| /* |
| * Copyright (c) 2021-2022 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. |
| */ |
| #if defined(ARM_COMPUTE_ENABLE_SVE) |
| #include "src/cpu/kernels/elementwise_binary/generic/sve/impl.h" |
| #include "src/core/NEON/SVEMath.h" |
| #include <arm_sve.h> |
| |
| namespace arm_compute |
| { |
| namespace cpu |
| { |
| using namespace arm_compute::wrapper; |
| |
| 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> |
| 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> |
| 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> |
| 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> |
| 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 void elementwise_arithmetic_op<ArithmeticOperation::ADD, float32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::SUB, float32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::DIV, float32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::MIN, float32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::MAX, float32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::SQUARED_DIFF, float32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::POWER, float32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::PRELU, float32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| |
| template void elementwise_arithmetic_op<ArithmeticOperation::ADD, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::SUB, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::DIV, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::MIN, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::MAX, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::SQUARED_DIFF, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::POWER, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::PRELU, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| |
| template void elementwise_arithmetic_op<ArithmeticOperation::ADD, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::SUB, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::DIV, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::MIN, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::MAX, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::SQUARED_DIFF, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::POWER, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::PRELU, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| |
| template void elementwise_arithmetic_op<ArithmeticOperation::ADD, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::SUB, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::DIV, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::MIN, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::MAX, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::SQUARED_DIFF, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::POWER, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_arithmetic_op<ArithmeticOperation::PRELU, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| |
| 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>); |
| } |
| |
| template void elementwise_comparison_op<ComparisonOperation::Equal, float32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::NotEqual, float32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::Greater, float32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::GreaterEqual, float32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::Less, float32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::LessEqual, float32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| |
| template void elementwise_comparison_op<ComparisonOperation::Equal, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::NotEqual, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::Greater, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::GreaterEqual, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::Less, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::LessEqual, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| |
| template void elementwise_comparison_op<ComparisonOperation::Equal, uint8_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::NotEqual, uint8_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::Greater, uint8_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::GreaterEqual, uint8_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::Less, uint8_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::LessEqual, uint8_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| |
| template void elementwise_comparison_op<ComparisonOperation::Equal, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::NotEqual, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::Greater, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::GreaterEqual, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::Less, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::LessEqual, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| |
| template void elementwise_comparison_op<ComparisonOperation::Equal, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::NotEqual, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::Greater, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::GreaterEqual, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::Less, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| template void elementwise_comparison_op<ComparisonOperation::LessEqual, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); |
| |
| template <> |
| 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 <> |
| 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 <> |
| svint16_t elementwise_div<svint16_t>(svbool_t &pg, const svint16_t &a, const svint16_t &b) |
| { |
| ARM_COMPUTE_UNUSED(pg, a, b); |
| ARM_COMPUTE_ERROR("Not supported"); |
| } |
| |
| } // namespace cpu |
| } // namespace arm_compute |
| #endif /* defined(ARM_COMPUTE_ENABLE_SVE) */ |
