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/*
* Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
* Copyright (c) 2019 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/runtime/NEON/functions/NESpaceToBatchLayerEx.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/runtime/NEON/NEScheduler.h"
namespace arm_compute
{
NESpaceToBatchLayerEx::NESpaceToBatchLayerEx()
: _space_to_batch_kernel(), _memset_kernel(), _has_padding(false)
{
}
void NESpaceToBatchLayerEx::configure(const ITensor *input, const ITensor *block_shape,
const ITensor *paddings, ITensor *output)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, block_shape, paddings, output);
if (input->info()->tensor_shape().total_size() != output->info()->tensor_shape().total_size())
{
_has_padding = true;
_memset_kernel.configure(
output, PixelValue(0, output->info()->data_type(), output->info()->quantization_info()));
}
_space_to_batch_kernel.configure(input, block_shape, paddings, output);
}
void NESpaceToBatchLayerEx::configure(const ITensor *input, const int block_shape_x,
const int block_shape_y, const Size2D &padding_left,
const Size2D &padding_right, ITensor *output)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
if (input->info()->tensor_shape().total_size() != output->info()->tensor_shape().total_size())
{
_has_padding = true;
_memset_kernel.configure(
output, PixelValue(0, output->info()->data_type(), output->info()->quantization_info()));
}
_space_to_batch_kernel.configure(input, block_shape_x, block_shape_y, padding_left, padding_right,
output);
}
Status NESpaceToBatchLayerEx::validate(const ITensorInfo *input, const ITensorInfo *block_shape,
const ITensorInfo *paddings, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ON_ERROR(
NESpaceToBatchLayerKernel::validate(input, block_shape, paddings, output));
return Status{};
}
Status NESpaceToBatchLayerEx::validate(const ITensorInfo *input, const int block_shape_x,
const int block_shape_y, const Size2D &padding_left,
const Size2D &padding_right, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ON_ERROR(NESpaceToBatchLayerKernel::validate(
input, block_shape_x, block_shape_y, padding_left, padding_right, output));
return Status{};
}
void NESpaceToBatchLayerEx::run()
{
// Zero out output only if we have paddings
if (_has_padding)
{
NEScheduler::get().schedule(&_memset_kernel, Window::DimY);
}
NEScheduler::get().schedule(&_space_to_batch_kernel, Window::DimY);
}
} // namespace arm_compute
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