.
*
@@ -164,7 +164,7 @@
*
* pow(x,n) = e^(n*log(x))
*
- * @param[in] pg Input reciprocal.
+ * @param[in] pg Input predicate.
* @param[in] a Input vector value in F16 format.
* @param[in] b Powers to raise the input to.
*
diff --git a/src/core/NEON/SVEMath.inl b/src/core/NEON/SVEMath.inl
index 86592f6..fbf90f9 100644
--- a/src/core/NEON/SVEMath.inl
+++ b/src/core/NEON/SVEMath.inl
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2020 Arm Limited.
+ * Copyright (c) 2020-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
diff --git a/src/core/NEON/kernels/NEArithmeticAdditionKernel.cpp b/src/core/NEON/kernels/NEArithmeticAdditionKernel.cpp
index aa7af54..f706ee5 100644
--- a/src/core/NEON/kernels/NEArithmeticAdditionKernel.cpp
+++ b/src/core/NEON/kernels/NEArithmeticAdditionKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2016-2020 Arm Limited.
+ * Copyright (c) 2016-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -28,7 +28,11 @@
#include "arm_compute/core/ITensor.h"
#include "arm_compute/core/Validate.h"
#include "src/core/CPP/Validate.h"
+#include "src/core/NEON/kernels/arithmetic_addition/impl/NEON/list.h"
+#include "src/core/NEON/kernels/arithmetic_addition/impl/SVE/list.h"
#include "src/core/NEON/wrapper/wrapper.h"
+#include "src/core/common/Registrars.h"
+#include "src/core/common/StdTypes.h"
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
@@ -39,788 +43,156 @@
{
namespace
{
-template <typename T>
-void add_same(const ITensor *in1, const ITensor *in2, ITensor *out, const ConvertPolicy policy, const Window &window)
+struct ArithmeticAdditionSelectorData
{
- /** NEON vector tag type. */
- using ExactTagType = typename wrapper::traits::neon_bitvector_tag_t<T, wrapper::traits::BitWidth::W128>;
+ DataType dt1;
+ DataType dt2;
+ DataType dt3;
+};
- // 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());
+using ArithmeticAdditionSelectorPtr = std::add_pointer<bool(const ArithmeticAdditionSelectorData &data)>::type;
- // 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();
-
- 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);
- const auto res = (policy == ConvertPolicy::SATURATE) ? wrapper::vqadd(broadcast_value_vec, non_broadcast_v) : wrapper::vadd(broadcast_value_vec, non_broadcast_v);
- 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);
- *(output_ptr + x) = (policy == ConvertPolicy::SATURATE) ? wrapper::add_sat(broadcast_value, non_broadcast_v) : broadcast_value + non_broadcast_v;
- }
- },
- 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 = (policy == ConvertPolicy::SATURATE) ? wrapper::vqadd(val1, val2) : wrapper::vadd(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) = (policy == ConvertPolicy::SATURATE) ? wrapper::add_sat(val1, val2) : val1 + val2;
- }
- },
- input1, input2, output);
- }
-}
-
-void add_QASYMM8_QASYMM8_QASYMM8(const ITensor *in1, const ITensor *in2, ITensor *out, ConvertPolicy policy, const Window &window)
+struct ArithmeticAdditionKernel
{
- ARM_COMPUTE_UNUSED(policy);
+ const char *name;
+ const ArithmeticAdditionSelectorPtr is_selected;
+ NEArithmeticAdditionKernel::ArithmeticAdditionKernelPtr ukernel;
+};
- // 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 uint8_t *>(non_broadcast_input.ptr());
- const auto output_ptr = reinterpret_cast<uint8_t *>(output.ptr());
-
- const uint8_t broadcast_value = *reinterpret_cast<const uint8_t *>(broadcast_input.ptr());
- const uint8x16_t broadcast_value_vec = vdupq_n_u8(broadcast_value);
-
- const float32x4x4_t bf =
- {
- {
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_low_u8(broadcast_value_vec))))), voffset2)), vscale2),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_low_u8(broadcast_value_vec))))), voffset2)), vscale2),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_high_u8(broadcast_value_vec))))), voffset2)), vscale2),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_high_u8(broadcast_value_vec))))), voffset2)), vscale2),
- }
- };
- const float bfs = static_cast<int32_t>(broadcast_value - broadcast_qinfo.offset) * broadcast_qinfo.scale;
-
- // Compute S elements per iteration
- int x = window_start_x;
- for(; x <= (window_end_x - window_step_x); x += window_step_x)
- {
- const uint8x16_t a = vld1q_u8(non_broadcast_input_ptr + x);
- const float32x4x4_t af =
- {
- {
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_low_u8(a))))), voffset1)), vscale1),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_low_u8(a))))), voffset1)), vscale1),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_high_u8(a))))), voffset1)), vscale1),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_high_u8(a))))), voffset1)), vscale1),
- }
- };
-
- const int32x4x4_t rf =
- {
- {
-#ifdef __aarch64__
- vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[0], bf.val[0]), invvscaleo)),
- vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[1], bf.val[1]), invvscaleo)),
- vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[2], bf.val[2]), invvscaleo)),
- vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[3], bf.val[3]), invvscaleo)),
-#else //__aarch64__
- vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[0], bf.val[0]), invvscaleo)),
- vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[1], bf.val[1]), invvscaleo)),
- vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[2], bf.val[2]), invvscaleo)),
- vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[3], bf.val[3]), invvscaleo)),
-#endif //__aarch64__
- }
- };
-
- const uint8x8_t pa = vqmovun_s16(vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1])));
- const uint8x8_t pb = vqmovun_s16(vcombine_s16(vqmovn_s32(rf.val[2]), vqmovn_s32(rf.val[3])));
- vst1q_u8(output_ptr + x, vcombine_u8(pa, pb));
- }
-
- // Compute left-over elements
- for(; x < window_end_x; ++x)
- {
- const float afs = static_cast<int32_t>(*(non_broadcast_input_ptr + x) - non_broadcast_qinfo.offset) * non_broadcast_qinfo.scale;
- *(output_ptr + x) = quantize_qasymm8((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);
-
- 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);
-
- 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 uint8x16_t a = vld1q_u8(input1_ptr + x);
- const uint8x16_t b = vld1q_u8(input2_ptr + x);
-
- const float32x4x4_t af =
- {
- {
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_low_u8(a))))), voffset1)), vscale1),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_low_u8(a))))), voffset1)), vscale1),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_high_u8(a))))), voffset1)), vscale1),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_high_u8(a))))), voffset1)), vscale1),
- }
- };
-
- const float32x4x4_t bf =
- {
- {
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_low_u8(b))))), voffset2)), vscale2),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_low_u8(b))))), voffset2)), vscale2),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_high_u8(b))))), voffset2)), vscale2),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_high_u8(b))))), voffset2)), vscale2),
- }
- };
-
- const int32x4x4_t rf =
- {
- {
-#ifdef __aarch64__
- vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[0], bf.val[0]), invvscaleo)),
- vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[1], bf.val[1]), invvscaleo)),
- vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[2], bf.val[2]), invvscaleo)),
- vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[3], bf.val[3]), invvscaleo)),
-#else //__aarch64__
- vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[0], bf.val[0]), invvscaleo)),
- vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[1], bf.val[1]), invvscaleo)),
- vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[2], bf.val[2]), invvscaleo)),
- vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[3], bf.val[3]), invvscaleo)),
-#endif //__aarch64__
- }
- };
-
- const uint8x8_t pa = vqmovun_s16(vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1])));
- const uint8x8_t pb = vqmovun_s16(vcombine_s16(vqmovn_s32(rf.val[2]), vqmovn_s32(rf.val[3])));
- vst1q_u8(output_ptr + x, vcombine_u8(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), out->info()->quantization_info());
- }
- },
- input1, input2, output);
- }
-}
-
-void add_QASYMM8_SIGNED_QASYMM8_SIGNED_QASYMM8_SIGNED(const ITensor *in1, const ITensor *in2, ITensor *out, ConvertPolicy policy, const Window &window)
+static const ArithmeticAdditionKernel available_kernels[] =
{
- ARM_COMPUTE_UNUSED(policy);
-
- // 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)
+#if defined(__ARM_FEATURE_SVE)
{
- 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 int8_t *>(non_broadcast_input.ptr());
- const auto output_ptr = reinterpret_cast<int8_t *>(output.ptr());
-
- const int8_t broadcast_value = *reinterpret_cast<const int8_t *>(broadcast_input.ptr());
- const int8x16_t broadcast_value_vec = vdupq_n_s8(broadcast_value);
-
- const float32x4x4_t bf =
- {
- {
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_low_s8(broadcast_value_vec)))), voffset2)), vscale2),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_low_s8(broadcast_value_vec)))), voffset2)), vscale2),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_high_s8(broadcast_value_vec)))), voffset2)), vscale2),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_high_s8(broadcast_value_vec)))), voffset2)), vscale2),
- }
- };
- const float bfs = static_cast<int32_t>(broadcast_value - broadcast_qinfo.offset) * broadcast_qinfo.scale;
-
- // Compute S elements per iteration
- int x = window_start_x;
- for(; x <= (window_end_x - window_step_x); x += window_step_x)
- {
- const int8x16_t a = vld1q_s8(non_broadcast_input_ptr + x);
- const float32x4x4_t af =
- {
- {
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_low_s8(a)))), voffset1)), vscale1),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_low_s8(a)))), voffset1)), vscale1),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_high_s8(a)))), voffset1)), vscale1),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_high_s8(a)))), voffset1)), vscale1),
- }
- };
-
- const int32x4x4_t rf =
- {
- {
-#ifdef __aarch64__
- vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[0], bf.val[0]), invvscaleo)),
- vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[1], bf.val[1]), invvscaleo)),
- vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[2], bf.val[2]), invvscaleo)),
- vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[3], bf.val[3]), invvscaleo)),
-#else //__aarch64__
- vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[0], bf.val[0]), invvscaleo)),
- vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[1], bf.val[1]), invvscaleo)),
- vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[2], bf.val[2]), invvscaleo)),
- vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[3], bf.val[3]), invvscaleo)),
-#endif //__aarch64__
- }
- };
-
- const int8x8_t pa = vqmovn_s16(vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1])));
- const int8x8_t pb = vqmovn_s16(vcombine_s16(vqmovn_s32(rf.val[2]), vqmovn_s32(rf.val[3])));
- vst1q_s8(output_ptr + x, vcombine_s8(pa, pb));
- }
-
- // Compute left-over elements
- for(; x < window_end_x; ++x)
- {
- const float afs = static_cast<int32_t>(*(non_broadcast_input_ptr + x) - non_broadcast_qinfo.offset) * non_broadcast_qinfo.scale;
- *(output_ptr + x) = quantize_qasymm8_signed((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);
-
- 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);
- 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 int8x16_t a = vld1q_s8(input1_ptr + x);
- const int8x16_t b = vld1q_s8(input2_ptr + x);
-
- const float32x4x4_t af =
- {
- {
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_low_s8(a)))), voffset1)), vscale1),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_low_s8(a)))), voffset1)), vscale1),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_high_s8(a)))), voffset1)), vscale1),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_high_s8(a)))), voffset1)), vscale1),
- }
- };
-
- const float32x4x4_t bf =
- {
- {
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_low_s8(b)))), voffset2)), vscale2),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_low_s8(b)))), voffset2)), vscale2),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_high_s8(b)))), voffset2)), vscale2),
- vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_high_s8(b)))), voffset2)), vscale2),
- }
- };
-
- const int32x4x4_t rf =
- {
- {
-#ifdef __aarch64__
- vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[0], bf.val[0]), invvscaleo)),
- vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[1], bf.val[1]), invvscaleo)),
- vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[2], bf.val[2]), invvscaleo)),
- vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[3], bf.val[3]), invvscaleo)),
-#else //__aarch64__
- vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[0], bf.val[0]), invvscaleo)),
- vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[1], bf.val[1]), invvscaleo)),
- vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[2], bf.val[2]), invvscaleo)),
- vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af.val[3], bf.val[3]), invvscaleo)),
-#endif //__aarch64__
- }
- };
-
- const int8x8_t pa = vqmovn_s16(vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1])));
- const int8x8_t pb = vqmovn_s16(vcombine_s16(vqmovn_s32(rf.val[2]), vqmovn_s32(rf.val[3])));
- vst1q_s8(output_ptr + x, vcombine_s8(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), out->info()->quantization_info());
- }
- },
- input1, input2, output);
- }
-}
-
-void add_QSYMM16_QSYMM16_QSYMM16(const ITensor *in1, const ITensor *in2, ITensor *out, ConvertPolicy policy, const Window &window)
-{
- ARM_COMPUTE_UNUSED(policy);
-
- // 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(vaddq_f32(af.val[0], bf.val[0]), invvscaleo)),
- vcvtnq_s32_f32(vmulq_f32(vaddq_f32(af.val[1], bf.val[1]), invvscaleo)),
-#else //__aarch64__
- vcvtq_s32_f32(vmulq_f32(vaddq_f32(af.val[0], bf.val[0]), invvscaleo)),
- vcvtq_s32_f32(vmulq_f32(vaddq_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((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(vaddq_f32(af.val[0], bf.val[0]), invvscaleo)),
- vcvtnq_s32_f32(vmulq_f32(vaddq_f32(af.val[1], bf.val[1]), invvscaleo)),
-#else //__aarch64__
- vcvtq_s32_f32(vmulq_f32(vaddq_f32(af.val[0], bf.val[0]), invvscaleo)),
- vcvtq_s32_f32(vmulq_f32(vaddq_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 add_S16_U8_S16(const ITensor *in1, const ITensor *in2, ITensor *out, ConvertPolicy policy, const Window &window)
-{
- // 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(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)));
- wrapper::vstore(output_ptr + x, wrapper::vadd(vin1, vin2));
- }
-
- // Compute left-over elements
- for(; x < window_end_x; ++x)
- {
- *(output_ptr + x) = *(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 = wrapper::vloadq(input1_ptr + x);
- const auto vin2 = vreinterpretq_s16_u16(wrapper::vmovl(wrapper::vload(input2_ptr + x)));
- wrapper::vstore(output_ptr + x, wrapper::vqadd(vin1, vin2));
- }
-
- // Compute left-over elements
- for(; x < window_end_x; ++x)
- {
- *(output_ptr + x) = wrapper::add_sat(*(input1_ptr + x), static_cast<int16_t>(*(input2_ptr + x)));
- }
- }
+ "arithmetic_addition_same_sve",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == DataType::F32)); },
+ REGISTER_FP32_SVE(arm_compute::cpu::arithmetic_addition_same_sve<float>)
},
- input1, input2, output);
-}
-
-inline void add_U8_S16_S16(const ITensor *input1, const ITensor *input2, ITensor *output, ConvertPolicy policy, const Window &window)
-{
- // Simply swap the two input buffers:
- add_S16_U8_S16(input2, input1, output, policy, window);
-}
-
-void add_U8_U8_S16(const ITensor *in1, const ITensor *in2, ITensor *out, ConvertPolicy policy, const Window &window)
-{
- // 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(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::vadd(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::vqadd(vin1, vin2));
- }
-
- // Compute left-over elements
- for(; x < window_end_x; ++x)
- {
- *(output_ptr + x) = wrapper::add_sat(static_cast<int16_t>(*(input1_ptr + x)),
- static_cast<int16_t>(*(input2_ptr + x)));
- }
- }
+ "arithmetic_addition_same_sve",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == DataType::F16)); },
+ REGISTER_FP16_SVE(arm_compute::cpu::arithmetic_addition_same_sve<float16_t>)
},
- input1, input2, output);
+ {
+ "arithmetic_addition_same_sve",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == data.dt3) && (data.dt1 == DataType::U8)); },
+ REGISTER_INTEGER_SVE(arm_compute::cpu::arithmetic_addition_same_sve<uint8_t>)
+ },
+ {
+ "arithmetic_addition_same_sve",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == data.dt3) && (data.dt1 == DataType::S16)); },
+ REGISTER_INTEGER_SVE(arm_compute::cpu::arithmetic_addition_same_sve<int16_t>)
+ },
+ {
+ "arithmetic_addition_same_sve",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == data.dt3) && (data.dt1 == DataType::S32)); },
+ REGISTER_INTEGER_SVE(arm_compute::cpu::arithmetic_addition_same_sve<int32_t>)
+ },
+ {
+ "arithmetic_addition_U8_S16_S16_sve",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == DataType::U8) && (data.dt2 == DataType::S16)); },
+ REGISTER_INTEGER_SVE(arm_compute::cpu::arithmetic_addition_U8_S16_S16_sve)
+ },
+ {
+ "arithmetic_addition_S16_U8_S16_sve",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == DataType::S16) && (data.dt2 == DataType::U8)); },
+ REGISTER_INTEGER_SVE(arm_compute::cpu::arithmetic_addition_S16_U8_S16_sve)
+ },
+ {
+ "arithmetic_addition_U8_U8_S16_sve",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt3 == DataType::S16)); },
+ REGISTER_INTEGER_SVE(arm_compute::cpu::arithmetic_addition_U8_U8_S16_sve)
+ },
+#else /* !defined(__ARM_FEATURE_SVE) */
+ {
+ "arithmetic_addition_same_neon",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == DataType::F32)); },
+ REGISTER_FP32_NEON(arm_compute::cpu::arithmetic_addition_same_neon<float>)
+ },
+#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC)
+ {
+ "arithmetic_addition_same_neon",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == DataType::F16)); },
+ REGISTER_FP16_NEON(arm_compute::cpu::arithmetic_addition_same_neon<float16_t>)
+ },
+#endif /* defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) */
+ {
+ "arithmetic_addition_same_neon",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == data.dt3) && (data.dt1 == DataType::U8)); },
+ REGISTER_INTEGER_NEON(arm_compute::cpu::arithmetic_addition_same_neon<uint8_t>)
+ },
+ {
+ "arithmetic_addition_same_neon",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == data.dt3) && (data.dt1 == DataType::S16)); },
+ REGISTER_INTEGER_NEON(arm_compute::cpu::arithmetic_addition_same_neon<int16_t>)
+ },
+ {
+ "arithmetic_addition_same_neon",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == data.dt3) && (data.dt1 == DataType::S32)); },
+ REGISTER_INTEGER_NEON(arm_compute::cpu::arithmetic_addition_same_neon<int32_t>)
+ },
+ {
+ "arithmetic_addition_U8_S16_S16_neon",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == DataType::U8) && (data.dt2 == DataType::S16)); },
+ REGISTER_INTEGER_NEON(arm_compute::cpu::arithmetic_addition_U8_S16_S16_neon)
+ },
+ {
+ "arithmetic_addition_S16_U8_S16_neon",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == DataType::S16) && (data.dt2 == DataType::U8)); },
+ REGISTER_INTEGER_NEON(arm_compute::cpu::arithmetic_addition_S16_U8_S16_neon)
+ },
+ {
+ "arithmetic_addition_U8_U8_S16_neon",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt3 == DataType::S16)); },
+ REGISTER_INTEGER_NEON(arm_compute::cpu::arithmetic_addition_U8_U8_S16_neon)
+ },
+#endif /* defined(__ARM_FEATURE_SVE) */
+
+#if defined(__ARM_FEATURE_SVE2)
+ {
+ "arithmetic_addition_qasymm8_sve",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == DataType::QASYMM8)); },
+ REGISTER_QASYMM8_SVE(arm_compute::cpu::arithmetic_addition_qasymm8_sve)
+ },
+ {
+ "arithmetic_addition_qasymm8_signed_sve",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == DataType::QASYMM8_SIGNED)); },
+ REGISTER_QASYMM8_SIGNED_SVE(arm_compute::cpu::arithmetic_addition_qasymm8_signed_sve)
+ },
+ {
+ "arithmetic_addition_qsymm16_sve",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == DataType::QSYMM16)); },
+ REGISTER_QSYMM16_SVE(arm_compute::cpu::arithmetic_addition_qsymm16_sve)
+ },
+#else /* !defined(__ARM_FEATURE_SVE2) */
+ {
+ "arithmetic_addition_qasymm8_neon",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == DataType::QASYMM8)); },
+ REGISTER_QASYMM8_NEON(arm_compute::cpu::arithmetic_addition_qasymm8_neon)
+ },
+ {
+ "arithmetic_addition_qasymm8_signed_neon",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == DataType::QASYMM8_SIGNED)); },
+ REGISTER_QASYMM8_SIGNED_NEON(arm_compute::cpu::arithmetic_addition_qasymm8_signed_neon)
+ },
+ {
+ "arithmetic_addition_qsymm16_neon",
+ [](const ArithmeticAdditionSelectorData & data) { return ((data.dt1 == data.dt2) && (data.dt1 == DataType::QSYMM16)); },
+ REGISTER_QSYMM16_NEON(arm_compute::cpu::arithmetic_addition_qsymm16_neon)
+ },
+#endif /* defined(__ARM_FEATURE_SVE2) */
+
+};
+
+const ArithmeticAdditionKernel *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;
}
Status validate_arguments(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output, ConvertPolicy policy)
@@ -926,53 +298,12 @@
ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(*input1, *input2, *output, policy));
+ _policy = policy;
+ _func = get_implementation(input1->data_type(), input2->data_type(), output->data_type())->ukernel;
+
// Configure kernel window
auto win_config = validate_and_configure_window(*input1, *input2, *output);
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
-
- static std::map<std::string, AddFunction *> map_function =
- {
- { "add_wrap_QASYMM8_QASYMM8_QASYMM8", &add_QASYMM8_QASYMM8_QASYMM8 },
- { "add_saturate_QASYMM8_QASYMM8_QASYMM8", &add_QASYMM8_QASYMM8_QASYMM8 },
- { "add_wrap_QASYMM8_SIGNED_QASYMM8_SIGNED_QASYMM8_SIGNED", &add_QASYMM8_SIGNED_QASYMM8_SIGNED_QASYMM8_SIGNED },
- { "add_saturate_QASYMM8_SIGNED_QASYMM8_SIGNED_QASYMM8_SIGNED", &add_QASYMM8_SIGNED_QASYMM8_SIGNED_QASYMM8_SIGNED },
- { "add_wrap_QSYMM16_QSYMM16_QSYMM16", &add_QSYMM16_QSYMM16_QSYMM16 },
- { "add_saturate_QSYMM16_QSYMM16_QSYMM16", &add_QSYMM16_QSYMM16_QSYMM16 },
- { "add_wrap_U8_U8_U8", &add_same<uint8_t> },
- { "add_saturate_U8_U8_U8", &add_same<uint8_t> },
- { "add_wrap_S16_U8_S16", &add_S16_U8_S16 },
- { "add_saturate_S16_U8_S16", &add_S16_U8_S16 },
- { "add_wrap_U8_S16_S16", &add_U8_S16_S16 },
- { "add_saturate_U8_S16_S16", &add_U8_S16_S16 },
- { "add_wrap_U8_U8_S16", &add_U8_U8_S16 },
- { "add_saturate_U8_U8_S16", &add_U8_U8_S16 },
- { "add_wrap_S16_S16_S16", &add_same<int16_t> },
- { "add_saturate_S16_S16_S16", &add_same<int16_t> },
- { "add_wrap_S32_S32_S32", &add_same<int32_t> },
- { "add_saturate_S32_S32_S32", &add_same<int32_t> },
- { "add_wrap_F32_F32_F32", &add_same<float> },
- { "add_saturate_F32_F32_F32", &add_same<float> },
-#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
- { "add_wrap_F16_F16_F16", &add_same<float16_t> },
- { "add_saturate_F16_F16_F16", &add_same<float16_t> },
-#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
- };
-
- _policy = policy;
-
- std::string function_to_call("add_");
- function_to_call += policy == ConvertPolicy::WRAP ? "wrap_" : "saturate_";
- function_to_call += string_from_data_type(input1->data_type()) + "_";
- function_to_call += string_from_data_type(input2->data_type()) + "_";
- function_to_call += string_from_data_type(output->data_type());
-
- auto it = map_function.find(function_to_call);
-
- if(it != map_function.end())
- {
- _func = it->second;
- }
-
INEKernel::configure(win_config.second);
}
diff --git a/src/core/NEON/kernels/NEArithmeticAdditionKernel.h b/src/core/NEON/kernels/NEArithmeticAdditionKernel.h
index 2072ad9..b88fc8a 100644
--- a/src/core/NEON/kernels/NEArithmeticAdditionKernel.h
+++ b/src/core/NEON/kernels/NEArithmeticAdditionKernel.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2016-2020 Arm Limited.
+ * Copyright (c) 2016-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -88,7 +88,6 @@
// Inherited methods overridden:
void run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) override;
-private:
/** Common signature for all the specialised add functions
*
* @param[in] input1 First input tensor. Data types supported: U8/QASYMM8/S16/QSYMM16/F16/S32/F32
@@ -97,10 +96,12 @@
* @param[in] policy Overflow policy.
* @param[in] window Region on which to execute the kernel.
*/
- using AddFunction = void(const ITensor *input1, const ITensor *input2, ITensor *output, ConvertPolicy policy, const Window &window);
+ using ArithmeticAdditionKernelPtr = std::add_pointer<void(const ITensor *, const ITensor *, ITensor *, const ConvertPolicy &, const Window &)>::type;
+
+private:
/** Add function to use for the particular tensor types passed to configure() */
- AddFunction *_func;
- ConvertPolicy _policy;
+ ArithmeticAdditionKernelPtr _func;
+ ConvertPolicy _policy;
};
} // namespace arm_compute
#endif /*ARM_COMPUTE_NEARITHMETICADDITIONKERNEL_H */
diff --git a/src/core/NEON/kernels/arithmetic_addition/impl/NEON/integer.cpp b/src/core/NEON/kernels/arithmetic_addition/impl/NEON/integer.cpp
new file mode 100644
index 0000000..8dd58ce
--- /dev/null
+++ b/src/core/NEON/kernels/arithmetic_addition/impl/NEON/integer.cpp
@@ -0,0 +1,171 @@
+/*
+ * Copyright (c) 2020-2021 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/common/StdTypes.h"
+#include "src/core/helpers/WindowHelpers.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+void arithmetic_addition_U8_U8_S16_neon(const ITensor *in1, const ITensor *in2, ITensor *out, const ConvertPolicy &policy, const Window &window)
+{
+ // 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(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::vadd(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::vqadd(vin1, vin2));
+ }
+
+ // Compute left-over elements
+ for(; x < window_end_x; ++x)
+ {
+ *(output_ptr + x) = wrapper::add_sat(static_cast<int16_t>(*(input1_ptr + x)),
+ static_cast<int16_t>(*(input2_ptr + x)));
+ }
+ }
+ },
+ input1, input2, output);
+}
+
+void arithmetic_addition_S16_U8_S16_neon(const ITensor *in1, const ITensor *in2, ITensor *out, const ConvertPolicy &policy, const Window &window)
+{
+ // 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(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)));
+ wrapper::vstore(output_ptr + x, wrapper::vadd(vin1, vin2));
+ }
+
+ // Compute left-over elements
+ for(; x < window_end_x; ++x)
+ {
+ *(output_ptr + x) = *(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 = wrapper::vloadq(input1_ptr + x);
+ const auto vin2 = vreinterpretq_s16_u16(wrapper::vmovl(wrapper::vload(input2_ptr + x)));
+ wrapper::vstore(output_ptr + x, wrapper::vqadd(vin1, vin2));
+ }
+
+ // Compute left-over elements
+ for(; x < window_end_x; ++x)
+ {
+ *(output_ptr + x) = wrapper::add_sat(*(input1_ptr + x), static_cast<int16_t>(*(input2_ptr + x)));
+ }
+ }
+ },
+ input1, input2, output);
+}
+
+void arithmetic_addition_U8_S16_S16_neon(const ITensor *input1, const ITensor *input2, ITensor *output, const ConvertPolicy &policy, const Window &window)
+{
+ // Simply swap the two input buffers:
+ arithmetic_addition_S16_U8_S16_neon(input2, input1, output, policy, window);
+}
+} // namespace cpu
+} // namespace arm_compute
\ No newline at end of file
diff --git a/src/core/NEON/kernels/arithmetic_addition/impl/NEON/list.h b/src/core/NEON/kernels/arithmetic_addition/impl/NEON/list.h
new file mode 100644
index 0000000..a8ab091
--- /dev/null
+++ b/src/core/NEON/kernels/arithmetic_addition/impl/NEON/list.h
@@ -0,0 +1,146 @@
+/*
+ * Copyright (c) 2020-2021 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_ARITHMETIC_ADDITION_LIST_H
+#define SRC_CORE_NEON_KERNELS_ARITHMETIC_ADDITION_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_ARITHMETIC_ADDITION_KERNEL(func_name) \
+ void func_name(const ITensor *in1, const ITensor *in2, ITensor *out, const ConvertPolicy &policy, const Window &window)
+
+DECLARE_ARITHMETIC_ADDITION_KERNEL(arithmetic_addition_qasymm8_neon);
+DECLARE_ARITHMETIC_ADDITION_KERNEL(arithmetic_addition_qasymm8_signed_neon);
+DECLARE_ARITHMETIC_ADDITION_KERNEL(arithmetic_addition_qsymm16_neon);
+DECLARE_ARITHMETIC_ADDITION_KERNEL(arithmetic_addition_S16_U8_S16_neon);
+DECLARE_ARITHMETIC_ADDITION_KERNEL(arithmetic_addition_U8_S16_S16_neon);
+DECLARE_ARITHMETIC_ADDITION_KERNEL(arithmetic_addition_U8_U8_S16_neon);
+
+#undef DECLARE_ARITHMETIC_ADDITION_KERNEL
+
+template <typename ScalarType>
+void arithmetic_addition_same_neon(const ITensor *in1, const ITensor *in2, ITensor *out, const ConvertPolicy &policy, const Window &window)
+{
+ /** NEON vector tag type. */
+ using ExactTagType = typename wrapper::traits::neon_bitvector_tag_t<ScalarType, 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(ScalarType);
+ 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();
+
+ 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 ScalarType *>(non_broadcast_input.ptr());
+ const auto output_ptr = reinterpret_cast<ScalarType *>(output.ptr());
+
+ const ScalarType broadcast_value = *reinterpret_cast<const ScalarType *>(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);
+ const auto res = (policy == ConvertPolicy::SATURATE) ? wrapper::vqadd(broadcast_value_vec, non_broadcast_v) : wrapper::vadd(broadcast_value_vec, non_broadcast_v);
+ 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);
+ *(output_ptr + x) = (policy == ConvertPolicy::SATURATE) ? wrapper::add_sat(broadcast_value, non_broadcast_v) : broadcast_value + non_broadcast_v;
+ }
+ },
+ 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 ScalarType *>(input1.ptr());
+ const auto input2_ptr = reinterpret_cast<const ScalarType *>(input2.ptr());
+ const auto output_ptr = reinterpret_cast<ScalarType *>(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 = (policy == ConvertPolicy::SATURATE) ? wrapper::vqadd(val1, val2) : wrapper::vadd(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) = (policy == ConvertPolicy::SATURATE) ? wrapper::add_sat(val1, val2) : val1 + val2;
+ }
+ },
+ input1, input2, output);
+ }
+}
+} // namespace cpu
+} // namespace arm_compute
+#endif // SRC_CORE_NEON_KERNELS_ARITHMETIC_ADDITION_LIST_H
\ No newline at end of file
diff --git a/src/core/NEON/kernels/arithmetic_addition/impl/NEON/qasymm8.cpp b/src/core/NEON/kernels/arithmetic_addition/impl/NEON/qasymm8.cpp
new file mode 100644
index 0000000..b93dad2
--- /dev/null
+++ b/src/core/NEON/kernels/arithmetic_addition/impl/NEON/qasymm8.cpp
@@ -0,0 +1,210 @@
+/*
+ * Copyright (c) 2020-2021 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/common/StdTypes.h"
+#include "src/core/helpers/WindowHelpers.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+void arithmetic_addition_qasymm8_neon(const ITensor *in1, const ITensor *in2, ITensor *out, const ConvertPolicy &policy, const Window &window)
+{
+ ARM_COMPUTE_UNUSED(policy);
+
+ // 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 uint8_t *>(non_broadcast_input.ptr());
+ const auto output_ptr = reinterpret_cast<uint8_t *>(output.ptr());
+
+ const uint8_t broadcast_value = *reinterpret_cast<const uint8_t *>(broadcast_input.ptr());
+ const uint8x16_t broadcast_value_vec = vdupq_n_u8(broadcast_value);
+
+ const auto bf_0 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_low_u8(broadcast_value_vec))))), voffset2)), vscale2);
+ const auto bf_1 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_low_u8(broadcast_value_vec))))), voffset2)), vscale2);
+ const auto bf_2 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_high_u8(broadcast_value_vec))))), voffset2)), vscale2);
+ const auto bf_3 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_high_u8(broadcast_value_vec))))), voffset2)), vscale2);
+
+ const float bfs = static_cast<int32_t>(broadcast_value - broadcast_qinfo.offset) * broadcast_qinfo.scale;
+
+ // Compute S elements per iteration
+ int x = window_start_x;
+ for(; x <= (window_end_x - window_step_x); x += window_step_x)
+ {
+ const uint8x16_t a = vld1q_u8(non_broadcast_input_ptr + x);
+ const auto af_0 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_low_u8(a))))), voffset1)), vscale1);
+ const auto af_1 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_low_u8(a))))), voffset1)), vscale1);
+ const auto af_2 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_high_u8(a))))), voffset1)), vscale1);
+ const auto af_3 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_high_u8(a))))), voffset1)), vscale1);
+
+ int32x4_t rf_0{};
+ int32x4_t rf_1{};
+ int32x4_t rf_2{};
+ int32x4_t rf_3{};
+
+#ifdef __aarch64__
+ rf_0 = vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_0, bf_0), invvscaleo));
+ rf_1 = vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_1, bf_1), invvscaleo));
+ rf_2 = vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_2, bf_2), invvscaleo));
+ rf_3 = vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_3, bf_3), invvscaleo));
+#else //__aarch64__
+ rf_0 = vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_0, bf_0), invvscaleo));
+ rf_1 = vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_1, bf_1), invvscaleo));
+ rf_2 = vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_2, bf_2), invvscaleo));
+ rf_3 = vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_3, bf_3), invvscaleo));
+#endif //__aarch64__
+
+ const uint8x8_t pa = vqmovun_s16(vcombine_s16(vqmovn_s32(rf_0), vqmovn_s32(rf_1)));
+ const uint8x8_t pb = vqmovun_s16(vcombine_s16(vqmovn_s32(rf_2), vqmovn_s32(rf_3)));
+ vst1q_u8(output_ptr + x, vcombine_u8(pa, pb));
+ }
+
+ // Compute left-over elements
+ for(; x < window_end_x; ++x)
+ {
+ const float afs = static_cast<int32_t>(*(non_broadcast_input_ptr + x) - non_broadcast_qinfo.offset) * non_broadcast_qinfo.scale;
+ *(output_ptr + x) = quantize_qasymm8((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);
+
+ 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);
+
+ 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 uint8x16_t a = vld1q_u8(input1_ptr + x);
+ const uint8x16_t b = vld1q_u8(input2_ptr + x);
+
+ const auto af_0 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_low_u8(a))))), voffset1)), vscale1);
+ const auto af_1 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_low_u8(a))))), voffset1)), vscale1);
+ const auto af_2 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_high_u8(a))))), voffset1)), vscale1);
+ const auto af_3 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_high_u8(a))))), voffset1)), vscale1);
+
+ const auto bf_0 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_low_u8(b))))), voffset2)), vscale2);
+ const auto bf_1 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_low_u8(b))))), voffset2)), vscale2);
+ const auto bf_2 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_high_u8(b))))), voffset2)), vscale2);
+ const auto bf_3 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_high_u8(b))))), voffset2)), vscale2);
+
+ int32x4_t rf_0{};
+ int32x4_t rf_1{};
+ int32x4_t rf_2{};
+ int32x4_t rf_3{};
+
+#ifdef __aarch64__
+ rf_0 = vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_0, bf_0), invvscaleo));
+ rf_1 = vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_1, bf_1), invvscaleo));
+ rf_2 = vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_2, bf_2), invvscaleo));
+ rf_3 = vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_3, bf_3), invvscaleo));
+#else //__aarch64__
+ rf_0 = vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_0, bf_0), invvscaleo));
+ rf_1 = vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_1, bf_1), invvscaleo));
+ rf_2 = vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_2, bf_2), invvscaleo));
+ rf_3 = vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_3, bf_3), invvscaleo));
+#endif //__aarch64__
+
+ const uint8x8_t pa = vqmovun_s16(vcombine_s16(vqmovn_s32(rf_0), vqmovn_s32(rf_1)));
+ const uint8x8_t pb = vqmovun_s16(vcombine_s16(vqmovn_s32(rf_2), vqmovn_s32(rf_3)));
+ vst1q_u8(output_ptr + x, vcombine_u8(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), out->info()->quantization_info());
+ }
+ },
+ input1, input2, output);
+ }
+}
+} // namespace cpu
+} // namespace arm_compute
\ No newline at end of file
diff --git a/src/core/NEON/kernels/arithmetic_addition/impl/NEON/qasymm8_signed.cpp b/src/core/NEON/kernels/arithmetic_addition/impl/NEON/qasymm8_signed.cpp
new file mode 100644
index 0000000..ba81cfc
--- /dev/null
+++ b/src/core/NEON/kernels/arithmetic_addition/impl/NEON/qasymm8_signed.cpp
@@ -0,0 +1,209 @@
+/*
+ * Copyright (c) 2020-2021 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/common/StdTypes.h"
+#include "src/core/helpers/WindowHelpers.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+void arithmetic_addition_qasymm8_signed_neon(const ITensor *in1, const ITensor *in2, ITensor *out, const ConvertPolicy &policy, const Window &window)
+{
+ ARM_COMPUTE_UNUSED(policy);
+
+ // 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 int8_t *>(non_broadcast_input.ptr());
+ const auto output_ptr = reinterpret_cast<int8_t *>(output.ptr());
+
+ const int8_t broadcast_value = *reinterpret_cast<const int8_t *>(broadcast_input.ptr());
+ const int8x16_t broadcast_value_vec = vdupq_n_s8(broadcast_value);
+
+ const auto bf_0 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_low_s8(broadcast_value_vec)))), voffset2)), vscale2);
+ const auto bf_1 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_low_s8(broadcast_value_vec)))), voffset2)), vscale2);
+ const auto bf_2 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_high_s8(broadcast_value_vec)))), voffset2)), vscale2);
+ const auto bf_3 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_high_s8(broadcast_value_vec)))), voffset2)), vscale2);
+ const float bfs = static_cast<int32_t>(broadcast_value - broadcast_qinfo.offset) * broadcast_qinfo.scale;
+
+ // Compute S elements per iteration
+ int x = window_start_x;
+ for(; x <= (window_end_x - window_step_x); x += window_step_x)
+ {
+ const int8x16_t a = vld1q_s8(non_broadcast_input_ptr + x);
+
+ const auto af_0 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_low_s8(a)))), voffset1)), vscale1);
+ const auto af_1 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_low_s8(a)))), voffset1)), vscale1);
+ const auto af_2 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_high_s8(a)))), voffset1)), vscale1);
+ const auto af_3 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_high_s8(a)))), voffset1)), vscale1);
+
+ int32x4_t rf_0{};
+ int32x4_t rf_1{};
+ int32x4_t rf_2{};
+ int32x4_t rf_3{};
+
+#ifdef __aarch64__
+ rf_0 = vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_0, bf_0), invvscaleo));
+ rf_1 = vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_1, bf_1), invvscaleo));
+ rf_2 = vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_2, bf_2), invvscaleo));
+ rf_3 = vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_3, bf_3), invvscaleo));
+#else //__aarch64__
+ rf_0 = vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_0, bf_0), invvscaleo));
+ rf_1 = vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_1, bf_1), invvscaleo));
+ rf_2 = vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_2, bf_2), invvscaleo));
+ rf_3 = vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_3, bf_3), invvscaleo));
+#endif //__aarch64__
+
+ const int8x8_t pa = vqmovn_s16(vcombine_s16(vqmovn_s32(rf_0), vqmovn_s32(rf_1)));
+ const int8x8_t pb = vqmovn_s16(vcombine_s16(vqmovn_s32(rf_2), vqmovn_s32(rf_3)));
+ vst1q_s8(output_ptr + x, vcombine_s8(pa, pb));
+ }
+
+ // Compute left-over elements
+ for(; x < window_end_x; ++x)
+ {
+ const float afs = static_cast<int32_t>(*(non_broadcast_input_ptr + x) - non_broadcast_qinfo.offset) * non_broadcast_qinfo.scale;
+ *(output_ptr + x) = quantize_qasymm8_signed((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);
+
+ 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);
+ 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 int8x16_t a = vld1q_s8(input1_ptr + x);
+ const int8x16_t b = vld1q_s8(input2_ptr + x);
+
+ const auto af_0 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_low_s8(a)))), voffset1)), vscale1);
+ const auto af_1 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_low_s8(a)))), voffset1)), vscale1);
+ const auto af_2 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_high_s8(a)))), voffset1)), vscale1);
+ const auto af_3 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_high_s8(a)))), voffset1)), vscale1);
+
+ const auto bf_0 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_low_s8(b)))), voffset2)), vscale2);
+ const auto bf_1 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_low_s8(b)))), voffset2)), vscale2);
+ const auto bf_2 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_high_s8(b)))), voffset2)), vscale2);
+ const auto bf_3 = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_high_s8(b)))), voffset2)), vscale2);
+
+ int32x4_t rf_0{};
+ int32x4_t rf_1{};
+ int32x4_t rf_2{};
+ int32x4_t rf_3{};
+
+#ifdef __aarch64__
+ rf_0 = vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_0, bf_0), invvscaleo));
+ rf_1 = vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_1, bf_1), invvscaleo));
+ rf_2 = vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_2, bf_2), invvscaleo));
+ rf_3 = vcvtnq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_3, bf_3), invvscaleo));
+#else //__aarch64__
+ rf_0 = vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_0, bf_0), invvscaleo));
+ rf_1 = vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_1, bf_1), invvscaleo));
+ rf_2 = vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_2, bf_2), invvscaleo));
+ rf_3 = vcvtq_s32_f32(vmlaq_f32(voffseto, vaddq_f32(af_3, bf_3), invvscaleo));
+#endif //__aarch64__
+
+ const int8x8_t pa = vqmovn_s16(vcombine_s16(vqmovn_s32(rf_0), vqmovn_s32(rf_1)));
+ const int8x8_t pb = vqmovn_s16(vcombine_s16(vqmovn_s32(rf_2), vqmovn_s32(rf_3)));
+ vst1q_s8(output_ptr + x, vcombine_s8(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), out->info()->quantization_info());
+ }
+ },
+ input1, input2, output);
+ }
+}
+} // namespace cpu
+} // namespace arm_compute
\ No newline at end of file
diff --git a/src/core/NEON/kernels/arithmetic_addition/impl/NEON/qsymm16.cpp b/src/core/NEON/kernels/arithmetic_addition/impl/NEON/qsymm16.cpp
new file mode 100644
index 0000000..538c600
--- /dev/null
+++ b/src/core/NEON/kernels/arithmetic_addition/impl/NEON/qsymm16.cpp
@@ -0,0 +1,175 @@
+/*
+ * Copyright (c) 2020-2021 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/common/StdTypes.h"
+#include "src/core/helpers/WindowHelpers.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+void arithmetic_addition_qsymm16_neon(const ITensor *in1, const ITensor *in2, ITensor *out, const ConvertPolicy &policy, const Window &window)
+{
+ ARM_COMPUTE_UNUSED(policy);
+
+ // 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 auto bf_0 = vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(broadcast_value_vec))), vscale2);
+ const auto bf_1 = 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 auto af_0 = vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(a))), vscale1);
+ const auto af_1 = vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(a))), vscale1);
+
+ int32x4_t rf_0{};
+ int32x4_t rf_1{};
+#ifdef __aarch64__
+ rf_0 = vcvtnq_s32_f32(vmulq_f32(vaddq_f32(af_0, bf_0), invvscaleo));
+ rf_1 = vcvtnq_s32_f32(vmulq_f32(vaddq_f32(af_1, bf_1), invvscaleo));
+#else //__aarch64__
+ rf_0 = vcvtq_s32_f32(vmulq_f32(vaddq_f32(af_0, bf_0), invvscaleo));
+ rf_1 = vcvtq_s32_f32(vmulq_f32(vaddq_f32(af_1, bf_1), invvscaleo));
+#endif //__aarch64__
+
+ const int16x8_t pa = vcombine_s16(vqmovn_s32(rf_0), vqmovn_s32(rf_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((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 auto af_0 = vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(a))), vscale1);
+ const auto af_1 = vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(a))), vscale1);
+ const auto bf_0 = vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(b))), vscale2);
+ const auto bf_1 = vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(b))), vscale2);
+
+ int32x4_t rf_0{};
+ int32x4_t rf_1{};
+#ifdef __aarch64__
+ rf_0 = vcvtnq_s32_f32(vmulq_f32(vaddq_f32(af_0, bf_0), invvscaleo));
+ rf_1 = vcvtnq_s32_f32(vmulq_f32(vaddq_f32(af_1, bf_1), invvscaleo));
+#else //__aarch64__
+ rf_0 = vcvtq_s32_f32(vmulq_f32(vaddq_f32(af_0, bf_0), invvscaleo));
+ rf_1 = vcvtq_s32_f32(vmulq_f32(vaddq_f32(af_1, bf_1), invvscaleo));
+#endif //__aarch64__
+
+ const int16x8_t pa = vcombine_s16(vqmovn_s32(rf_0), vqmovn_s32(rf_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);
+ }
+}
+} // namespace cpu
+} // namespace arm_compute
\ No newline at end of file
diff --git a/src/core/NEON/kernels/arithmetic_addition/impl/SVE/integer.cpp b/src/core/NEON/kernels/arithmetic_addition/impl/SVE/integer.cpp
new file mode 100644
index 0000000..c502a02
--- /dev/null
+++ b/src/core/NEON/kernels/arithmetic_addition/impl/SVE/integer.cpp
@@ -0,0 +1,201 @@
+/*
+ * Copyright (c) 2020-2021 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"
+#if defined(__ARM_FEATURE_SVE)
+#include "src/core/NEON/SVEMath.h"
+#include <arm_sve.h>
+
+namespace arm_compute
+{
+namespace cpu
+{
+void arithmetic_addition_U8_U8_S16_sve(const ITensor *in1, const ITensor *in2, ITensor *out, const ConvertPolicy &policy, const Window &window)
+{
+ // 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 auto window_start_x = static_cast<int>(window.x().start());
+ const auto window_end_x = static_cast<int>(window.x().end());
+ const auto all_true_pg = svptrue_b8();
+
+ 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)
+ {
+ int x = window_start_x;
+ svbool_t pg_u = svwhilelt_b8(x, window_end_x);
+ svbool_t pg_0 = svwhilelt_b16(x, window_end_x);
+ svbool_t pg_1 = svwhilelt_b16(x, static_cast<int>(window_end_x + svcnth()));
+ do
+ {
+ const auto vin1 = svld1(pg_u, input1_ptr + x);
+ const auto vin2 = svld1(pg_u, input2_ptr + x);
+
+ const auto vin1_lo = svreinterpret_s16_u16(svunpklo(vin1));
+ const auto vin1_hi = svreinterpret_s16_u16(svunpkhi(vin1));
+ const auto vin2_lo = svreinterpret_s16_u16(svunpklo(vin2));
+ const auto vin2_hi = svreinterpret_s16_u16(svunpkhi(vin2));
+ svst1(pg_0, output_ptr + x, svqadd(vin1_lo, vin2_lo));
+ svst1(pg_1, output_ptr + x + svcnth(), svqadd(vin1_hi, vin2_hi));
+
+ x += svcntb();
+ pg_u = svwhilelt_b8(x, window_end_x);
+ pg_0 = svwhilelt_b16(x, window_end_x);
+ pg_1 = svwhilelt_b16(x, static_cast<int>(window_end_x + svcnth()));
+ }
+ while(svptest_any(all_true_pg, pg_u));
+ }
+ else
+ {
+ int x = window_start_x;
+ svbool_t pg_u = svwhilelt_b8(x, window_end_x);
+ svbool_t pg_0 = svwhilelt_b16(x, window_end_x);
+ svbool_t pg_1 = svwhilelt_b16(x, static_cast<int>(window_end_x + svcnth()));
+ do
+ {
+ const auto vin1 = svld1(pg_u, input1_ptr + x);
+ const auto vin2 = svld1(pg_u, input2_ptr + x);
+
+ const auto vin1_lo = svreinterpret_s16_u16(svunpklo(vin1));
+ const auto vin1_hi = svreinterpret_s16_u16(svunpkhi(vin1));
+ const auto vin2_lo = svreinterpret_s16_u16(svunpklo(vin2));
+ const auto vin2_hi = svreinterpret_s16_u16(svunpkhi(vin2));
+ svst1(pg_0, output_ptr + x, svqadd(vin1_lo, vin2_lo));
+ svst1(pg_1, output_ptr + x + svcnth(), svqadd(vin1_hi, vin2_hi));
+
+ x += svcntb();
+ pg_u = svwhilelt_b8(x, window_end_x);
+ pg_0 = svwhilelt_b16(x, window_end_x);
+ pg_1 = svwhilelt_b16(x, static_cast<int>(window_end_x + svcnth()));
+ }
+ while(svptest_any(all_true_pg, pg_u));
+ }
+ },
+ input1, input2, output);
+}
+
+void arithmetic_addition_S16_U8_S16_sve(const ITensor *in1, const ITensor *in2, ITensor *out, const ConvertPolicy &policy, const Window &window)
+{
+ // 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 auto window_start_x = static_cast<int>(window.x().start());
+ const auto window_end_x = static_cast<int>(window.x().end());
+ const auto all_true_pg = svptrue_b8();
+
+ 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)
+ {
+ int x = window_start_x;
+ svbool_t pg_u = svwhilelt_b8(x, window_end_x);
+ svbool_t pg_0 = svwhilelt_b16(x, window_end_x);
+ svbool_t pg_1 = svwhilelt_b16(x + static_cast<int>(svcnth()), window_end_x);
+ do
+ {
+ const auto vin1_0 = svld1_s16(pg_0, input1_ptr + x);
+ const auto vin1_1 = svld1_s16(pg_1, input1_ptr + x + svcnth());
+ const auto vin2_u8 = svld1_u8(pg_u, input2_ptr + x);
+ const auto vin2_0 = svreinterpret_s16_u16(svunpklo(vin2_u8));
+ const auto vin2_1 = svreinterpret_s16_u16(svunpkhi(vin2_u8));
+ svst1_s16(pg_0, output_ptr + x, svadd_s16_z(pg_0, vin1_0, vin2_0));
+ svst1_s16(pg_1, output_ptr + x, svadd_s16_z(pg_1, vin1_1, vin2_1));
+
+ x += svcnth();
+ pg_u = svwhilelt_b8(x, window_end_x);
+ pg_0 = svwhilelt_b16(x, window_end_x);
+ pg_1 = svwhilelt_b16(x + static_cast<int>(svcnth()), window_end_x);
+ }
+ while(svptest_any(all_true_pg, pg_u));
+ }
+ else
+ {
+ int x = window_start_x;
+ svbool_t pg_u = svwhilelt_b8(x, window_end_x);
+ svbool_t pg_0 = svwhilelt_b16(x, window_end_x);
+ svbool_t pg_1 = svwhilelt_b16(x + static_cast<int>(svcnth()), window_end_x);
+ do
+ {
+ const auto vin1_0 = svld1_s16(pg_0, input1_ptr + x);
+ const auto vin1_1 = svld1_s16(pg_1, input1_ptr + x);
+ const auto vin2_u8 = svld1_u8(pg_u, input2_ptr + x);
+ const auto vin2_0 = svreinterpret_s16_u16(svunpklo(vin2_u8));
+ const auto vin2_1 = svreinterpret_s16_u16(svunpkhi(vin2_u8));
+
+ svst1_s16(pg_0, output_ptr + x, svqadd(vin1_0, vin2_0));
+ svst1_s16(pg_1, output_ptr + x, svqadd(vin1_1, vin2_1));
+
+ x += svcnth();
+ pg_u = svwhilelt_b8(x, window_end_x);
+ pg_0 = svwhilelt_b16(x, window_end_x);
+ pg_1 = svwhilelt_b16(x + static_cast<int>(svcnth()), window_end_x);
+ }
+ while(svptest_any(all_true_pg, pg_u));
+ }
+ },
+ input1, input2, output);
+}
+
+void arithmetic_addition_U8_S16_S16_sve(const ITensor *input1, const ITensor *input2, ITensor *output, const ConvertPolicy &policy, const Window &window)
+{
+ // Simply swap the two input buffers:
+ arithmetic_addition_S16_U8_S16_sve(input2, input1, output, policy, window);
+}
+} // namespace cpu
+} // namespace arm_compute
+#endif /* defined(__ARM_FEATURE_SVE) */
\ No newline at end of file
diff --git a/src/core/NEON/kernels/arithmetic_addition/impl/SVE/list.h b/src/core/NEON/kernels/arithmetic_addition/impl/SVE/list.h
new file mode 100644
index 0000000..3e238c4
--- /dev/null
+++ b/src/core/NEON/kernels/arithmetic_addition/impl/SVE/list.h
@@ -0,0 +1,145 @@
+/*
+ * Copyright (c) 2020-2021 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_SVE_KERNELS_ARITHMETIC_ADDITION_LIST_H
+#define SRC_CORE_SVE_KERNELS_ARITHMETIC_ADDITION_LIST_H
+
+#if defined(__ARM_FEATURE_SVE)
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/utils/misc/Traits.h"
+#include "src/core/NEON/SVEMath.h"
+#include "src/core/NEON/wrapper/intrinsics/intrinsics.h"
+#include <arm_sve.h>
+
+namespace arm_compute
+{
+namespace cpu
+{
+#define DECLARE_ARITHMETIC_ADDITION_KERNEL(func_name) \
+ void func_name(const ITensor *in1, const ITensor *in2, ITensor *out, const ConvertPolicy &policy, const Window &window)
+
+DECLARE_ARITHMETIC_ADDITION_KERNEL(arithmetic_addition_qasymm8_sve);
+DECLARE_ARITHMETIC_ADDITION_KERNEL(arithmetic_addition_qasymm8_signed_sve);
+DECLARE_ARITHMETIC_ADDITION_KERNEL(arithmetic_addition_qsymm16_sve);
+DECLARE_ARITHMETIC_ADDITION_KERNEL(arithmetic_addition_S16_U8_S16_sve);
+DECLARE_ARITHMETIC_ADDITION_KERNEL(arithmetic_addition_U8_S16_S16_sve);
+DECLARE_ARITHMETIC_ADDITION_KERNEL(arithmetic_addition_U8_U8_S16_sve);
+
+#undef DECLARE_ARITHMETIC_ADDITION_KERNEL
+
+template <typename ScalarType>
+void arithmetic_addition_same_sve(const ITensor *in1, const ITensor *in2, ITensor *out, const ConvertPolicy &policy, const Window &window)
+{
+ const auto all_true_pg = wrapper::svptrue<ScalarType>();
+ 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 bool is_sat = (policy == ConvertPolicy::SATURATE);
+
+ // Clear X Dimension on execution window as we handle manually
+ Window win = window;
+ win.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+ // 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());
+
+ 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 ScalarType *>(non_broadcast_input.ptr());
+ const auto output_ptr = reinterpret_cast<ScalarType *>(output.ptr());
+
+ const ScalarType broadcast_value = *reinterpret_cast<const ScalarType *>(broadcast_input.ptr());
+ const auto broadcast_value_vec = wrapper::svdup_n(broadcast_value);
+
+ int x = window_start_x;
+ svbool_t pg = wrapper::svwhilelt<ScalarType>(x, window_end_x);
+ do
+ {
+ const auto non_broadcast_v = svld1(pg, non_broadcast_input_ptr + x);
+ auto res = is_sat ? wrapper::svqadd(broadcast_value_vec, non_broadcast_v) : svadd_z(pg, broadcast_value_vec, non_broadcast_v);
+ svst1(pg, output_ptr + x, res);
+
+ x += wrapper::svcnt<ScalarType>();
+ pg = wrapper::svwhilelt<ScalarType>(x, window_end_x);
+ }
+ while(svptest_any(all_true_pg, pg));
+ },
+ 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 ScalarType *>(input1.ptr());
+ const auto input2_ptr = reinterpret_cast<const ScalarType *>(input2.ptr());
+ const auto output_ptr = reinterpret_cast<ScalarType *>(output.ptr());
+
+ int x = window_start_x;
+ svbool_t pg = wrapper::svwhilelt<ScalarType>(x, window_end_x);
+ do
+ {
+ const auto val1 = svld1(pg, input1_ptr + x);
+ const auto val2 = svld1(pg, input2_ptr + x);
+ const auto res = is_sat ? wrapper::svqadd(val1, val2) : svadd_z(pg, val1, val2);
+ svst1(pg, output_ptr + x, res);
+
+ x += wrapper::svcnt<ScalarType>();
+ pg = wrapper::svwhilelt<ScalarType>(x, window_end_x);
+ }
+ while(svptest_any(all_true_pg, pg));
+ },
+ input1, input2, output);
+ }
+}
+} // namespace cpu
+} // namespace arm_compute
+#endif // defined(__ARM_FEATURE_SVE)
+#endif // SRC_CORE_SVE_KERNELS_ARITHMETIC_ADDITION_LIST_H
\ No newline at end of file
diff --git a/src/core/NEON/kernels/arithmetic_addition/impl/SVE/qasymm8.cpp b/src/core/NEON/kernels/arithmetic_addition/impl/SVE/qasymm8.cpp
new file mode 100644
index 0000000..871ee23
--- /dev/null
+++ b/src/core/NEON/kernels/arithmetic_addition/impl/SVE/qasymm8.cpp
@@ -0,0 +1,182 @@
+/*
+ * Copyright (c) 2020-2021 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"
+#if defined(__ARM_FEATURE_SVE2)
+#include "src/core/NEON/SVEMath.h"
+#include <arm_sve.h>
+
+namespace arm_compute
+{
+namespace cpu
+{
+void arithmetic_addition_qasymm8_sve(const ITensor *in1, const ITensor *in2, ITensor *out, const ConvertPolicy &policy, const Window &window)
+{
+ ARM_COMPUTE_UNUSED(policy);
+
+ // 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 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 auto all_true_pg = svptrue_b8();
+
+ 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 auto invvscaleo = svdup_n_f32(1.f / oq_info.scale);
+ const auto voffseto = svdup_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 svfloat32_t vscale1 = is_broadcast_input_2 ? svdup_n_f32(iq1_info.scale) : svdup_n_f32(iq2_info.scale);
+ const svfloat32_t vscale2 = is_broadcast_input_2 ? svdup_n_f32(iq2_info.scale) : svdup_n_f32(iq1_info.scale);
+ const svint32_t voffset1 = is_broadcast_input_2 ? svdup_n_s32(iq1_info.offset) : svdup_n_s32(iq2_info.offset);
+ const svint32_t voffset2 = is_broadcast_input_2 ? svdup_n_s32(iq2_info.offset) : svdup_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 uint8_t *>(non_broadcast_input.ptr());
+ const auto output_ptr = reinterpret_cast<uint8_t *>(output.ptr());
+
+ const uint8_t broadcast_value = *reinterpret_cast<const uint8_t *>(broadcast_input.ptr());
+ const svuint8_t broadcast_value_vec = svdup_n_u8(broadcast_value);
+
+ int x = window_start_x;
+ svbool_t pg = svwhilelt_b8(x, window_end_x);
+
+ const auto bf_0 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svreinterpret_s32_u32(svmovlb_u32(svmovlb_u16(broadcast_value_vec))), voffset2)), vscale2);
+ const auto bf_1 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svreinterpret_s32_u32(svmovlt_u32(svmovlb_u16(broadcast_value_vec))), voffset2)), vscale2);
+ const auto bf_2 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svreinterpret_s32_u32(svmovlb_u32(svmovlt_u16(broadcast_value_vec))), voffset2)), vscale2);
+ const auto bf_3 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svreinterpret_s32_u32(svmovlt_u32(svmovlt_u16(broadcast_value_vec))), voffset2)), vscale2);
+
+ do
+ {
+ const svuint8_t a = svld1_u8(pg, non_broadcast_input_ptr + x);
+
+ const auto af_0 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svreinterpret_s32_u32(svmovlb_u32(svmovlb_u16(a))), voffset1)), vscale1);
+ const auto af_1 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svreinterpret_s32_u32(svmovlt_u32(svmovlb_u16(a))), voffset1)), vscale1);
+ const auto af_2 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svreinterpret_s32_u32(svmovlb_u32(svmovlt_u16(a))), voffset1)), vscale1);
+ const auto af_3 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svreinterpret_s32_u32(svmovlt_u32(svmovlt_u16(a))), voffset1)), vscale1);
+
+ const auto rf_0 = svcvt_u32_f32_z(pg, svmla_f32_z(pg, voffseto, svadd_f32_z(pg, af_0, bf_0), invvscaleo));
+ const auto rf_1 = svcvt_u32_f32_z(pg, svmla_f32_z(pg, voffseto, svadd_f32_z(pg, af_1, bf_1), invvscaleo));
+ const auto rf_2 = svcvt_u32_f32_z(pg, svmla_f32_z(pg, voffseto, svadd_f32_z(pg, af_2, bf_2), invvscaleo));
+ const auto rf_3 = svcvt_u32_f32_z(pg, svmla_f32_z(pg, voffseto, svadd_f32_z(pg, af_3, bf_3), invvscaleo));
+
+ const auto pa = svqxtnt_u32(svqxtnb_u32(rf_0), rf_1);
+ const auto pb = svqxtnt_u32(svqxtnb_u32(rf_2), rf_3);
+
+ const auto res = svqxtnt_u16(svqxtnb_u16(pa), pb);
+ svst1_u8(pg, output_ptr + x, res);
+
+ x += svcntb();
+ pg = svwhilelt_b8(x, window_end_x);
+ }
+ while(svptest_any(all_true_pg, pg));
+ },
+ 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);
+
+ const auto vscale1 = svdup_n_f32(iq1_info.scale);
+ const auto vscale2 = svdup_n_f32(iq2_info.scale);
+ const auto voffset1 = svdup_n_s32(iq1_info.offset);
+ const auto voffset2 = svdup_n_s32(iq2_info.offset);
+
+ 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());
+
+ int x = window_start_x;
+ svbool_t pg = svwhilelt_b8(x, window_end_x);
+ do
+ {
+ const auto a = svld1_u8(pg, input1_ptr + x);
+ const auto b = svld1_u8(pg, input2_ptr + x);
+ const auto af_0 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svreinterpret_s32_u32(svmovlb_u32(svmovlb_u16(a))), voffset1)), vscale1);
+ const auto af_1 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svreinterpret_s32_u32(svmovlt_u32(svmovlb_u16(a))), voffset1)), vscale1);
+ const auto af_2 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svreinterpret_s32_u32(svmovlb_u32(svmovlt_u16(a))), voffset1)), vscale1);
+ const auto af_3 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svreinterpret_s32_u32(svmovlt_u32(svmovlt_u16(a))), voffset1)), vscale1);
+
+ const auto bf_0 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svreinterpret_s32_u32(svmovlb_u32(svmovlb_u16(b))), voffset2)), vscale2);
+ const auto bf_1 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svreinterpret_s32_u32(svmovlt_u32(svmovlb_u16(b))), voffset2)), vscale2);
+ const auto bf_2 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svreinterpret_s32_u32(svmovlb_u32(svmovlt_u16(b))), voffset2)), vscale2);
+ const auto bf_3 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svreinterpret_s32_u32(svmovlt_u32(svmovlt_u16(b))), voffset2)), vscale2);
+
+ const auto rf_0 = svcvt_u32_f32_z(pg, svmla_f32_z(pg, voffseto, svadd_f32_z(pg, af_0, bf_0), invvscaleo));
+ const auto rf_1 = svcvt_u32_f32_z(pg, svmla_f32_z(pg, voffseto, svadd_f32_z(pg, af_1, bf_1), invvscaleo));
+ const auto rf_2 = svcvt_u32_f32_z(pg, svmla_f32_z(pg, voffseto, svadd_f32_z(pg, af_2, bf_2), invvscaleo));
+ const auto rf_3 = svcvt_u32_f32_z(pg, svmla_f32_z(pg, voffseto, svadd_f32_z(pg, af_3, bf_3), invvscaleo));
+
+ const auto pa = svqxtnt_u32(svqxtnb_u32(rf_0), rf_1);
+ const auto pb = svqxtnt_u32(svqxtnb_u32(rf_2), rf_3);
+ const auto res = svqxtnt_u16(svqxtnb_u16(pa), pb);
+
+ svst1_u8(pg, output_ptr + x, res);
+
+ x += svcntb();
+ pg = svwhilelt_b8(x, window_end_x);
+ }
+ while(svptest_any(all_true_pg, pg));
+ },
+ input1, input2, output);
+ }
+}
+} // namespace cpu
+} // namespace arm_compute
+#endif /* defined(__ARM_FEATURE_SVE2) */
\ No newline at end of file
diff --git a/src/core/NEON/kernels/arithmetic_addition/impl/SVE/qasymm8_signed.cpp b/src/core/NEON/kernels/arithmetic_addition/impl/SVE/qasymm8_signed.cpp
new file mode 100644
index 0000000..2ba5d39
--- /dev/null
+++ b/src/core/NEON/kernels/arithmetic_addition/impl/SVE/qasymm8_signed.cpp
@@ -0,0 +1,181 @@
+/*
+ * Copyright (c) 2020-2021 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"
+#if defined(__ARM_FEATURE_SVE2)
+#include "src/core/NEON/SVEMath.h"
+#include <arm_sve.h>
+
+namespace arm_compute
+{
+namespace cpu
+{
+void arithmetic_addition_qasymm8_signed_sve(const ITensor *in1, const ITensor *in2, ITensor *out, const ConvertPolicy &policy, const Window &window)
+{
+ ARM_COMPUTE_UNUSED(policy);
+
+ // 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 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 auto invvscaleo = svdup_n_f32(1.f / oq_info.scale);
+ const auto voffseto = svdup_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 auto all_true_pg = svptrue_b8();
+
+ const auto vscale1 = is_broadcast_input_2 ? svdup_n_f32(iq1_info.scale) : svdup_n_f32(iq2_info.scale);
+ const auto vscale2 = is_broadcast_input_2 ? svdup_n_f32(iq2_info.scale) : svdup_n_f32(iq1_info.scale);
+ const auto voffset1 = is_broadcast_input_2 ? svdup_n_s32(iq1_info.offset) : svdup_n_s32(iq2_info.offset);
+ const auto voffset2 = is_broadcast_input_2 ? svdup_n_s32(iq2_info.offset) : svdup_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 int8_t *>(non_broadcast_input.ptr());
+ const auto output_ptr = reinterpret_cast<int8_t *>(output.ptr());
+
+ const int8_t broadcast_value = *reinterpret_cast<const int8_t *>(broadcast_input.ptr());
+ const auto broadcast_value_vec = svdup_n_s8(broadcast_value);
+
+ int x = window_start_x;
+ svbool_t pg = svwhilelt_b8(x, window_end_x);
+ const auto bf_0 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svmovlb_s32(svmovlb_s16(broadcast_value_vec)), voffset2)), vscale2);
+ const auto bf_1 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svmovlt_s32(svmovlb_s16(broadcast_value_vec)), voffset2)), vscale2);
+ const auto bf_2 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svmovlb_s32(svmovlt_s16(broadcast_value_vec)), voffset2)), vscale2);
+ const auto bf_3 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svmovlt_s32(svmovlt_s16(broadcast_value_vec)), voffset2)), vscale2);
+
+ do
+ {
+ const auto a = svld1_s8(pg, non_broadcast_input_ptr + x);
+ const auto af_0 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svmovlb_s32(svmovlb_s16(a)), voffset1)), vscale1);
+ const auto af_1 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svmovlt_s32(svmovlb_s16(a)), voffset1)), vscale1);
+ const auto af_2 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svmovlb_s32(svmovlt_s16(a)), voffset1)), vscale1);
+ const auto af_3 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svmovlt_s32(svmovlt_s16(a)), voffset1)), vscale1);
+
+ const auto rf_0 = svcvt_s32_f32_z(pg, svmla_f32_z(pg, voffseto, svadd_f32_z(pg, af_0, bf_0), invvscaleo));
+ const auto rf_1 = svcvt_s32_f32_z(pg, svmla_f32_z(pg, voffseto, svadd_f32_z(pg, af_1, bf_1), invvscaleo));
+ const auto rf_2 = svcvt_s32_f32_z(pg, svmla_f32_z(pg, voffseto, svadd_f32_z(pg, af_2, bf_2), invvscaleo));
+ const auto rf_3 = svcvt_s32_f32_z(pg, svmla_f32_z(pg, voffseto, svadd_f32_z(pg, af_3, bf_3), invvscaleo));
+
+ const auto pa = svqxtnt_s32(svqxtnb_s32(rf_0), rf_1);
+ const auto pb = svqxtnt_s32(svqxtnb_s32(rf_2), rf_3);
+ const auto res = svqxtnt_s16(svqxtnb_s16(pa), pb);
+
+ svst1_s8(pg, output_ptr + x, res);
+
+ x += svcntb();
+ pg = svwhilelt_b8(x, window_end_x);
+ }
+ while(svptest_any(all_true_pg, pg));
+ },
+ 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);
+
+ const auto vscale1 = svdup_n_f32(iq1_info.scale);
+ const auto vscale2 = svdup_n_f32(iq2_info.scale);
+ const auto voffset1 = svdup_n_s32(iq1_info.offset);
+ const auto voffset2 = svdup_n_s32(iq2_info.offset);
+
+ 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());
+
+ int x = window_start_x;
+ svbool_t pg = svwhilelt_b8(x, window_end_x);
+ do
+ {
+ const auto a = svld1_s8(pg, input1_ptr + x);
+ const auto b = svld1_s8(pg, input2_ptr + x);
+
+ const auto af_0 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svmovlb_s32(svmovlb_s16(a)), voffset1)), vscale1);
+ const auto af_1 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svmovlt_s32(svmovlb_s16(a)), voffset1)), vscale1);
+ const auto af_2 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svmovlb_s32(svmovlt_s16(a)), voffset1)), vscale1);
+ const auto af_3 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svmovlt_s32(svmovlt_s16(a)), voffset1)), vscale1);
+
+ const auto bf_0 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svmovlb_s32(svmovlb_s16(b)), voffset2)), vscale2);
+ const auto bf_1 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svmovlt_s32(svmovlb_s16(b)), voffset2)), vscale2);
+ const auto bf_2 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svmovlb_s32(svmovlt_s16(b)), voffset2)), vscale2);
+ const auto bf_3 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svsub_s32_z(pg, svmovlt_s32(svmovlt_s16(b)), voffset2)), vscale2);
+
+ const auto rf_0 = svcvt_s32_f32_z(pg, svmla_f32_z(pg, voffseto, svadd_f32_z(pg, af_0, bf_0), invvscaleo));
+ const auto rf_1 = svcvt_s32_f32_z(pg, svmla_f32_z(pg, voffseto, svadd_f32_z(pg, af_1, bf_1), invvscaleo));
+ const auto rf_2 = svcvt_s32_f32_z(pg, svmla_f32_z(pg, voffseto, svadd_f32_z(pg, af_2, bf_2), invvscaleo));
+ const auto rf_3 = svcvt_s32_f32_z(pg, svmla_f32_z(pg, voffseto, svadd_f32_z(pg, af_3, bf_3), invvscaleo));
+
+ const auto pa = svqxtnt_s32(svqxtnb_s32(rf_0), rf_1);
+ const auto pb = svqxtnt_s32(svqxtnb_s32(rf_2), rf_3);
+ const auto res = svqxtnt_s16(svqxtnb_s16(pa), pb);
+
+ svst1_s8(pg, output_ptr + x, res);
+
+ x += svcntb();
+ pg = svwhilelt_b8(x, window_end_x);
+ }
+ while(svptest_any(svptrue_b8(), pg));
+ },
+ input1, input2, output);
+ }
+}
+} // namespace cpu
+} // namespace arm_compute
+#endif /* defined(__ARM_FEATURE_SVE2) */
\ No newline at end of file
diff --git a/src/core/NEON/kernels/arithmetic_addition/impl/SVE/qsymm16.cpp b/src/core/NEON/kernels/arithmetic_addition/impl/SVE/qsymm16.cpp
new file mode 100644
index 0000000..c072cdb
--- /dev/null
+++ b/src/core/NEON/kernels/arithmetic_addition/impl/SVE/qsymm16.cpp
@@ -0,0 +1,156 @@
+/*
+ * Copyright (c) 2020-2021 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"
+#if defined(__ARM_FEATURE_SVE2)
+#include "src/core/NEON/SVEMath.h"
+#include <arm_sve.h>
+
+namespace arm_compute
+{
+namespace cpu
+{
+void arithmetic_addition_qsymm16_sve(const ITensor *in1, const ITensor *in2, ITensor *out, const ConvertPolicy &policy, const Window &window)
+{
+ ARM_COMPUTE_UNUSED(policy);
+
+ // 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 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 auto vscale1 = svdup_n_f32(iq1_info.scale);
+ const auto vscale2 = svdup_n_f32(iq2_info.scale);
+ const auto invvscaleo = svdup_n_f32(1.f / oq_info.scale);
+ const auto all_true_pg = svptrue_b16();
+
+ 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 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 auto broadcast_value_vec = svdup_n_s16(broadcast_value);
+
+ int x = window_start_x;
+ svbool_t pg = svwhilelt_b16(x, window_end_x);
+
+ const auto bf_0 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svmovlb_s32(broadcast_value_vec)), vscale2);
+ const auto bf_1 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svmovlt_s32(broadcast_value_vec)), vscale2);
+
+ do
+ {
+ const auto a = svld1_s16(pg, non_broadcast_input_ptr + x);
+ const auto af_0 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svmovlb_s32(a)), vscale1);
+ const auto af_1 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svmovlt_s32(a)), vscale1);
+
+ const auto rf_0 = svcvt_s32_f32_z(pg, svmul_f32_z(pg, svadd_f32_z(pg, af_0, bf_0), invvscaleo));
+ const auto rf_1 = svcvt_s32_f32_z(pg, svmul_f32_z(pg, svadd_f32_z(pg, af_1, bf_1), invvscaleo));
+
+ const auto res = svqxtnt_s32(svqxtnb_s32(rf_0), rf_1);
+
+ svst1_s16(pg, output_ptr + x, res);
+
+ x += svcnth();
+ pg = svwhilelt_b16(x, window_end_x);
+ }
+ while(svptest_any(all_true_pg, pg));
+ },
+ 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());
+
+ int x = window_start_x;
+ svbool_t pg = svwhilelt_b16(x, window_end_x);
+ do
+ {
+ auto a = svld1_s16(pg, input1_ptr + x);
+ auto b = svld1_s16(pg, input2_ptr + x);
+
+ const auto af_0 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svmovlb_s32(a)), vscale1);
+ const auto af_1 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svmovlt_s32(a)), vscale1);
+
+ const auto bf_0 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svmovlb_s32(b)), vscale2);
+ const auto bf_1 = svmul_f32_z(pg, svcvt_f32_s32_z(pg, svmovlt_s32(b)), vscale2);
+
+ const auto rf_0 = svcvt_s32_f32_z(pg, svmul_f32_z(pg, svadd_f32_z(pg, af_0, bf_0), invvscaleo));
+ const auto rf_1 = svcvt_s32_f32_z(pg, svmul_f32_z(pg, svadd_f32_z(pg, af_1, bf_1), invvscaleo));
+
+ const auto res = svqxtnt_s32(svqxtnb_s32(rf_0), rf_1);
+ svst1_s16(pg, output_ptr + x, res);
+
+ x += svcnth();
+ pg = svwhilelt_b16(x, window_end_x);
+ }
+ while(svptest_any(all_true_pg, pg));
+ },
+ input1, input2, output);
+ }
+}
+} // namespace cpu
+} // namespace arm_compute
+#endif /* defined(__ARM_FEATURE_SVE2) */
\ No newline at end of file
diff --git a/src/core/NEON/wrapper/intrinsics/intrinsics.h b/src/core/NEON/wrapper/intrinsics/intrinsics.h
index 6cf7f9d..4c7b674 100644
--- a/src/core/NEON/wrapper/intrinsics/intrinsics.h
+++ b/src/core/NEON/wrapper/intrinsics/intrinsics.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018-2020 Arm Limited.
+ * Copyright (c) 2018-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -80,6 +80,7 @@
#include "src/core/NEON/wrapper/intrinsics/svexp.h"
#include "src/core/NEON/wrapper/intrinsics/svlog.h"
#include "src/core/NEON/wrapper/intrinsics/svptrue.h"
+#include "src/core/NEON/wrapper/intrinsics/svqadd.h"
#include "src/core/NEON/wrapper/intrinsics/svsin.h"
#include "src/core/NEON/wrapper/intrinsics/svwhilelt.h"
#endif /* defined(__ARM_FEATURE_SVE) */
diff --git a/src/core/NEON/wrapper/intrinsics/svqadd.h b/src/core/NEON/wrapper/intrinsics/svqadd.h
new file mode 100644
index 0000000..fd45d82
--- /dev/null
+++ b/src/core/NEON/wrapper/intrinsics/svqadd.h
@@ -0,0 +1,60 @@
+/*
+ * Copyright (c) 2020-2021 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_WRAPPER_INTRINSICS_SVQADD_H
+#define SRC_CORE_NEON_WRAPPER_INTRINSICS_SVQADD_H
+#if defined(__ARM_FEATURE_SVE)
+#include <arm_sve.h>
+namespace arm_compute
+{
+namespace wrapper
+{
+#define SVQADD_IMPL_F(type, postfix, svppostfix) \
+ inline type svqadd(const type &val1, const type &val2) \
+ { \
+ return svadd_##postfix##_z(svptrue_##svppostfix(), val1, val2); \
+ }
+
+SVQADD_IMPL_F(svfloat32_t, f32, b32)
+SVQADD_IMPL_F(svfloat16_t, f16, b16)
+#undef SVQADD_IMPL_F
+
+#define SVQADD_IMPL(type, postfix) \
+ inline type svqadd(const type &val1, const type &val2) \
+ { \
+ return svqadd_##postfix(val1, val2); \
+ }
+
+SVQADD_IMPL(svint32_t, s32)
+SVQADD_IMPL(svint16_t, s16)
+SVQADD_IMPL(svint8_t, s8)
+SVQADD_IMPL(svuint32_t, u32)
+SVQADD_IMPL(svuint16_t, u16)
+SVQADD_IMPL(svuint8_t, u8)
+
+#undef SVQADD_IMPL
+} // namespace wrapper
+} // namespace arm_compute
+
+#endif /* defined(__ARM_FEATURE_SVE) */
+#endif /* SRC_CORE_NEON_WRAPPER_INTRINSICS_SVQADD_H */
\ No newline at end of file
diff --git a/src/core/common/Registrars.h b/src/core/common/Registrars.h
index 649fe46..112c83a 100644
--- a/src/core/common/Registrars.h
+++ b/src/core/common/Registrars.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2020 Arm Limited.
+ * Copyright (c) 2020-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -83,4 +83,14 @@
#define REGISTER_QSYMM16_SVE(func_name) nullptr
#endif /* defined(ENABLE_QSYMM16_KERNELS) */
+#if defined(ENABLE_INTEGER_KERNELS)
+#if defined(__ARM_FEATURE_SVE)
+#define REGISTER_INTEGER_SVE(func_name) &(func_name)
+#endif /* defined(__ARM_FEATURE_SVE) */
+#define REGISTER_INTEGER_NEON(func_name) &(func_name)
+#else /* defined(ENABLE_INTEGER_KERNELS) */
+#define REGISTER_INTEGER_NEON(func_name) nullptr
+#define REGISTER_INTEGER_SVE(func_name) nullptr
+#endif /* defined(ENABLE_INTEGER_KERNELS) */
+
#endif /* SRC_CORE_COMMON_REGISTRARS_H */