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/*
* Copyright (c) 2017 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.
*/
#include "arm_compute/core/NEON/kernels/NEL2NormalizeKernel.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/ITensor.h"
#include "arm_compute/core/NEON/NEMath.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/Window.h"
#include <arm_neon.h>
#include <cmath>
using namespace arm_compute;
namespace
{
void l2_normalize_X(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window)
{
Window window_sum(window);
window_sum.set(Window::DimX, Window::Dimension(0, 0, 0));
Window in_slice = window.first_slice_window_1D();
Window sum_slice = window_sum.first_slice_window_1D();
do
{
Iterator input_it(in, in_slice);
Iterator sum_it(sum, sum_slice);
Iterator output_it(out, in_slice);
const float sum_value = *reinterpret_cast<const float *>(sum_it.ptr());
const float32x4_t vec_normalize_value = vdupq_n_f32(1.f / std::sqrt(std::max(sum_value, epsilon)));
execute_window_loop(in_slice, [&](const Coordinates & id)
{
const auto in_ptr = reinterpret_cast<const float *>(input_it.ptr());
const auto out_ptr = reinterpret_cast<float *>(output_it.ptr());
vst1q_f32(out_ptr, vmulq_f32(vld1q_f32(in_ptr), vec_normalize_value));
},
input_it, output_it);
}
while(window.slide_window_slice_1D(in_slice) && window.slide_window_slice_1D(sum_slice));
}
} // namespace
NEL2NormalizeKernel::NEL2NormalizeKernel()
: _input(nullptr), _sum(nullptr), _output(nullptr), _axis(0), _epsilon(1e-12)
{
}
void NEL2NormalizeKernel::configure(const ITensor *input, const ITensor *sum, ITensor *output, unsigned int axis, float epsilon)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, sum, output);
ARM_COMPUTE_ERROR_ON_MSG(axis >= TensorShape::num_max_dimensions, "Normalization axis greater than max number of dimensions");
ARM_COMPUTE_ERROR_ON_MSG(axis > 0, "Unsupported normalization axis, Supported axis is 0");
// Output auto initialization if not yet initialized
auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type(), input->info()->fixed_point_position());
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32);
ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, sum);
ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output);
unsigned int num_elems_processed_per_iteration = 16 / data_size_from_type(input->info()->data_type());
unsigned int num_elems_processed_per_iteration_sum = (axis == 0) ? 1 : num_elems_processed_per_iteration;
_input = input;
_sum = sum;
_output = output;
_axis = axis;
_epsilon = epsilon;
// Configure kernel window
Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));
AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
AccessWindowHorizontal sum_access(sum->info(), 0, num_elems_processed_per_iteration_sum);
AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration);
update_window_and_padding(win, input_access, sum_access, output_access);
output_access.set_valid_region(win, input->info()->valid_region());
INEKernel::configure(win);
}
void NEL2NormalizeKernel::run(const Window &window, const ThreadInfo &info)
{
ARM_COMPUTE_UNUSED(info);
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
switch(_axis)
{
case 0:
l2_normalize_X(_input, _sum, _output, _epsilon, window);
break;
default:
ARM_COMPUTE_ERROR("Unsupported normalization axis");
}
}
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