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Diffstat (limited to 'src/core/cpu/kernels/elementwise/sve/elementwise_list.h')
| -rw-r--r-- | src/core/cpu/kernels/elementwise/sve/elementwise_list.h | 366 |
1 files changed, 0 insertions, 366 deletions
diff --git a/src/core/cpu/kernels/elementwise/sve/elementwise_list.h b/src/core/cpu/kernels/elementwise/sve/elementwise_list.h deleted file mode 100644 index 83c3355de4..0000000000 --- a/src/core/cpu/kernels/elementwise/sve/elementwise_list.h +++ /dev/null @@ -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_LIST_H -#define SRC_CORE_SVE_KERNELS_ELEMENTWISE_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 "src/core/NEON/wrapper/svtraits.h" -#include <arm_sve.h> - -namespace arm_compute -{ -namespace cpu -{ -namespace sve -{ -using namespace arm_compute::wrapper; - -template <typename VectorType> -inline VectorType elementwise_pow(svbool_t &pg, const VectorType &a, const VectorType &b) -{ - return svpow_z(pg, a, b); -} - -template <> -inline svint32_t elementwise_pow<svint32_t>(svbool_t &pg, const svint32_t &a, const svint32_t &b) -{ - return svcvt_s32_z(pg, svpow_z(pg, svcvt_f32_z(pg, a), svcvt_f32_z(pg, b))); -} - -template <typename VectorType> -inline VectorType elementwise_div(svbool_t &pg, const VectorType &a, const VectorType &b) -{ - return svdiv_z(pg, a, b); -} - -template <> -inline svint32_t elementwise_div<svint32_t>(svbool_t &pg, const svint32_t &a, const svint32_t &b) -{ - return svcvt_s32_z(pg, svdiv_z(pg, svcvt_f32_z(pg, a), svcvt_f32_z(pg, b))); -} - -template <typename VectorType> -inline VectorType elementwise_arithmetic_op(svbool_t &pg, const VectorType &a, const VectorType &b, ArithmeticOperation op) -{ - using ScalarType = typename sve_scalar<VectorType>::type; - VectorType res{}; - - switch(op) - { - case ArithmeticOperation::MAX: - res = svmax_z(pg, a, b); - break; - case ArithmeticOperation::MIN: - res = svmin_z(pg, a, b); - break; - case ArithmeticOperation::SQUARED_DIFF: - { - const auto tmp = svsub_z(pg, a, b); - res = svmul_z(pg, tmp, tmp); - break; - } - case ArithmeticOperation::PRELU: - { - const auto zero = svdup_n(ScalarType(0)); - const auto tmp = svmul_z(pg, a, b); - const auto gt = svcmpgt(pg, a, zero); - res = svsel(gt, a, tmp); - break; - } - case ArithmeticOperation::DIV: - { - res = elementwise_div(pg, a, b); - break; - } - case ArithmeticOperation::POWER: - { - res = elementwise_pow(pg, a, b); - break; - } - default: - ARM_COMPUTE_ERROR("NOT_SUPPORTED!"); - } - - return res; -} - -template <uint32_t bytewidth> -inline svbool_t narrow_to_byte_predicate(svbool_t pg) -{ - const auto all_false = svpfalse(); - - switch(bytewidth) - { - case 8: - pg = svuzp1_b32(pg, all_false); - /* fall through */ - case 4: - pg = svuzp1_b16(pg, all_false); - /* fall through */ - case 2: - pg = svuzp1_b8(pg, all_false); - /* fall through */ - default: - break; - } - return pg; -} - -template <typename InputVectorType, typename OutputVectorType> -inline OutputVectorType elementwise_comparison_op(svbool_t &pg, const InputVectorType &a, const InputVectorType &b, ComparisonOperation op) -{ - svbool_t selection_vector{}; - - switch(op) - { - case ComparisonOperation::Equal: - selection_vector = svcmpeq(pg, a, b); - break; - case ComparisonOperation::NotEqual: - selection_vector = svcmpne(pg, a, b); - break; - case ComparisonOperation::Greater: - selection_vector = svcmpgt(pg, a, b); - break; - case ComparisonOperation::GreaterEqual: - selection_vector = svcmpge(pg, a, b); - break; - case ComparisonOperation::Less: - selection_vector = svcmplt(pg, a, b); - break; - case ComparisonOperation::LessEqual: - selection_vector = svcmple(pg, a, b); - break; - default: - ARM_COMPUTE_ERROR("NOT_SUPPORTED!"); - } - - using InputScalarType = typename sve_scalar<InputVectorType>::type; - selection_vector = narrow_to_byte_predicate<sizeof(InputScalarType)>(selection_vector); - - using OutputScalarType = typename sve_scalar<OutputVectorType>::type; - const auto false_vector = svdup_n(static_cast<OutputScalarType>((uint32_t)0)); - const auto true_vector = svdup_n(static_cast<OutputScalarType>(~(uint32_t)0)); - auto ret = svsel(selection_vector, true_vector, false_vector); - - return ret; -} - -template <typename InputScalarType, typename OutputScalarType, typename OperatorType> -struct LoopArguments -{ - OperatorType op; - const InputScalarType *input1_ptr; - const InputScalarType *input2_ptr; - OutputScalarType *output_ptr; -}; - -template <typename InputScalarType, typename OutputScalarType, typename OperatorType> -struct BroadcastLoopArguments -{ - OperatorType op; - const InputScalarType *input1_ptr; - InputScalarType broadcast_value; - OutputScalarType *output_ptr; - bool reorder; -}; - -template <typename InputScalarType, typename OutputScalarType> -inline void arithmetic_op_loop(svbool_t pg, const LoopArguments<InputScalarType, OutputScalarType, ArithmeticOperation> &args) -{ - const auto in1 = svld1(pg, args.input1_ptr); - const auto in2 = svld1(pg, args.input2_ptr); - const auto res = elementwise_arithmetic_op<typename sve_vector<InputScalarType>::type>(pg, in1, in2, args.op); - svst1(pg, args.output_ptr, res); -} - -template <typename InputScalarType, typename OutputScalarType> -inline void arithmetic_op_broadcast_loop(svbool_t pg, const BroadcastLoopArguments<InputScalarType, OutputScalarType, ArithmeticOperation> &args) -{ - const auto non_broadcast_vector = svld1(pg, args.input1_ptr); - const auto broadcast_vector = svdup_n(args.broadcast_value); - const auto in1 = args.reorder ? broadcast_vector : non_broadcast_vector; - const auto in2 = args.reorder ? non_broadcast_vector : broadcast_vector; - const auto res = elementwise_arithmetic_op<typename sve_vector<InputScalarType>::type>(pg, in1, in2, args.op); - svst1(pg, args.output_ptr, res); -} - -template <typename InputScalarType, typename OutputScalarType> -inline void comparison_op_loop(svbool_t pg, const LoopArguments<InputScalarType, OutputScalarType, ComparisonOperation> &args) -{ - const auto in1 = svld1(pg, args.input1_ptr); - const auto in2 = svld1(pg, args.input2_ptr); - const auto res = elementwise_comparison_op<typename sve_vector<InputScalarType>::type, typename sve_vector<OutputScalarType>::type>(pg, in1, in2, args.op); - const svbool_t output_pg = narrow_to_byte_predicate<sizeof(InputScalarType)>(pg); - svst1(output_pg, args.output_ptr, res); -} - -template <typename InputScalarType, typename OutputScalarType> -inline void comparison_op_broadcast_loop(svbool_t pg, const BroadcastLoopArguments<InputScalarType, OutputScalarType, ComparisonOperation> &args) -{ - const auto non_broadcast_vector = svld1(pg, args.input1_ptr); - const auto broadcast_vector = svdup_n(args.broadcast_value); - const auto in1 = args.reorder ? broadcast_vector : non_broadcast_vector; - const auto in2 = args.reorder ? non_broadcast_vector : broadcast_vector; - const auto res = elementwise_comparison_op<typename sve_vector<InputScalarType>::type, typename sve_vector<OutputScalarType>::type>(pg, in1, in2, args.op); - const svbool_t output_pg = narrow_to_byte_predicate<sizeof(InputScalarType)>(pg); - svst1(output_pg, args.output_ptr, res); -} - -template <typename InputScalarType, typename OutputScalarType, typename OperatorType> -using LoopFuncType = void (*)(svbool_t, const LoopArguments<InputScalarType, OutputScalarType, OperatorType> &); - -template <typename InputScalarType, typename OutputScalarType, typename OperatorType> -using BroadcastLoopFuncType = void (*)(svbool_t, const BroadcastLoopArguments<InputScalarType, OutputScalarType, OperatorType> &); - -template <typename InputVectorType, typename OutputVectorType, typename OperatorType, - typename InputScalarType = typename sve_scalar<InputVectorType>::type, - typename OutputScalarType = typename sve_scalar<OutputVectorType>::type> -void elementwise_op(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, - OperatorType op, - LoopFuncType<InputScalarType, OutputScalarType, OperatorType> func, - BroadcastLoopFuncType<InputScalarType, OutputScalarType, OperatorType> broadcast_func) -{ - const auto all_true_pg = 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(); - - 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 &) - { - 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 = svwhilelt<InputScalarType>(x, window_end_x); - do - { - broadcast_func(pg, - { - op, - non_broadcast_input_ptr + x, - broadcast_value, - output_ptr + x, - !is_broadcast_input_2 - }); - x += svcnt<InputScalarType>(); - pg = 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); - - 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 = svwhilelt<InputScalarType>(x, window_end_x); - do - { - func(pg, - { - op, - input1_ptr + x, - input2_ptr + x, - output_ptr + x - }); - x += svcnt<InputScalarType>(); - pg = svwhilelt<InputScalarType>(x, window_end_x); - } - while(svptest_any(all_true_pg, pg)); - }, - input1, input2, output); - } -} - -template <ArithmeticOperation op, typename ScalarType> -void elementwise_arithmetic_op(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) -{ - using VectorType = typename sve_vector<ScalarType>::type; - - elementwise_op<VectorType, VectorType, ArithmeticOperation>(in1, in2, out, window, op, - &arithmetic_op_loop<ScalarType, ScalarType>, - &arithmetic_op_broadcast_loop<ScalarType, ScalarType>); -} - -template <ComparisonOperation op, typename InputScalarType, typename OutputScalarType = uint8_t> -void elementwise_comparison_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 sve_vector<InputScalarType>::type; - using OutputVectorType = typename sve_vector<OutputScalarType>::type; - - elementwise_op<InputVectorType, OutputVectorType, ComparisonOperation>(in1, in2, out, window, op, - &comparison_op_loop<InputScalarType, OutputScalarType>, - &comparison_op_broadcast_loop<InputScalarType, OutputScalarType>); -} - -} // namespace sve -} // namespace cpu -} // namespace arm_compute -#endif // defined(__ARM_FEATURE_SVE) -#endif /* SRC_CORE_SVE_KERNELS_ELEMENTWISE_LIST_H */ |