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/*
* Copyright (c) 2020-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef SRC_CORE_NEON_KERNELS_ADD_LIST_H
#define SRC_CORE_NEON_KERNELS_ADD_LIST_H
#include "arm_compute/core/Types.h"
#include "arm_compute/core/utils/misc/Traits.h"
#include "src/core/NEON/wrapper/wrapper.h"
namespace arm_compute
{
namespace cpu
{
#define DECLARE_ADD_KERNEL(func_name) \
void func_name(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window)
DECLARE_ADD_KERNEL(add_qasymm8_neon);
DECLARE_ADD_KERNEL(add_qasymm8_signed_neon);
DECLARE_ADD_KERNEL(add_qsymm16_neon);
DECLARE_ADD_KERNEL(add_s16_u8_s16_neon);
DECLARE_ADD_KERNEL(add_u8_s16_s16_neon);
DECLARE_ADD_KERNEL(add_u8_u8_s16_neon);
#undef DECLARE_ADD_KERNEL
template <typename ScalarType>
void add_same_neon(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window)
{
/** Neon vector tag type. */
using ExactTagType = typename wrapper::traits::neon_bitvector_tag_t<ScalarType, wrapper::traits::BitWidth::W128>;
// Create input windows
Window input1_win = window.broadcast_if_dimension_le_one(src0->info()->tensor_shape());
Window input2_win = window.broadcast_if_dimension_le_one(src1->info()->tensor_shape());
// Clear X Dimension on execution window as we handle manually
Window win = window;
win.set(Window::DimX, Window::Dimension(0, 1, 1));
constexpr int window_step_x = 16 / sizeof(ScalarType);
const auto window_start_x = static_cast<int>(window.x().start());
const auto window_end_x = static_cast<int>(window.x().end());
const bool is_broadcast_across_x = src0->info()->tensor_shape().x() != src1->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 ? src1 : src0;
const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? src1 : src0;
// 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(dst, win);
execute_window_loop(win, [&](const Coordinates &)
{
const auto non_broadcast_input_ptr = reinterpret_cast<const ScalarType *>(non_broadcast_input.ptr());
const auto output_ptr = reinterpret_cast<ScalarType *>(output.ptr());
const ScalarType broadcast_value = *reinterpret_cast<const ScalarType *>(broadcast_input.ptr());
const auto broadcast_value_vec = wrapper::vdup_n(broadcast_value, ExactTagType{});
// Compute S elements per iteration
int x = window_start_x;
for(; x <= (window_end_x - window_step_x); x += window_step_x)
{
const auto non_broadcast_v = wrapper::vloadq(non_broadcast_input_ptr + x);
const auto res = (policy == ConvertPolicy::SATURATE) ? wrapper::vqadd(broadcast_value_vec, non_broadcast_v) : wrapper::vadd(broadcast_value_vec, non_broadcast_v);
wrapper::vstore(output_ptr + x, res);
}
// Compute left-over elements
for(; x < window_end_x; ++x)
{
const auto non_broadcast_v = *(non_broadcast_input_ptr + x);
*(output_ptr + x) = (policy == ConvertPolicy::SATURATE) ? wrapper::add_sat(broadcast_value, non_broadcast_v) : broadcast_value + non_broadcast_v;
}
},
broadcast_input, non_broadcast_input, output);
}
else
{
// Clear X Dimension on execution window as we handle manually
input1_win.set(Window::DimX, Window::Dimension(0, 1, 1));
input2_win.set(Window::DimX, Window::Dimension(0, 1, 1));
Iterator input1(src0, input1_win);
Iterator input2(src1, input2_win);
Iterator output(dst, win);
execute_window_loop(win, [&](const Coordinates &)
{
const auto input1_ptr = reinterpret_cast<const ScalarType *>(input1.ptr());
const auto input2_ptr = reinterpret_cast<const ScalarType *>(input2.ptr());
const auto output_ptr = reinterpret_cast<ScalarType *>(output.ptr());
// Compute S elements per iteration
int x = window_start_x;
for(; x <= (window_end_x - window_step_x); x += window_step_x)
{
const auto val1 = wrapper::vloadq(input1_ptr + x);
const auto val2 = wrapper::vloadq(input2_ptr + x);
const auto res = (policy == ConvertPolicy::SATURATE) ? wrapper::vqadd(val1, val2) : wrapper::vadd(val1, val2);
wrapper::vstore(output_ptr + x, res);
}
// Compute left-over elements
for(; x < window_end_x; ++x)
{
const auto val1 = *(input1_ptr + x);
const auto val2 = *(input2_ptr + x);
*(output_ptr + x) = (policy == ConvertPolicy::SATURATE) ? wrapper::add_sat(val1, val2) : val1 + val2;
}
},
input1, input2, output);
}
}
} // namespace cpu
} // namespace arm_compute
#endif // SRC_CORE_NEON_KERNELS_ADD_LIST_H
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