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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.
*/
#ifndef __ARM_COMPUTE_TEST_DATASET_NORMALIZATION_LAYER_DATASET_H__
#define __ARM_COMPUTE_TEST_DATASET_NORMALIZATION_LAYER_DATASET_H__
#include "TypePrinter.h"
#include "arm_compute/core/TensorShape.h"
#include "arm_compute/core/Types.h"
#include "dataset/GenericDataset.h"
#include <sstream>
#include <type_traits>
#ifdef BOOST
#include "boost_wrapper.h"
#endif
namespace arm_compute
{
namespace test
{
class NormalizationLayerDataObject
{
public:
operator std::string() const
{
std::stringstream ss;
ss << "NormalizationLayer";
ss << "_I" << shape;
ss << "_F_" << info.type();
ss << "_S_" << info.norm_size();
return ss.str();
}
public:
TensorShape shape;
NormalizationLayerInfo info;
};
template <unsigned int Size>
using NormalizationLayerDataset = GenericDataset<NormalizationLayerDataObject, Size>;
class GoogLeNetNormalizationLayerDataset final : public NormalizationLayerDataset<2>
{
public:
GoogLeNetNormalizationLayerDataset()
: GenericDataset
{
// conv2/norm2
NormalizationLayerDataObject{ TensorShape(56U, 56U, 192U), NormalizationLayerInfo(NormType::CROSS_MAP, 5, 0.0001f, 0.75f) },
// pool1/norm1
NormalizationLayerDataObject{ TensorShape(56U, 56U, 64U), NormalizationLayerInfo(NormType::CROSS_MAP, 5, 0.0001f, 0.75f) }
}
{
}
~GoogLeNetNormalizationLayerDataset() = default;
};
class AlexNetNormalizationLayerDataset final : public NormalizationLayerDataset<2>
{
public:
AlexNetNormalizationLayerDataset()
: GenericDataset
{
NormalizationLayerDataObject{ TensorShape(55U, 55U, 96U), NormalizationLayerInfo(NormType::CROSS_MAP, 5, 0.0001f, 0.75f) },
NormalizationLayerDataObject{ TensorShape(27U, 27U, 256U), NormalizationLayerInfo(NormType::CROSS_MAP, 5, 0.0001f, 0.75f) },
}
{
}
~AlexNetNormalizationLayerDataset() = default;
};
} // namespace test
} // namespace arm_compute
#endif //__ARM_COMPUTE_TEST_DATASET_NORMALIZATION_LAYER_DATASET_H__