blob: d1cff6f62d8224ce50a59c9223ba7ed9d4cb15bb [file] [log] [blame]
/*
* Copyright (c) 2016, 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/NEFillInnerBorderKernel.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/ITensor.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/Window.h"
#include <algorithm>
#include <cstddef>
#include <cstdint>
using namespace arm_compute;
namespace arm_compute
{
class Coordinates;
} // namespace arm_compute
NEFillInnerBorderKernel::NEFillInnerBorderKernel()
: _tensor(nullptr), _border_size(0), _constant_border_value(static_cast<float>(0.f))
{
}
void NEFillInnerBorderKernel::configure(ITensor *input, BorderSize border_size, const PixelValue &constant_border_value)
{
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::S16, DataType::S32, DataType::F32);
_tensor = input;
_border_size = border_size;
_constant_border_value = constant_border_value;
Window win;
win.set(Window::DimX, Window::Dimension(0, 1, 1));
win.set(Window::DimY, Window::Dimension(0, 1, 1));
win.use_tensor_dimensions(_tensor->info()->tensor_shape(), Window::DimZ);
INEKernel::configure(win);
}
void NEFillInnerBorderKernel::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);
// If there is no border: early exit
if(_border_size.empty())
{
return;
}
switch(_tensor->info()->data_type())
{
case DataType::U8:
fill_value_single_channel<uint8_t>(window);
break;
case DataType::S16:
fill_value_single_channel<int16_t>(window);
break;
case DataType::S32:
fill_value_single_channel<int32_t>(window);
break;
case DataType::F32:
static_assert(sizeof(float) == 4, "Float must be 32 bit");
fill_value_single_channel<float>(window);
break;
default:
ARM_COMPUTE_ERROR("Not handled");
break;
}
}
template <typename T>
void NEFillInnerBorderKernel::fill_value_single_channel(const Window &window)
{
const size_t stride = _tensor->info()->strides_in_bytes()[1];
const size_t width = _tensor->info()->dimension(0);
const size_t height = _tensor->info()->dimension(1);
T constant_border_value;
_constant_border_value.get(constant_border_value);
// Left and right border
// All X values are set at once
Window vertical(window);
vertical.set(Window::DimY, Window::Dimension(0, height, 1));
Iterator vertical_it(_tensor, vertical);
execute_window_loop(vertical, [&](const Coordinates & id)
{
std::fill_n(reinterpret_cast<T *>(vertical_it.ptr()), _border_size.left, constant_border_value);
std::fill_n(reinterpret_cast<T *>(vertical_it.ptr()) + width - _border_size.right, _border_size.right, constant_border_value);
},
vertical_it);
// Top and bottom border
// All values are set at once
Iterator horizontal_it(_tensor, window);
execute_window_loop(window, [&](const Coordinates & id)
{
for(size_t i = 0; i < _border_size.top; ++i)
{
std::fill_n(reinterpret_cast<T *>(horizontal_it.ptr() + i * stride), width, constant_border_value);
}
for(size_t i = 0; i < _border_size.bottom; ++i)
{
std::fill_n(reinterpret_cast<T *>(horizontal_it.ptr() + (height - i - 1) * stride), width, constant_border_value);
}
},
horizontal_it);
}