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authorMichalis Spyrou <michalis.spyrou@arm.com>2020-05-13 00:12:08 +0100
committerMichalis Spyrou <michalis.spyrou@arm.com>2020-05-20 14:22:55 +0000
commit5f39091e502b0805f292d79a2a7da66d485f70ac (patch)
treee6d8802ab3f0966849546b372897fd0605a99363 /src/core
parent7a7fe65a6bdd09fd08678ba2ddd8d0da18565bc6 (diff)
downloadComputeLibrary-5f39091e502b0805f292d79a2a7da66d485f70ac.tar.gz
COMPMID-3176: Remove padding from NEArithmeticSubtractionKernel
COMPMID-3487: Refactor NEArithmeticSubtractionKernel Refactored code in order to remove paddings. This resulted in a big increase in libary size so after some rework the total size dropped by 4Kb. Change-Id: I4e3014c2ae49c29c6090b195ea16620afcf6c09f Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3206 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/core')
-rw-r--r--src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp1018
1 files changed, 588 insertions, 430 deletions
diff --git a/src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp b/src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp
index 9b7b235c9f..8bfb37ea18 100644
--- a/src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp
+++ b/src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp
@@ -26,6 +26,7 @@
#include "arm_compute/core/CPP/Validate.h"
#include "arm_compute/core/NEON/NEAsymm.h"
#include "arm_compute/core/NEON/NESymm.h"
+#include "arm_compute/core/NEON/wrapper/wrapper.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Validate.h"
@@ -33,437 +34,628 @@ namespace arm_compute
{
namespace
{
-constexpr unsigned int num_elems_processed_per_iteration = 16;
-
-void sub_wrap_U8_U8_U8(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
+template <typename T>
+inline typename std::enable_if<std::is_same<T, int8_t>::value, int8_t>::type
+quantize(float val, const QuantizationInfo &info)
{
- 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);
-
- execute_window_loop(window, [&](const Coordinates &)
- {
- const uint8x16_t ta1 = vld1q_u8(input1.ptr());
- const uint8x16_t ta2 = vld1q_u8(input2.ptr());
+ return quantize_qasymm8_signed(val, info);
+}
- vst1q_u8(output.ptr(), vsubq_u8(ta1, ta2));
- },
- input1, input2, output);
+template <typename T>
+inline typename std::enable_if<std::is_same<T, uint8_t>::value, uint8_t>::type
+quantize(float val, const QuantizationInfo &info)
+{
+ return quantize_qasymm8(val, info);
}
-void sub_saturate_U8_U8_U8(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
+template <typename T>
+void sub_same(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, bool is_sat)
{
- 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);
+ /** NEON vector tag type. */
+ using ExactTagType = typename wrapper::traits::neon_bitvector_tag_t<T, wrapper::traits::BitWidth::W128>;
- execute_window_loop(window, [&](const Coordinates &)
- {
- const uint8x16_t ta1 = vld1q_u8(input1.ptr());
- const uint8x16_t ta2 = vld1q_u8(input2.ptr());
+ // 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());
- vst1q_u8(output.ptr(), vqsubq_u8(ta1, ta2));
- },
- input1, input2, output);
-}
+ // Clear X Dimension on execution window as we handle manually
+ Window win = window;
+ win.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+ constexpr int window_step_x = 16 / sizeof(T);
+ const auto window_start_x = static_cast<int>(window.x().start());
+ const auto window_end_x = static_cast<int>(window.x().end());
+ const bool is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0);
-void sub_saturate_QAYSMM8_QAYSMM8_QAYSMM8(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
-{
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);
- 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();
-
- execute_window_loop(window, [&](const Coordinates &)
+ if(is_broadcast_across_x)
{
- const float32x4x4_t ta1 = vdequantize(vld1q_u8(reinterpret_cast<const qasymm8_t *>(input1.ptr())), iq1_info);
- const float32x4x4_t ta2 = vdequantize(vld1q_u8(reinterpret_cast<const qasymm8_t *>(input2.ptr())), iq2_info);
+ 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 float32x4x4_t ta3 =
- {
- {
- vsubq_f32(ta1.val[0], ta2.val[0]),
- vsubq_f32(ta1.val[1], ta2.val[1]),
- vsubq_f32(ta1.val[2], ta2.val[2]),
- vsubq_f32(ta1.val[3], ta2.val[3]),
- }
- };
+ // Clear X Dimension on execution window as we handle manually
+ non_broadcast_win.set(Window::DimX, Window::Dimension(0, 1, 1));
- const uint8x16_t result = vquantize(ta3, oq_info);
+ Iterator broadcast_input(broadcast_tensor, broadcast_win);
+ Iterator non_broadcast_input(non_broadcast_tensor, non_broadcast_win);
+ Iterator output(out, win);
- vst1q_u8(reinterpret_cast<qasymm8_t *>(output.ptr()), result);
- },
- input1, input2, output);
-}
+ 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());
-void sub_saturate_QASYMM8_SIGNED_QASYMM8_SIGNED_QASYMM8_SIGNED(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
-{
- 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);
+ const T broadcast_value = *reinterpret_cast<const T *>(broadcast_input.ptr());
+ const auto broadcast_value_vec = wrapper::vdup_n(broadcast_value, ExactTagType{});
- 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();
+ // Compute S elements per iteration
+ int x = window_start_x;
+ for(; x <= (window_end_x - window_step_x); x += window_step_x)
+ {
+ const auto non_broadcast_v = wrapper::vloadq(non_broadcast_input_ptr + x);
+ auto res = is_sat ? wrapper::vqsub(broadcast_value_vec, non_broadcast_v) : wrapper::vsub(broadcast_value_vec, non_broadcast_v);
+ if(is_broadcast_input_2)
+ {
+ res = wrapper::vmul(res, wrapper::vdup_n(static_cast<T>(-1), ExactTagType{}));
+ }
+ wrapper::vstore(output_ptr + x, res);
+ }
- execute_window_loop(window, [&](const Coordinates &)
+ // Compute left-over elements
+ for(; x < window_end_x; ++x)
+ {
+ const auto non_broadcast_v = *(non_broadcast_input_ptr + x);
+ auto res = is_sat ? wrapper::sub_sat(broadcast_value, non_broadcast_v) : broadcast_value - non_broadcast_v;
+ if(is_broadcast_input_2)
+ {
+ res = static_cast<T>(-1) * res;
+ }
+
+ *(output_ptr + x) = res;
+ }
+ },
+ broadcast_input, non_broadcast_input, output);
+ }
+ else
{
- const float32x4x4_t ta1 = vdequantize(vld1q_s8(reinterpret_cast<const qasymm8_signed_t *>(input1.ptr())), iq1_info);
- const float32x4x4_t ta2 = vdequantize(vld1q_s8(reinterpret_cast<const qasymm8_signed_t *>(input2.ptr())), iq2_info);
+ // 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));
- const float32x4x4_t ta3 =
+ 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)
{
- vsubq_f32(ta1.val[0], ta2.val[0]),
- vsubq_f32(ta1.val[1], ta2.val[1]),
- vsubq_f32(ta1.val[2], ta2.val[2]),
- vsubq_f32(ta1.val[3], ta2.val[3]),
+ const auto val1 = wrapper::vloadq(input1_ptr + x);
+ const auto val2 = wrapper::vloadq(input2_ptr + x);
+ const auto res = is_sat ? wrapper::vqsub(val1, val2) : wrapper::vsub(val1, val2);
+ wrapper::vstore(output_ptr + x, res);
}
- };
- const int8x16_t result = vquantize_signed(ta3, oq_info);
-
- vst1q_s8(reinterpret_cast<qasymm8_signed_t *>(output.ptr()), result);
- },
- input1, input2, output);
+ // Compute left-over elements
+ for(; x < window_end_x; ++x)
+ {
+ const auto val1 = *(input1_ptr + x);
+ const auto val2 = *(input2_ptr + x);
+ *(output_ptr + x) = is_sat ? wrapper::sub_sat(val1, val2) : val1 - val2;
+ }
+ },
+ input1, input2, output);
+ }
}
-void sub_saturate_QSYMM16_QSYMM16_QSYMM16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
+template <typename T>
+void sub_quantized(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, bool is_sat)
{
- 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);
+ ARM_COMPUTE_UNUSED(is_sat);
+
+ // Create input windows
+ Window input1_win = window.broadcast_if_dimension_le_one(in1->info()->tensor_shape());
+ Window input2_win = window.broadcast_if_dimension_le_one(in2->info()->tensor_shape());
+
+ // Clear X Dimension on execution window as we handle manually
+ Window win = window;
+ win.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+ const int window_step_x = 16;
+ const auto window_start_x = static_cast<int>(window.x().start());
+ const auto window_end_x = static_cast<int>(window.x().end());
+ const bool is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0);
const UniformQuantizationInfo iq1_info = in1->info()->quantization_info().uniform();
const UniformQuantizationInfo iq2_info = in2->info()->quantization_info().uniform();
const UniformQuantizationInfo oq_info = out->info()->quantization_info().uniform();
- execute_window_loop(window, [&](const Coordinates &)
+ const float32x4_t vscale1 = vdupq_n_f32(iq1_info.scale);
+ const float32x4_t vscale2 = vdupq_n_f32(iq2_info.scale);
+ const float32x4_t invvscaleo = vdupq_n_f32(1.f / oq_info.scale);
+ const int32x4_t voffset1 = vdupq_n_s32(iq1_info.offset);
+ const int32x4_t voffset2 = vdupq_n_s32(iq2_info.offset);
+ const float32x4_t voffseto = vdupq_n_f32(oq_info.offset);
+
+ if(is_broadcast_across_x)
{
- const int16x8x2_t in1_s16 =
+ const bool is_broadcast_input_2 = input2_win.x().step() == 0;
+ Window broadcast_win = is_broadcast_input_2 ? input2_win : input1_win;
+ Window non_broadcast_win = !is_broadcast_input_2 ? input2_win : input1_win;
+ const ITensor *broadcast_tensor = is_broadcast_input_2 ? in2 : in1;
+ const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? in2 : in1;
+ const UniformQuantizationInfo broadcast_qinfo = broadcast_tensor->info()->quantization_info().uniform();
+ const UniformQuantizationInfo non_broadcast_qinfo = non_broadcast_tensor->info()->quantization_info().uniform();
+
+ // Clear X Dimension on execution window as we handle manually
+ non_broadcast_win.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+ Iterator broadcast_input(broadcast_tensor, broadcast_win);
+ Iterator non_broadcast_input(non_broadcast_tensor, non_broadcast_win);
+ Iterator output(out, win);
+
+ execute_window_loop(win, [&](const Coordinates &)
{
+ const auto non_broadcast_input_ptr = reinterpret_cast<const T *>(non_broadcast_input.ptr());
+ const auto output_ptr = reinterpret_cast<T *>(output.ptr());
+
+ const auto broadcast_value = *reinterpret_cast<const T *>(broadcast_input.ptr());
+ const auto broadcast_value_vec = wrapper::vdup_n(static_cast<T>(broadcast_value), wrapper::traits::vector_128_tag{});
+
+ const float32x4x4_t bf =
{
- vld1q_s16(reinterpret_cast<const qsymm16_t *>(input1.ptr())),
- vld1q_s16(reinterpret_cast<const qsymm16_t *>(input1.ptr()) + 8),
- }
- };
- const int16x8x2_t in2_s16 =
- {
+ {
+ vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgetlow(wrapper::vmovl(wrapper::vgetlow(broadcast_value_vec))))), voffset2)), vscale2),
+ vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgethigh(wrapper::vmovl(wrapper::vgetlow(broadcast_value_vec))))), voffset2)), vscale2),
+ vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgetlow(wrapper::vmovl(wrapper::vgethigh(broadcast_value_vec))))), voffset2)), vscale2),
+ vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgethigh(wrapper::vmovl(wrapper::vgethigh(broadcast_value_vec))))), voffset2)), vscale2),
+ }
+ };
+ const float bfs = static_cast<int32_t>(broadcast_value - broadcast_qinfo.offset) * broadcast_qinfo.scale;
+
+ // Compute S elements per iteration
+ int x = window_start_x;
+ for(; x <= (window_end_x - window_step_x); x += window_step_x)
{
- vld1q_s16(reinterpret_cast<const qsymm16_t *>(input2.ptr())),
- vld1q_s16(reinterpret_cast<const qsymm16_t *>(input2.ptr()) + 8),
+ const auto a = wrapper::vloadq(non_broadcast_input_ptr + x);
+
+ const float32x4x4_t af =
+ {
+ {
+ vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgetlow(wrapper::vmovl(wrapper::vgetlow(a))))), voffset1)), vscale1),
+ vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgethigh(wrapper::vmovl(wrapper::vgetlow(a))))), voffset1)), vscale1),
+ vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgetlow(wrapper::vmovl(wrapper::vgethigh(a))))), voffset1)), vscale1),
+ vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgethigh(wrapper::vmovl(wrapper::vgethigh(a))))), voffset1)), vscale1),
+ }
+ };
+
+ const int32x4x4_t rf =
+ {
+ {
+#ifdef __aarch64__
+ vcvtnq_s32_f32(vmlaq_f32(voffseto, is_broadcast_input_2 ? vsubq_f32(bf.val[0], af.val[0]) : vsubq_f32(af.val[0], bf.val[0]), invvscaleo)),
+ vcvtnq_s32_f32(vmlaq_f32(voffseto, is_broadcast_input_2 ? vsubq_f32(bf.val[1], af.val[1]) : vsubq_f32(af.val[1], bf.val[1]), invvscaleo)),
+ vcvtnq_s32_f32(vmlaq_f32(voffseto, is_broadcast_input_2 ? vsubq_f32(bf.val[2], af.val[2]) : vsubq_f32(af.val[2], bf.val[2]), invvscaleo)),
+ vcvtnq_s32_f32(vmlaq_f32(voffseto, is_broadcast_input_2 ? vsubq_f32(bf.val[3], af.val[3]) : vsubq_f32(af.val[3], bf.val[3]), invvscaleo)),
+#else //__aarch64__
+ vcvtq_s32_f32(vmlaq_f32(voffseto, is_broadcast_input_2 ? vsubq_f32(bf.val[0], af.val[0]) : vsubq_f32(af.val[0], bf.val[0]), invvscaleo)),
+ vcvtq_s32_f32(vmlaq_f32(voffseto, is_broadcast_input_2 ? vsubq_f32(bf.val[1], af.val[1]) : vsubq_f32(af.val[1], bf.val[1]), invvscaleo)),
+ vcvtq_s32_f32(vmlaq_f32(voffseto, is_broadcast_input_2 ? vsubq_f32(bf.val[2], af.val[2]) : vsubq_f32(af.val[2], bf.val[2]), invvscaleo)),
+ vcvtq_s32_f32(vmlaq_f32(voffseto, is_broadcast_input_2 ? vsubq_f32(bf.val[3], af.val[3]) : vsubq_f32(af.val[3], bf.val[3]), invvscaleo)),
+#endif //__aarch64__
+ }
+ };
+
+ const auto pa = wrapper::vqmov<T>(vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1])));
+ const auto pb = wrapper::vqmov<T>(vcombine_s16(vqmovn_s32(rf.val[2]), vqmovn_s32(rf.val[3])));
+ wrapper::vstore(output_ptr + x, wrapper::vcombine(pa, pb));
}
- };
- const float32x4x4_t ta1 = vdequantize(in1_s16, iq1_info);
- const float32x4x4_t ta2 = vdequantize(in2_s16, iq2_info);
- const float32x4x4_t ta3 =
- {
+ // Compute left-over elements
+ for(; x < window_end_x; ++x)
{
- vsubq_f32(ta1.val[0], ta2.val[0]),
- vsubq_f32(ta1.val[1], ta2.val[1]),
- vsubq_f32(ta1.val[2], ta2.val[2]),
- vsubq_f32(ta1.val[3], ta2.val[3]),
+ const float afs = static_cast<int32_t>(*(non_broadcast_input_ptr + x) - non_broadcast_qinfo.offset) * non_broadcast_qinfo.scale;
+ *(output_ptr + x) = quantize<T>((afs - bfs), out->info()->quantization_info());
}
- };
-
- const int16x8x2_t result = vquantize_qsymm16(ta3, oq_info);
-
- vst1q_s16(reinterpret_cast<qsymm16_t *>(output.ptr()), result.val[0]);
- vst1q_s16(reinterpret_cast<qsymm16_t *>(output.ptr()) + 8, result.val[1]);
- },
- input1, input2, output);
-}
+ },
+ 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));
-void sub_wrap_S16_S16_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
-{
- 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);
+ Iterator input1(in1, input1_win);
+ Iterator input2(in2, input2_win);
+ Iterator output(out, win);
- execute_window_loop(window, [&](const Coordinates &)
- {
- const int16x8x2_t ta1 =
- {
- {
- vld1q_s16(reinterpret_cast<const int16_t *>(input1.ptr())),
- vld1q_s16(reinterpret_cast<const int16_t *>(input1.ptr()) + 8),
- }
- };
- const int16x8x2_t ta2 =
+ 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)
{
- vld1q_s16(reinterpret_cast<const int16_t *>(input2.ptr())),
- vld1q_s16(reinterpret_cast<const int16_t *>(input2.ptr()) + 8),
+ const auto a = wrapper::vloadq(input1_ptr + x);
+ const auto b = wrapper::vloadq(input2_ptr + x);
+
+ const float32x4x4_t af =
+ {
+ {
+ vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgetlow(wrapper::vmovl(wrapper::vgetlow(a))))), voffset1)), vscale1),
+ vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgethigh(wrapper::vmovl(wrapper::vgetlow(a))))), voffset1)), vscale1),
+ vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgetlow(wrapper::vmovl(wrapper::vgethigh(a))))), voffset1)), vscale1),
+ vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgethigh(wrapper::vmovl(wrapper::vgethigh(a))))), voffset1)), vscale1),
+ }
+ };
+
+ const float32x4x4_t bf =
+ {
+ {
+ vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgetlow(wrapper::vmovl(wrapper::vgetlow(b))))), voffset2)), vscale2),
+ vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgethigh(wrapper::vmovl(wrapper::vgetlow(b))))), voffset2)), vscale2),
+ vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgetlow(wrapper::vmovl(wrapper::vgethigh(b))))), voffset2)), vscale2),
+ vmulq_f32(vcvtq_f32_s32(vsubq_s32(wrapper::vreinterpret(wrapper::vmovl(wrapper::vgethigh(wrapper::vmovl(wrapper::vgethigh(b))))), voffset2)), vscale2),
+ }
+ };
+
+ const int32x4x4_t rf =
+ {
+ {
+#ifdef __aarch64__
+ vcvtnq_s32_f32(vmlaq_f32(voffseto, vsubq_f32(af.val[0], bf.val[0]), invvscaleo)),
+ vcvtnq_s32_f32(vmlaq_f32(voffseto, vsubq_f32(af.val[1], bf.val[1]), invvscaleo)),
+ vcvtnq_s32_f32(vmlaq_f32(voffseto, vsubq_f32(af.val[2], bf.val[2]), invvscaleo)),
+ vcvtnq_s32_f32(vmlaq_f32(voffseto, vsubq_f32(af.val[3], bf.val[3]), invvscaleo)),
+#else //__aarch64__
+ vcvtq_s32_f32(vmlaq_f32(voffseto, vsubq_f32(af.val[0], bf.val[0]), invvscaleo)),
+ vcvtq_s32_f32(vmlaq_f32(voffseto, vsubq_f32(af.val[1], bf.val[1]), invvscaleo)),
+ vcvtq_s32_f32(vmlaq_f32(voffseto, vsubq_f32(af.val[2], bf.val[2]), invvscaleo)),
+ vcvtq_s32_f32(vmlaq_f32(voffseto, vsubq_f32(af.val[3], bf.val[3]), invvscaleo)),
+#endif //__aarch64__
+ }
+ };
+
+ const auto pa = wrapper::vqmov<T>(vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1])));
+ const auto pb = wrapper::vqmov<T>(vcombine_s16(vqmovn_s32(rf.val[2]), vqmovn_s32(rf.val[3])));
+ wrapper::vstore(output_ptr + x, wrapper::vcombine(pa, pb));
}
- };
- const int16x8x2_t ta3 =
- {
+ // Compute left-over elements
+ for(; x < window_end_x; ++x)
{
- vsubq_s16(ta1.val[0], ta2.val[0]),
- vsubq_s16(ta1.val[1], ta2.val[1])
- }
- };
+ 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;
- vst1q_s16(reinterpret_cast<int16_t *>(output.ptr()), ta3.val[0]);
- vst1q_s16(reinterpret_cast<int16_t *>(output.ptr()) + 8, ta3.val[1]);
- },
- input1, input2, output);
+ *(output_ptr + x) = quantize<T>((afs - bfs), out->info()->quantization_info());
+ }
+ },
+ input1, input2, output);
+ }
}
-void sub_saturate_S16_S16_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
+void sub_QSYMM16_QSYMM16_QSYMM16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, bool is_sat)
{
- 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);
+ ARM_COMPUTE_UNUSED(is_sat);
+
+ // Create input windows
+ Window input1_win = window.broadcast_if_dimension_le_one(in1->info()->tensor_shape());
+ Window input2_win = window.broadcast_if_dimension_le_one(in2->info()->tensor_shape());
+
+ // Clear X Dimension on execution window as we handle manually
+ Window win = window;
+ win.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+ const int window_step_x = 8;
+ const auto window_start_x = static_cast<int>(window.x().start());
+ const auto window_end_x = static_cast<int>(window.x().end());
+ const bool is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0);
+
+ const UniformQuantizationInfo iq1_info = in1->info()->quantization_info().uniform();
+ const UniformQuantizationInfo iq2_info = in2->info()->quantization_info().uniform();
+ const UniformQuantizationInfo oq_info = out->info()->quantization_info().uniform();
+
+ const float32x4_t vscale1 = vdupq_n_f32(iq1_info.scale);
+ const float32x4_t vscale2 = vdupq_n_f32(iq2_info.scale);
+ const float32x4_t invvscaleo = vdupq_n_f32(1.f / oq_info.scale);
- execute_window_loop(window, [&](const Coordinates &)
+ if(is_broadcast_across_x)
{
- const int16x8x2_t ta1 =
+ 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 =
{
- vld1q_s16(reinterpret_cast<const int16_t *>(input1.ptr())),
- vld1q_s16(reinterpret_cast<const int16_t *>(input1.ptr()) + 8),
- }
- };
- const int16x8x2_t ta2 =
- {
+ {
+ 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)
{
- vld1q_s16(reinterpret_cast<const int16_t *>(input2.ptr())),
- vld1q_s16(reinterpret_cast<const int16_t *>(input2.ptr()) + 8),
+ const int16x8_t a = vld1q_s16(non_broadcast_input_ptr + x);
+ const float32x4x2_t af =
+ {
+ {
+ vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(a))), vscale1),
+ vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(a))), vscale1),
+ }
+ };
+
+ const int32x4x4_t rf =
+ {
+ {
+#ifdef __aarch64__
+ vcvtnq_s32_f32(vmulq_f32(is_broadcast_input_2 ? vsubq_f32(bf.val[0], af.val[0]) : vsubq_f32(af.val[0], bf.val[0]), invvscaleo)),
+ vcvtnq_s32_f32(vmulq_f32(is_broadcast_input_2 ? vsubq_f32(bf.val[1], af.val[1]) : vsubq_f32(af.val[1], bf.val[1]), invvscaleo)),
+#else //__aarch64__
+ vcvtq_s32_f32(vmulq_f32(is_broadcast_input_2 ? vsubq_f32(bf.val[0], af.val[0]) : vsubq_f32(af.val[0], bf.val[0]), invvscaleo)),
+ vcvtq_s32_f32(vmulq_f32(is_broadcast_input_2 ? vsubq_f32(bf.val[1], af.val[1]) : vsubq_f32(af.val[1], bf.val[1]), invvscaleo)),
+#endif //__aarch64__
+ }
+ };
+
+ const int16x8_t pa = vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1]));
+ vst1q_s16(output_ptr + x, pa);
}
- };
- const int16x8x2_t ta3 =
- {
+ // Compute left-over elements
+ for(; x < window_end_x; ++x)
{
- vqsubq_s16(ta1.val[0], ta2.val[0]),
- vqsubq_s16(ta1.val[1], ta2.val[1])
+ const float afs = static_cast<int32_t>(*(non_broadcast_input_ptr + x)) * non_broadcast_qinfo.scale;
+ *(output_ptr + x) = quantize_qsymm16(is_broadcast_input_2 ? (bfs - afs) : (afs - bfs), oq_info);
}
- };
-
- vst1q_s16(reinterpret_cast<int16_t *>(output.ptr()), ta3.val[0]);
- vst1q_s16(reinterpret_cast<int16_t *>(output.ptr()) + 8, ta3.val[1]);
- },
- input1, input2, output);
-}
+ },
+ 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));
-void sub_F16_F16_F16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
-{
-#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
- 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);
+ Iterator input1(in1, input1_win);
+ Iterator input2(in2, input2_win);
+ Iterator output(out, win);
- execute_window_loop(window, [&](const Coordinates &)
- {
- const float16x8x2_t a =
- {
- {
- vld1q_f16(reinterpret_cast<const float16_t *>(input1.ptr())),
- vld1q_f16(reinterpret_cast<const float16_t *>(input1.ptr()) + 8),
- }
- };
- const float16x8x2_t b =
+ 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)
{
- vld1q_f16(reinterpret_cast<const float16_t *>(input2.ptr())),
- vld1q_f16(reinterpret_cast<const float16_t *>(input2.ptr()) + 8),
+ const int16x8_t a = vld1q_s16(input1_ptr + x);
+ const int16x8_t b = vld1q_s16(input2_ptr + x);
+
+ const float32x4x2_t af =
+ {
+ {
+ vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(a))), vscale1),
+ vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(a))), vscale1),
+ }
+ };
+
+ const float32x4x2_t bf =
+ {
+ {
+ vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(b))), vscale2),
+ vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(b))), vscale2),
+ }
+ };
+
+ const int32x4x2_t rf =
+ {
+ {
+#ifdef __aarch64__
+ vcvtnq_s32_f32(vmulq_f32(vsubq_f32(af.val[0], bf.val[0]), invvscaleo)),
+ vcvtnq_s32_f32(vmulq_f32(vsubq_f32(af.val[1], bf.val[1]), invvscaleo)),
+#else //__aarch64__
+ vcvtq_s32_f32(vmulq_f32(vsubq_f32(af.val[0], bf.val[0]), invvscaleo)),
+ vcvtq_s32_f32(vmulq_f32(vsubq_f32(af.val[1], bf.val[1]), invvscaleo)),
+#endif //__aarch64__
+ }
+ };
+
+ const int16x8_t pa = vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1]));
+ vst1q_s16(output_ptr + x, pa);
}
- };
- const float16x8x2_t res =
- {
+
+ // Compute left-over elements
+ for(; x < window_end_x; ++x)
{
- vsubq_f16(a.val[0], b.val[0]),
- vsubq_f16(a.val[1], b.val[1]),
+ 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());
}
- };
-
- vst1q_f16(reinterpret_cast<float16_t *>(output.ptr()), res.val[0]);
- vst1q_f16(reinterpret_cast<float16_t *>(output.ptr()) + 8, res.val[1]);
- },
- input1, input2, output);
-#else /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
- ARM_COMPUTE_UNUSED(in1);
- ARM_COMPUTE_UNUSED(in2);
- ARM_COMPUTE_UNUSED(out);
- ARM_COMPUTE_UNUSED(window);
- ARM_COMPUTE_ERROR("Not supported, recompile the library with arch=arm64-v8.2-a");
-#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
+ },
+ input1, input2, output);
+ }
}
-void sub_F32_F32_F32(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
+void sub_S16_U8_S16_impl(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, bool is_sat, bool is_swapped)
{
- 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);
+ // 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());
- execute_window_loop(window, [&](const Coordinates &)
+ // 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 float32x4x4_t ta1 =
+ const auto input1_ptr = reinterpret_cast<const int16_t *>(input1.ptr());
+ const auto input2_ptr = reinterpret_cast<const uint8_t *>(input2.ptr());
+ const auto output_ptr = reinterpret_cast<int16_t *>(output.ptr());
+
+ if(!is_sat)
{
+ // Compute S elements per iteration
+ int x = window_start_x;
+ for(; x <= (window_end_x - window_step_x); x += window_step_x)
{
- vld1q_f32(reinterpret_cast<const float *>(input1.ptr())),
- vld1q_f32(reinterpret_cast<const float *>(input1.ptr()) + 4),
- vld1q_f32(reinterpret_cast<const float *>(input1.ptr()) + 8),
- vld1q_f32(reinterpret_cast<const float *>(input1.ptr()) + 12),
+ const auto vin1 = wrapper::vloadq(input1_ptr + x);
+ const auto vin2 = vreinterpretq_s16_u16(wrapper::vmovl(wrapper::vload(input2_ptr + x)));
+ const auto res = is_swapped ? wrapper::vsub(vin2, vin1) : wrapper::vsub(vin1, vin2);
+ wrapper::vstore(output_ptr + x, res);
}
- };
- const float32x4x4_t ta2 =
- {
+
+ // Compute left-over elements
+ for(; x < window_end_x; ++x)
{
- vld1q_f32(reinterpret_cast<const float *>(input2.ptr())),
- vld1q_f32(reinterpret_cast<const float *>(input2.ptr()) + 4),
- vld1q_f32(reinterpret_cast<const float *>(input2.ptr()) + 8),
- vld1q_f32(reinterpret_cast<const float *>(input2.ptr()) + 12),
+ const auto res = is_swapped ? static_cast<int16_t>(*(input2_ptr + x)) - *(input1_ptr + x) : *(input1_ptr + x) - static_cast<int16_t>(*(input2_ptr + x));
+ *(output_ptr + x) = res;
}
- };
-
- const float32x4x4_t ta3 =
+ }
+ else
{
+ // Compute S elements per iteration
+ int x = window_start_x;
+ for(; x <= (window_end_x - window_step_x); x += window_step_x)
{
- vsubq_f32(ta1.val[0], ta2.val[0]),
- vsubq_f32(ta1.val[1], ta2.val[1]),
- vsubq_f32(ta1.val[2], ta2.val[2]),
- vsubq_f32(ta1.val[3], ta2.val[3]),
+ const auto vin1 = wrapper::vloadq(input1_ptr + x);
+ const auto vin2 = vreinterpretq_s16_u16(wrapper::vmovl(wrapper::vload(input2_ptr + x)));
+ const auto res = is_swapped ? wrapper::vqsub(vin2, vin1) : wrapper::vqsub(vin1, vin2);
+ wrapper::vstore(output_ptr + x, res);
}
- };
-
- vst1q_f32(reinterpret_cast<float *>(output.ptr()), ta3.val[0]);
- vst1q_f32(reinterpret_cast<float *>(output.ptr()) + 4, ta3.val[1]);
- vst1q_f32(reinterpret_cast<float *>(output.ptr()) + 8, ta3.val[2]);
- vst1q_f32(reinterpret_cast<float *>(output.ptr()) + 12, ta3.val[3]);
- },
- input1, input2, output);
-}
-void sub_wrap_S16_U8_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
-{
- 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);
- execute_window_loop(window, [&](const Coordinates &)
- {
- const uint8x16_t bv_0 = vld1q_u8(input2.ptr());
- int16x8_t a1_0 = vld1q_s16(reinterpret_cast<const int16_t *>(input1.ptr()));
- int16x8_t a2_0 = vld1q_s16(reinterpret_cast<const int16_t *>(input1.ptr()) + 8);
-
- a1_0 = vsubq_s16(a1_0, vreinterpretq_s16_u16(vmovl_u8(vget_low_u8(bv_0))));
- a2_0 = vsubq_s16(a2_0, vreinterpretq_s16_u16(vmovl_u8(vget_high_u8(bv_0))));
-
- vst1q_s16(reinterpret_cast<int16_t *>(output.ptr()), a1_0);
- vst1q_s16(reinterpret_cast<int16_t *>(output.ptr()) + 8, a2_0);
+ // Compute left-over elements
+ for(; x < window_end_x; ++x)
+ {
+ const auto res = is_swapped ? wrapper::sub_sat(static_cast<int16_t>(*(input2_ptr + x)), *(input1_ptr + x)) : wrapper::sub_sat(*(input1_ptr + x), static_cast<int16_t>(*(input2_ptr + x)));
+ *(output_ptr + x) = res;
+ }
+ }
},
input1, input2, output);
}
-void sub_saturate_S16_U8_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
+void sub_S16_U8_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, bool is_sat)
{
- 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);
-
- execute_window_loop(window, [&](const Coordinates &)
- {
- const uint8x16_t bv_0 = vld1q_u8(input2.ptr());
- int16x8_t a1_0 = vld1q_s16(reinterpret_cast<const int16_t *>(input1.ptr()));
- int16x8_t a2_0 = vld1q_s16(reinterpret_cast<const int16_t *>(input1.ptr()) + 8);
-
- a1_0 = vqsubq_s16(a1_0, vreinterpretq_s16_u16(vmovl_u8(vget_low_u8(bv_0))));
- a2_0 = vqsubq_s16(a2_0, vreinterpretq_s16_u16(vmovl_u8(vget_high_u8(bv_0))));
-
- vst1q_s16(reinterpret_cast<int16_t *>(output.ptr()), a1_0);
- vst1q_s16(reinterpret_cast<int16_t *>(output.ptr()) + 8, a2_0);
- },
- input1, input2, output);
+ sub_S16_U8_S16_impl(in1, in2, out, window, is_sat, false);
}
-void sub_wrap_U8_S16_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
+void sub_U8_S16_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, bool is_sat)
{
- 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);
-
- execute_window_loop(window, [&](const Coordinates &)
- {
- const uint8x16_t bv_0 = vld1q_u8(input1.ptr());
- int16x8_t a1_0 = vld1q_s16(reinterpret_cast<const int16_t *>(input2.ptr()));
- int16x8_t a2_0 = vld1q_s16(reinterpret_cast<const int16_t *>(input2.ptr()) + 8);
-
- a1_0 = vsubq_s16(vreinterpretq_s16_u16(vmovl_u8(vget_low_u8(bv_0))), a1_0);
- a2_0 = vsubq_s16(vreinterpretq_s16_u16(vmovl_u8(vget_high_u8(bv_0))), a2_0);
-
- vst1q_s16(reinterpret_cast<int16_t *>(output.ptr()), a1_0);
- vst1q_s16(reinterpret_cast<int16_t *>(output.ptr()) + 8, a2_0);
- },
- input1, input2, output);
+ // Swap arguments
+ sub_S16_U8_S16_impl(in2, in1, out, window, is_sat, true);
}
-void sub_saturate_U8_S16_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
+void sub_U8_U8_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, bool is_sat)
{
- 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);
+ // 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());
- execute_window_loop(window, [&](const Coordinates &)
- {
- const uint8x16_t bv_0 = vld1q_u8(input1.ptr());
- int16x8_t a1_0 = vld1q_s16(reinterpret_cast<const int16_t *>(input2.ptr()));
- int16x8_t a2_0 = vld1q_s16(reinterpret_cast<const int16_t *>(input2.ptr()) + 8);
+ // 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));
- a1_0 = vqsubq_s16(vreinterpretq_s16_u16(vmovl_u8(vget_low_u8(bv_0))), a1_0);
- a2_0 = vqsubq_s16(vreinterpretq_s16_u16(vmovl_u8(vget_high_u8(bv_0))), a2_0);
+ Iterator input1(in1, input1_win);
+ Iterator input2(in2, input2_win);
+ Iterator output(out, win);
- vst1q_s16(reinterpret_cast<int16_t *>(output.ptr()), a1_0);
- vst1q_s16(reinterpret_cast<int16_t *>(output.ptr()) + 8, a2_0);
- },
- input1, input2, output);
-}
+ 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());
-void sub_wrap_U8_U8_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
-{
- 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);
-
- execute_window_loop(window, [&](const Coordinates &)
+ execute_window_loop(win, [&](const Coordinates &)
{
- const uint8x16_t av_0 = vld1q_u8(input1.ptr());
- const uint8x16_t bv_0 = vld1q_u8(input2.ptr());
+ 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());
- const int16x8_t a1_0 = vsubq_s16(vreinterpretq_s16_u16(vmovl_u8(vget_low_u8(av_0))),
- vreinterpretq_s16_u16(vmovl_u8(vget_low_u8(bv_0))));
- const int16x8_t a2_0 = vsubq_s16(vreinterpretq_s16_u16(vmovl_u8(vget_high_u8(av_0))),
- vreinterpretq_s16_u16(vmovl_u8(vget_high_u8(bv_0))));
-
- vst1q_s16(reinterpret_cast<int16_t *>(output.ptr()), a1_0);
- vst1q_s16(reinterpret_cast<int16_t *>(output.ptr()) + 8, a2_0);
- },
- input1, input2, output);
-}
-
-void sub_saturate_U8_U8_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
-{
- 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);
-
- execute_window_loop(window, [&](const Coordinates &)
- {
- const uint8x16_t av_0 = vld1q_u8(input1.ptr());
- const uint8x16_t bv_0 = vld1q_u8(input2.ptr());
+ if(!is_sat)
+ {
+ // Compute S elements per iteration
+ int x = window_start_x;
+ for(; x <= (window_end_x - window_step_x); x += window_step_x)
+ {
+ const auto vin1 = vreinterpretq_s16_u16(wrapper::vmovl(wrapper::vload(input1_ptr + x)));
+ const auto vin2 = vreinterpretq_s16_u16(wrapper::vmovl(wrapper::vload(input2_ptr + x)));
+ wrapper::vstore(output_ptr + x, wrapper::vsub(vin1, vin2));
+ }
- const int16x8_t a1_0 = vqsubq_s16(vreinterpretq_s16_u16(vmovl_u8(vget_low_u8(av_0))),
- vreinterpretq_s16_u16(vmovl_u8(vget_low_u8(bv_0))));
- const int16x8_t a2_0 = vqsubq_s16(vreinterpretq_s16_u16(vmovl_u8(vget_high_u8(av_0))),
- vreinterpretq_s16_u16(vmovl_u8(vget_high_u8(bv_0))));
+ // Compute left-over elements
+ for(; x < window_end_x; ++x)
+ {
+ *(output_ptr + x) = static_cast<int16_t>(*(input1_ptr + x)) - static_cast<int16_t>(*(input2_ptr + x));
+ }
+ }
+ else
+ {
+ // Compute S elements per iteration
+ int x = window_start_x;
+ for(; x <= (window_end_x - window_step_x); x += window_step_x)
+ {
+ const auto vin1 = vreinterpretq_s16_u16(wrapper::vmovl(wrapper::vload(input1_ptr + x)));
+ const auto vin2 = vreinterpretq_s16_u16(wrapper::vmovl(wrapper::vload(input2_ptr + x)));
+ wrapper::vstore(output_ptr + x, wrapper::vqsub(vin1, vin2));
+ }
- vst1q_s16(reinterpret_cast<int16_t *>(output.ptr()), a1_0);
- vst1q_s16(reinterpret_cast<int16_t *>(output.ptr()) + 8, a2_0);
+ // Compute left-over elements
+ for(; x < window_end_x; ++x)
+ {
+ *(output_ptr + x) = wrapper::sub_sat(static_cast<int16_t>(*(input1_ptr + x)),
+ static_cast<int16_t>(*(input2_ptr + x)));
+ }
+ }
},
input1, input2, output);
}
@@ -519,64 +711,10 @@ inline Status validate_arguments(const ITensorInfo &input1, const ITensorInfo &i
}
return Status{};
}
-
-inline std::pair<Status, Window> validate_and_configure_window(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output)
-{
- const std::pair<TensorShape, ValidRegion> broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(input1, input2);
- const TensorShape &out_shape = broadcast_pair.first;
- const ValidRegion &valid_region = broadcast_pair.second;
-
- // Auto initialize output if not initialized
- {
- set_shape_if_empty(output, out_shape);
-
- if(input1.data_type() == DataType::S16 || input2.data_type() == DataType::S16)
- {
- set_format_if_unknown(output, Format::S16);
- }
- else if(input1.data_type() == DataType::F16 || input2.data_type() == DataType::F16)
- {
- set_format_if_unknown(output, Format::F16);
- }
- else if(input1.data_type() == DataType::F32 || input2.data_type() == DataType::F32)
- {
- set_format_if_unknown(output, Format::F32);
- }
- else if(input1.data_type() == DataType::QASYMM8 || input2.data_type() == DataType::QASYMM8)
- {
- set_data_type_if_unknown(output, DataType::QASYMM8);
- }
- else if(input1.data_type() == DataType::QASYMM8_SIGNED || input2.data_type() == DataType::QASYMM8_SIGNED)
- {
- set_data_type_if_unknown(output, DataType::QASYMM8_SIGNED);
- }
- else if(input1.data_type() == DataType::QSYMM16 || input2.data_type() == DataType::QSYMM16)
- {
- set_data_type_if_unknown(output, DataType::QSYMM16);
- }
- }
-
- Window win = calculate_max_window(valid_region, Steps(num_elems_processed_per_iteration));
- Window win_input1 = win.broadcast_if_dimension_le_one(input1);
- Window win_input2 = win.broadcast_if_dimension_le_one(input2);
-
- AccessWindowHorizontal input1_access(&input1, 0, num_elems_processed_per_iteration);
- AccessWindowHorizontal input2_access(&input2, 0, num_elems_processed_per_iteration);
- AccessWindowHorizontal output_access(&output, 0, num_elems_processed_per_iteration);
-
- bool window_changed = update_window_and_padding(win_input1, input1_access)
- || update_window_and_padding(win_input2, input2_access)
- || update_window_and_padding(win, output_access);
-
- output_access.set_valid_region(win, valid_region);
-
- Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
- return std::make_pair(err, win);
-}
} // namespace
NEArithmeticSubtractionKernel::NEArithmeticSubtractionKernel()
- : _func(nullptr), _input1(nullptr), _input2(nullptr), _output(nullptr)
+ : _func(nullptr), _input1(nullptr), _input2(nullptr), _output(nullptr), _policy(ConvertPolicy::WRAP)
{
}
@@ -585,57 +723,84 @@ void NEArithmeticSubtractionKernel::configure(const ITensor *input1, const ITens
ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(*input1->info(), *input2->info(), *output->info(), policy));
- // Configure kernel window
- auto win_config = validate_and_configure_window(*input1->info(), *input2->info(), *output->info());
- ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
-
- static std::map<std::string, NEArithmeticSubtractionKernel::SubFunction *> map_function =
- {
- { "sub_wrap_U8_U8_U8", &sub_wrap_U8_U8_U8 },
- { "sub_wrap_U8_U8_S16", &sub_wrap_U8_U8_S16 },
- { "sub_saturate_U8_U8_U8", &sub_saturate_U8_U8_U8 },
- { "sub_saturate_U8_U8_S16", &sub_saturate_U8_U8_S16 },
- { "sub_saturate_QASYMM8_QASYMM8_QASYMM8", &sub_saturate_QAYSMM8_QAYSMM8_QAYSMM8 },
- { "sub_saturate_QASYMM8_SIGNED_QASYMM8_SIGNED_QASYMM8_SIGNED", &sub_saturate_QASYMM8_SIGNED_QASYMM8_SIGNED_QASYMM8_SIGNED },
- { "sub_saturate_QSYMM16_QSYMM16_QSYMM16", &sub_saturate_QSYMM16_QSYMM16_QSYMM16 },
- { "sub_wrap_U8_S16_S16", &sub_wrap_U8_S16_S16 },
- { "sub_wrap_S16_U8_S16", &sub_wrap_S16_U8_S16 },
- { "sub_saturate_U8_S16_S16", &sub_saturate_U8_S16_S16 },
- { "sub_saturate_S16_U8_S16", &sub_saturate_S16_U8_S16 },
- { "sub_wrap_S16_S16_S16", &sub_wrap_S16_S16_S16 },
- { "sub_saturate_S16_S16_S16", &sub_saturate_S16_S16_S16 },
- { "sub_wrap_F32_F32_F32", &sub_F32_F32_F32 },
- { "sub_saturate_F32_F32_F32", &sub_F32_F32_F32 },
- { "sub_wrap_F16_F16_F16", &sub_F16_F16_F16 },
- { "sub_saturate_F16_F16_F16", &sub_F16_F16_F16 },
- };
-
_input1 = input1;
_input2 = input2;
_output = output;
+ _policy = policy;
- std::string function_to_call("sub_");
- function_to_call += policy == ConvertPolicy::WRAP ? "wrap_" : "saturate_";
- function_to_call += string_from_data_type(input1->info()->data_type()) + "_";
- function_to_call += string_from_data_type(input2->info()->data_type()) + "_";
- function_to_call += string_from_data_type(output->info()->data_type());
+ const std::pair<TensorShape, ValidRegion> broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(*input1->info(), *input2->info());
+ const TensorShape &out_shape = broadcast_pair.first;
+ const ValidRegion &valid_region = broadcast_pair.second;
- auto it = map_function.find(function_to_call);
+ // Auto initialize output if not initialized
+ set_shape_if_empty(*output->info(), out_shape);
- if(it != map_function.end())
+ switch(input1->info()->data_type())
{
- _func = it->second;
+ case DataType::U8:
+ if(input2->info()->data_type() == DataType::U8 && output->info()->data_type() == DataType::U8)
+ {
+ _func = &sub_same<uint8_t>;
+ }
+ else if(input2->info()->data_type() == DataType::U8 && output->info()->data_type() == DataType::S16)
+ {
+ _func = &sub_U8_U8_S16;
+ }
+ else
+ {
+ _func = &sub_U8_S16_S16;
+ }
+ break;
+ case DataType::QASYMM8:
+ _func = &sub_quantized<uint8_t>;
+ set_data_type_if_unknown(*output->info(), DataType::QASYMM8);
+ break;
+ case DataType::QASYMM8_SIGNED:
+ _func = &sub_quantized<int8_t>;
+ set_data_type_if_unknown(*output->info(), DataType::QASYMM8_SIGNED);
+ break;
+ case DataType::S16:
+ if(input2->info()->data_type() == DataType::U8)
+ {
+ _func = &sub_S16_U8_S16;
+ }
+ else
+ {
+ _func = &sub_same<int16_t>;
+ }
+ set_format_if_unknown(*output->info(), Format::S16);
+ break;
+ case DataType::QSYMM16:
+ _func = &sub_QSYMM16_QSYMM16_QSYMM16;
+ set_data_type_if_unknown(*output->info(), DataType::QSYMM16);
+ break;
+#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+ case DataType::F16:
+ _func = &sub_same<float16_t>;
+ set_format_if_unknown(*output->info(), Format::F16);
+ break;
+#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
+ case DataType::F32:
+ _func = &sub_same<float>;
+ set_format_if_unknown(*output->info(), Format::F32);
+ break;
+ default:
+ _func = nullptr;
}
- INEKernel::configure(win_config.second);
+ // NEArithmeticSubtractionKernel doesn't need padding so update_window_and_padding() can be skipped
+ Coordinates coord;
+ coord.set_num_dimensions(output->info()->num_dimensions());
+ output->info()->set_valid_region(valid_region);
+ Window win = calculate_max_window(valid_region, Steps());
+
+ INEKernel::configure(win);
}
Status NEArithmeticSubtractionKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output);
-
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(*input1, *input2, *output, policy));
- ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(*input1->clone(), *input2->clone(), *output->clone()).first);
return Status{};
}
@@ -647,13 +812,6 @@ void NEArithmeticSubtractionKernel::run(const Window &window, const ThreadInfo &
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
ARM_COMPUTE_ERROR_ON(_func == nullptr);
- (*_func)(_input1, _input2, _output, window);
-}
-
-BorderSize NEArithmeticSubtractionKernel::border_size() const
-{
- const unsigned int replicateSize = _output->info()->dimension(0) - std::min(_input1->info()->dimension(0), _input2->info()->dimension(0));
- const unsigned int border = std::min<unsigned int>(num_elems_processed_per_iteration - 1U, replicateSize);
- return BorderSize{ 0, border, 0, 0 };
+ (*_func)(_input1, _input2, _output, window, (_policy == ConvertPolicy::SATURATE));
}
-} // namespace arm_compute \ No newline at end of file
+} // namespace arm_compute