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diff --git a/src/core/cpu/kernels/elementwise/sve/elementwise_quantized_list.h b/src/core/cpu/kernels/elementwise/sve/elementwise_quantized_list.h
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index 6c5524e284..0000000000
--- a/src/core/cpu/kernels/elementwise/sve/elementwise_quantized_list.h
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@@ -1,366 +0,0 @@
-/*
- * Copyright (c) 2021 Arm Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#ifndef SRC_CORE_SVE_KERNELS_ELEMENTWISE_QUANTIZED_LIST_H
-#define SRC_CORE_SVE_KERNELS_ELEMENTWISE_QUANTIZED_LIST_H
-
-#if defined(__ARM_FEATURE_SVE2)
-
-#include "src/core/NEON/wrapper/svtraits.h"
-#include "src/core/cpu/kernels/elementwise/sve/elementwise_list.h"
-
-namespace arm_compute
-{
-namespace cpu
-{
-using namespace arm_compute::wrapper;
-
-template <typename InputScalarType, typename OutputScalarType, typename OperatorType>
-struct QuantizedLoopArguments
-{
- OperatorType op;
- const InputScalarType *input1_ptr;
- const InputScalarType *input2_ptr;
- OutputScalarType *output_ptr;
-
- const svint32_t &in1_offset;
- const svint32_t &in2_offset;
- const svint32_t &out_offset;
- const svfloat32_t &in1_scale;
- const svfloat32_t &in2_scale;
- const svfloat32_t &out_scale;
-};
-
-template <typename InputScalarType, typename OutputScalarType, typename OperatorType>
-struct BroadcastQuantizedLoopArguments
-{
- OperatorType op;
- const InputScalarType *input1_ptr;
- float broadcast_value;
- OutputScalarType *output_ptr;
- bool reorder;
-
- const svint32_t &in1_offset;
- const svint32_t &out_offset;
- const svfloat32_t &in1_scale;
- const svfloat32_t &out_scale;
-};
-
-svfloat32x4_t load_quantized(const int8_t *ptr, svbool_t pg, const svint32_t &offset, const svfloat32_t &scale)
-{
- auto x = svld1(pg, ptr);
-
- const auto widened = svcreate4(
- svmovlb(svmovlb(x)),
- svmovlt(svmovlb(x)),
- svmovlb(svmovlt(x)),
- svmovlt(svmovlt(x)));
-
- pg = svptrue_b8();
-
- return svcreate4(
- svmul_z(pg, svcvt_f32_z(pg, svsub_z(pg, svget4(widened, 0), offset)), scale),
- svmul_z(pg, svcvt_f32_z(pg, svsub_z(pg, svget4(widened, 1), offset)), scale),
- svmul_z(pg, svcvt_f32_z(pg, svsub_z(pg, svget4(widened, 2), offset)), scale),
- svmul_z(pg, svcvt_f32_z(pg, svsub_z(pg, svget4(widened, 3), offset)), scale));
-}
-
-svfloat32x4_t load_quantized(const uint8_t *ptr, svbool_t pg, const svint32_t &offset, const svfloat32_t &scale)
-{
- auto x = svld1(pg, ptr);
-
- //vprint(x);
-
- const auto widened = svcreate4(
- svmovlb(svmovlb(x)),
- svmovlt(svmovlb(x)),
- svmovlb(svmovlt(x)),
- svmovlt(svmovlt(x)));
-
- pg = svptrue_b8();
-
- return svcreate4(
- svmul_z(pg, svcvt_f32_z(pg, svsub_z(pg, svreinterpret_s32(svget4(widened, 0)), offset)), scale),
- svmul_z(pg, svcvt_f32_z(pg, svsub_z(pg, svreinterpret_s32(svget4(widened, 1)), offset)), scale),
- svmul_z(pg, svcvt_f32_z(pg, svsub_z(pg, svreinterpret_s32(svget4(widened, 2)), offset)), scale),
- svmul_z(pg, svcvt_f32_z(pg, svsub_z(pg, svreinterpret_s32(svget4(widened, 3)), offset)), scale));
-}
-
-void store_quantized(uint8_t *ptr, svbool_t pg, svfloat32x4_t data, const svint32_t &offset, const svfloat32_t &inv_scale)
-{
- const auto quantized = svcreate4(
- svadd_z(pg, svcvt_s32_z(pg, svrinta_z(pg, svmul_z(pg, svget4(data, 0), inv_scale))), offset),
- svadd_z(pg, svcvt_s32_z(pg, svrinta_z(pg, svmul_z(pg, svget4(data, 1), inv_scale))), offset),
- svadd_z(pg, svcvt_s32_z(pg, svrinta_z(pg, svmul_z(pg, svget4(data, 2), inv_scale))), offset),
- svadd_z(pg, svcvt_s32_z(pg, svrinta_z(pg, svmul_z(pg, svget4(data, 3), inv_scale))), offset));
-
- const auto narrowed_bottom = svqxtunt(svqxtunb(svget4(quantized, 0)), svget4(quantized, 1));
- const auto narrowed_top = svqxtunt(svqxtunb(svget4(quantized, 2)), svget4(quantized, 3));
- const auto narrowed = svqxtnt(svqxtnb(narrowed_bottom), narrowed_top);
- svst1(pg, ptr, narrowed);
-}
-
-void store_quantized(int8_t *ptr, svbool_t pg, svfloat32x4_t data, const svint32_t &offset, const svfloat32_t &inv_scale)
-{
- const auto quantized = svcreate4(
- svadd_z(pg, svcvt_s32_z(pg, svrinta_z(pg, svmul_z(pg, svget4(data, 0), inv_scale))), offset),
- svadd_z(pg, svcvt_s32_z(pg, svrinta_z(pg, svmul_z(pg, svget4(data, 1), inv_scale))), offset),
- svadd_z(pg, svcvt_s32_z(pg, svrinta_z(pg, svmul_z(pg, svget4(data, 2), inv_scale))), offset),
- svadd_z(pg, svcvt_s32_z(pg, svrinta_z(pg, svmul_z(pg, svget4(data, 3), inv_scale))), offset));
-
- const auto narrowed_bottom = svqxtnt(svqxtnb(svget4(quantized, 0)), svget4(quantized, 1));
- const auto narrowed_top = svqxtnt(svqxtnb(svget4(quantized, 2)), svget4(quantized, 3));
- const auto narrowed = svqxtnt(svqxtnb(narrowed_bottom), narrowed_top);
-
- svst1(pg, ptr, narrowed);
-}
-
-template <typename InputScalarType, typename OutputScalarType>
-inline void arithmetic_op_quantized_loop(svbool_t pg, const QuantizedLoopArguments<InputScalarType, OutputScalarType, ArithmeticOperation> &args)
-{
- const auto in1 = load_quantized(args.input1_ptr, pg, args.in1_offset, args.in1_scale);
- const auto in2 = load_quantized(args.input2_ptr, pg, args.in2_offset, args.in2_scale);
-
- const auto result = svcreate4(
- elementwise_arithmetic_op<svfloat32_t>(pg, svget4(in1, 0), svget4(in2, 0), args.op),
- elementwise_arithmetic_op<svfloat32_t>(pg, svget4(in1, 1), svget4(in2, 1), args.op),
- elementwise_arithmetic_op<svfloat32_t>(pg, svget4(in1, 2), svget4(in2, 2), args.op),
- elementwise_arithmetic_op<svfloat32_t>(pg, svget4(in1, 3), svget4(in2, 3), args.op));
-
- store_quantized(args.output_ptr, pg, result, args.out_offset, args.out_scale);
-}
-
-template <typename InputScalarType, typename OutputScalarType>
-inline void arithmetic_op_broadcast_quantized_loop(svbool_t pg, const BroadcastQuantizedLoopArguments<InputScalarType, OutputScalarType, ArithmeticOperation> &args)
-{
- const auto in1 = load_quantized(args.input1_ptr, pg, args.in1_offset, args.in1_scale);
- const auto in2 = svcreate4(
- svdup_n(args.broadcast_value), svdup_n(args.broadcast_value), svdup_n(args.broadcast_value), svdup_n(args.broadcast_value));
-
- const auto &af = args.reorder ? in2 : in1;
- const auto &bf = args.reorder ? in1 : in2;
-
- const auto result = svcreate4(
- elementwise_arithmetic_op<svfloat32_t>(pg, svget4(af, 0), svget4(bf, 0), args.op),
- elementwise_arithmetic_op<svfloat32_t>(pg, svget4(af, 1), svget4(bf, 1), args.op),
- elementwise_arithmetic_op<svfloat32_t>(pg, svget4(af, 2), svget4(bf, 2), args.op),
- elementwise_arithmetic_op<svfloat32_t>(pg, svget4(af, 3), svget4(bf, 3), args.op));
-
- store_quantized(args.output_ptr, pg, result, args.out_offset, args.out_scale);
-}
-
-template <typename InputScalarType, typename OutputScalarType>
-inline void comparison_op_quantized_loop(svbool_t pg, const QuantizedLoopArguments<InputScalarType, OutputScalarType, ComparisonOperation> &args)
-{
- const auto in1 = load_quantized(args.input1_ptr, pg, args.in1_offset, args.in1_scale);
- const auto in2 = load_quantized(args.input2_ptr, pg, args.in2_offset, args.in2_scale);
-
- using OutputVectorType = typename wrapper::traits::sve_vector<OutputScalarType>::type;
-
- const auto result = svcreate4(
- elementwise_comparison_op<svfloat32_t, OutputVectorType>(pg, svget4(in1, 0), svget4(in2, 0), args.op),
- elementwise_comparison_op<svfloat32_t, OutputVectorType>(pg, svget4(in1, 1), svget4(in2, 1), args.op),
- elementwise_comparison_op<svfloat32_t, OutputVectorType>(pg, svget4(in1, 2), svget4(in2, 2), args.op),
- elementwise_comparison_op<svfloat32_t, OutputVectorType>(pg, svget4(in1, 3), svget4(in2, 3), args.op));
-
- const auto zipped_bottom = svzip1(svget4(result, 0), svget4(result, 1));
- const auto zipped_top = svzip1(svget4(result, 2), svget4(result, 3));
- const auto zipped = svzip1(zipped_bottom, zipped_top);
- svst1(pg, args.output_ptr, zipped);
-}
-
-template <typename InputScalarType, typename OutputScalarType>
-inline void comparison_op_broadcast_quantized_loop(svbool_t pg, const BroadcastQuantizedLoopArguments<InputScalarType, OutputScalarType, ComparisonOperation> &args)
-{
- const auto in1 = load_quantized(args.input1_ptr, pg, args.in1_offset, args.in1_scale);
- const auto in2 = svcreate4(
- svdup_n(args.broadcast_value), svdup_n(args.broadcast_value), svdup_n(args.broadcast_value), svdup_n(args.broadcast_value));
-
- const auto &af = args.reorder ? in2 : in1;
- const auto &bf = args.reorder ? in1 : in2;
-
- using OutputVectorType = typename wrapper::traits::sve_vector<OutputScalarType>::type;
-
- const auto result = svcreate4(
- elementwise_comparison_op<svfloat32_t, OutputVectorType>(pg, svget4(af, 0), svget4(bf, 0), args.op),
- elementwise_comparison_op<svfloat32_t, OutputVectorType>(pg, svget4(af, 1), svget4(bf, 1), args.op),
- elementwise_comparison_op<svfloat32_t, OutputVectorType>(pg, svget4(af, 2), svget4(bf, 2), args.op),
- elementwise_comparison_op<svfloat32_t, OutputVectorType>(pg, svget4(af, 3), svget4(bf, 3), args.op));
-
- const auto zipped_bottom = svzip1(svget4(result, 0), svget4(result, 1));
- const auto zipped_top = svzip1(svget4(result, 2), svget4(result, 3));
- const auto zipped = svzip1(zipped_bottom, zipped_top);
- svst1(pg, args.output_ptr, zipped);
-}
-
-template <typename InputScalarType, typename OutputScalarType, typename OperatorType>
-using LoopQuantizedFuncType = void (*)(svbool_t, const QuantizedLoopArguments<InputScalarType, OutputScalarType, OperatorType> &);
-
-template <typename InputScalarType, typename OutputScalarType, typename OperatorType>
-using BroadcastQuantizedLoopFuncType = void (*)(svbool_t, const BroadcastQuantizedLoopArguments<InputScalarType, OutputScalarType, OperatorType> &);
-
-template <typename InputVectorType, typename OutputVectorType, typename OperatorType,
- typename InputScalarType = typename wrapper::sve_scalar<InputVectorType>::type,
- typename OutputScalarType = typename wrapper::sve_scalar<OutputVectorType>::type>
-void elementwise_quantized_op(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window,
- OperatorType op,
- LoopQuantizedFuncType<InputScalarType, OutputScalarType, OperatorType> func,
- BroadcastQuantizedLoopFuncType<InputScalarType, OutputScalarType, OperatorType> broadcast_func)
-{
- const auto all_true_pg = wrapper::svptrue<InputScalarType>();
-
- // 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 output_voffset = svdup_n(out->info()->quantization_info().uniform().offset);
- const auto output_vscale = svdup_n(1.f / out->info()->quantization_info().uniform().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 auto non_broadcast_qinfo = is_broadcast_input_2 ? in1->info()->quantization_info() : in2->info()->quantization_info();
- const auto broadcast_qinfo = is_broadcast_input_2 ? in2->info()->quantization_info() : in1->info()->quantization_info();
-
- const auto non_broadcast_voffset = svdup_n(non_broadcast_qinfo.uniform().offset);
- const auto non_broadcast_vscale = svdup_n(non_broadcast_qinfo.uniform().scale);
-
- // 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 &)
- {
- auto output_ptr = reinterpret_cast<OutputScalarType *>(output.ptr());
- const auto non_broadcast_input_ptr = reinterpret_cast<const InputScalarType *>(non_broadcast_input.ptr());
- const InputScalarType broadcast_value = *reinterpret_cast<const InputScalarType *>(broadcast_input.ptr());
-
- int x = window_start_x;
-
- svbool_t pg = wrapper::svwhilelt<InputScalarType>(x, window_end_x);
- do
- {
- const auto args = BroadcastQuantizedLoopArguments<InputScalarType, OutputScalarType, OperatorType>
- {
- op,
- non_broadcast_input_ptr + x,
- Qasymm8QuantizationHelper<InputScalarType>::dequantize(broadcast_value, broadcast_qinfo),
- output_ptr + x,
- !is_broadcast_input_2,
- non_broadcast_voffset, output_voffset,
- non_broadcast_vscale, output_vscale
- };
- broadcast_func(pg, args);
- x += wrapper::svcnt<InputScalarType>();
- pg = wrapper::svwhilelt<InputScalarType>(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 in1_voffset = svdup_n(in1->info()->quantization_info().uniform().offset);
- const auto in1_vscale = svdup_n(in1->info()->quantization_info().uniform().scale);
-
- const auto in2_voffset = svdup_n(in2->info()->quantization_info().uniform().offset);
- const auto in2_vscale = svdup_n(in2->info()->quantization_info().uniform().scale);
-
- execute_window_loop(win, [&](const Coordinates &)
- {
- auto output_ptr = reinterpret_cast<OutputScalarType *>(output.ptr());
- const auto input1_ptr = reinterpret_cast<const InputScalarType *>(input1.ptr());
- const auto input2_ptr = reinterpret_cast<const InputScalarType *>(input2.ptr());
-
- int x = window_start_x;
-
- svbool_t pg = wrapper::svwhilelt<InputScalarType>(x, window_end_x);
- do
- {
- const auto args = QuantizedLoopArguments<InputScalarType, OutputScalarType, OperatorType>
- {
- op,
- input1_ptr + x,
- input2_ptr + x,
- output_ptr + x,
- in1_voffset, in2_voffset, output_voffset,
- in1_vscale, in2_vscale, output_vscale
- };
- func(pg, args);
- x += wrapper::svcnt<InputScalarType>();
- pg = wrapper::svwhilelt<InputScalarType>(x, window_end_x);
- }
- while(svptest_any(all_true_pg, pg));
- },
- input1, input2, output);
- }
-}
-
-template <ArithmeticOperation op, typename ScalarType>
-void elementwise_arithmetic_quantized_op(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
-{
- using VectorType = typename wrapper::traits::sve_vector<ScalarType>::type;
- elementwise_quantized_op<VectorType, VectorType, ArithmeticOperation>(in1, in2, out, window, op,
- &arithmetic_op_quantized_loop<ScalarType, ScalarType>,
- &arithmetic_op_broadcast_quantized_loop<ScalarType, ScalarType>);
-}
-
-template <ComparisonOperation op, typename InputScalarType, typename OutputScalarType = uint8_t>
-void elementwise_comparison_quantized_op(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
-{
- static_assert(sizeof(InputScalarType) >= sizeof(OutputScalarType), "input data type's width should be equal to or greater than output data type's width");
- using InputVectorType = typename wrapper::traits::sve_vector<InputScalarType>::type;
- using OutputVectorType = typename wrapper::traits::sve_vector<OutputScalarType>::type;
- elementwise_quantized_op<InputVectorType, OutputVectorType, ComparisonOperation>(in1, in2, out, window, op,
- &comparison_op_quantized_loop<InputScalarType, OutputScalarType>,
- &comparison_op_broadcast_quantized_loop<InputScalarType, OutputScalarType>);
-}
-} // namespace cpu
-} // namespace arm_compute
-
-#endif /* defined(__ARM_FEATURE_SVE2) */
-#endif /* SRC_CORE_SVE_KERNELS_ELEMENTWISE_QUANTIZED_LIST_H */ \ No newline at end of file