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/*
* Copyright (c) 2017-2023 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_L2NORMLAYER_LIST_H
#define SRC_CORE_NEON_KERNELS_L2NORMLAYER_LIST_H
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/TensorInfo.h"
#include "src/core/NEON/wrapper/wrapper.h"
#include "src/core/common/Registrars.h"
#include <cstddef>
namespace arm_compute
{
namespace cpu
{
template <typename T, int S>
void l2_normalize_x(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window)
{
using ExactTagType = typename wrapper::traits::neon_vector<T, S>::tag_type;
const int window_step_x = 16 / data_size_from_type(in->info()->data_type());
const auto window_start_x = static_cast<int>(window.x().start());
const auto window_end_x = static_cast<int>(window.x().end());
Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));
Iterator input_it(in, win_collapsed);
Iterator sum_it(sum, win_collapsed);
Iterator output_it(out, win_collapsed);
execute_window_loop(win_collapsed, [&](const Coordinates &)
{
const auto in_ptr = reinterpret_cast<const T *>(input_it.ptr());
const auto out_ptr = reinterpret_cast<T *>(output_it.ptr());
const T sum_value = *reinterpret_cast<const T *>(sum_it.ptr());
const T norm_value = static_cast<T>(1.f) / std::sqrt(std::max(sum_value, static_cast<T>(epsilon)));
const auto vec_norm_value = wrapper::vdup_n(norm_value, ExactTagType{});
// Compute elements over vector steps
int x = window_start_x;
for(; x <= (window_end_x - window_step_x); x += window_step_x)
{
wrapper::vstore(out_ptr + x, wrapper::vmul(wrapper::vloadq(in_ptr + x), vec_norm_value));
}
// Compute left-over elements
for(; x < window_end_x; ++x)
{
out_ptr[x] = in_ptr[x] * norm_value;
}
},
input_it, sum_it, output_it);
}
template <typename T, int S>
void l2_normalize_yz(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window, size_t axis)
{
using ExactTagType = typename wrapper::traits::neon_vector<T, S>::tag_type;
const int window_step_x = 16 / data_size_from_type(in->info()->data_type());
const auto window_start_x = static_cast<int>(window.x().start());
const auto window_end_x = static_cast<int>(window.x().end());
Window win = window;
win.set(Window::DimX, Window::Dimension(0, 1, 1));
Window window_sum(win);
window_sum.set(axis, Window::Dimension(0, 0, 0));
Iterator input_it(in, win);
Iterator sum_it(sum, window_sum);
Iterator output_it(out, win);
const auto vec_eps = wrapper::vdup_n(static_cast<T>(epsilon), ExactTagType{});
execute_window_loop(win, [&](const Coordinates &)
{
const auto in_ptr = reinterpret_cast<const T *>(input_it.ptr());
const auto sum_ptr = reinterpret_cast<const T *>(sum_it.ptr());
const auto out_ptr = reinterpret_cast<T *>(output_it.ptr());
// Compute elements over vector steps
int x = window_start_x;
for(; x <= (window_end_x - window_step_x); x += window_step_x)
{
const auto vec_norm_value = wrapper::vinvsqrt(wrapper::vmax(wrapper::vloadq(sum_ptr + x), vec_eps));
wrapper::vstore(out_ptr + x, wrapper::vmul(wrapper::vloadq(in_ptr + x), vec_norm_value));
}
// Compute left-over elements
for(; x < window_end_x; ++x)
{
const T norm_value = static_cast<T>(1.f) / std::sqrt(std::max(sum_ptr[x], static_cast<T>(epsilon)));
out_ptr[x] = in_ptr[x] * norm_value;
}
},
input_it, sum_it, output_it);
}
} // namespace cpu
} // namespace arm_compute
#endif //SRC_CORE_NEON_KERNELS_L2NORMLAYER_LIST_H
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