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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/NEDepthConcatenateKernel.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/IAccessWindow.h"
#include "arm_compute/core/ITensor.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>
using namespace arm_compute;
NEDepthConcatenateKernel::NEDepthConcatenateKernel()
: _input(nullptr), _output(nullptr), _top_bottom(0), _left_right(0), _depth_offset(0)
{
}
BorderSize NEDepthConcatenateKernel::border_size() const
{
return BorderSize(_top_bottom, _left_right);
}
void NEDepthConcatenateKernel::configure(const ITensor *input, unsigned int depth_offset, ITensor *output)
{
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32);
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F32);
ARM_COMPUTE_ERROR_ON(input->info()->dimension(2) + depth_offset > output->info()->dimension(2));
ARM_COMPUTE_ERROR_ON(input->info()->dimension(0) > output->info()->dimension(0));
ARM_COMPUTE_ERROR_ON(input->info()->dimension(1) > output->info()->dimension(1));
ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(3, input, output);
// The gaps between the two lowest dimensions of input and output need to be divisible by 2
// Otherwise it is not clear how the padding should be added onto the input tensor
ARM_COMPUTE_ERROR_ON((output->info()->dimension(0) - input->info()->dimension(0)) % 2);
ARM_COMPUTE_ERROR_ON((output->info()->dimension(1) - input->info()->dimension(1)) % 2);
_input = input;
_output = output;
_depth_offset = depth_offset;
_left_right = (output->info()->dimension(0) - input->info()->dimension(0)) / 2;
_top_bottom = (output->info()->dimension(1) - input->info()->dimension(1)) / 2;
const unsigned int num_elems_processed_per_iteration = 4;
const unsigned int num_elems_read_per_iteration = 4;
const unsigned int num_rows_read_per_iteration = 1;
// The window needs to be based on input as we copy all the depths of input
Window win = calculate_max_enlarged_window(*input->info(), Steps(num_elems_processed_per_iteration), border_size());
AccessWindowRectangle input_access(input->info(), -_left_right, -_top_bottom, num_elems_read_per_iteration, num_rows_read_per_iteration);
AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration);
update_window_and_padding(win, input_access, output_access);
output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), output->info()->tensor_shape()));
INEKernel::configure(win);
}
void NEDepthConcatenateKernel::run(const Window &window)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
// Offset output
const unsigned int offset_to_first_elements_in_bytes = _output->info()->offset_first_element_in_bytes() + _left_right * _output->info()->strides_in_bytes()[0] + _top_bottom *
_output->info()->strides_in_bytes()[1] + _depth_offset * _output->info()->strides_in_bytes()[2];
uint8_t *output_ptr = _output->buffer() + offset_to_first_elements_in_bytes;
Iterator input(_input, window);
Iterator output(_output, window);
execute_window_loop(window, [&](const Coordinates & id)
{
const auto in_ptr = reinterpret_cast<const float *>(input.ptr());
const auto out_ptr = reinterpret_cast<float *>(output_ptr + output.offset());
vst1q_f32(out_ptr, vld1q_f32(in_ptr));
},
input, output);
}
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