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/*
* Copyright (c) 2018 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_WINOGRAD_FILTER_TRANSFORM_DATASET
#define ARM_COMPUTE_TEST_WINOGRAD_FILTER_TRANSFORM_DATASET
#include "utils/TypePrinter.h"
#include "arm_compute/core/TensorShape.h"
namespace arm_compute
{
namespace test
{
namespace datasets
{
class WinogradFilterTransformDataset
{
public:
using type = std::tuple<TensorShape, bool>;
struct iterator
{
iterator(std::vector<TensorShape>::const_iterator a_it,
std::vector<bool>::const_iterator is_nchw_it)
: _a_it{ std::move(a_it) },
_is_nchw_it{ std::move(is_nchw_it) }
{
}
std::string description() const
{
std::stringstream description;
description << "Input=" << *_a_it << ":";
description << "IsNCHW=" << *_is_nchw_it << ":";
return description.str();
}
WinogradFilterTransformDataset::type operator*() const
{
return std::make_tuple(*_a_it, *_is_nchw_it);
}
iterator &operator++()
{
++_a_it;
++_is_nchw_it;
return *this;
}
private:
std::vector<TensorShape>::const_iterator _a_it;
std::vector<bool>::const_iterator _is_nchw_it;
};
iterator begin() const
{
return iterator(_a_shapes.begin(), _is_nchw.begin());
}
int size() const
{
return std::min(_a_shapes.size(), _is_nchw.size());
}
void add_config(TensorShape a, bool is_nchw)
{
_a_shapes.emplace_back(std::move(a));
_is_nchw.emplace_back(std::move(is_nchw));
}
protected:
WinogradFilterTransformDataset() = default;
WinogradFilterTransformDataset(WinogradFilterTransformDataset &&) = default;
private:
std::vector<TensorShape> _a_shapes{};
std::vector<bool> _is_nchw{};
};
class SmallWinogradFilterTransformDataset final : public WinogradFilterTransformDataset
{
public:
SmallWinogradFilterTransformDataset()
{
add_config(TensorShape(3U, 3U, 7U, 4U), true);
add_config(TensorShape(3U, 3U, 4U, 13U), true);
add_config(TensorShape(3U, 3U, 9U, 2U), true);
add_config(TensorShape(3U, 3U, 3U, 5U), true);
}
};
class LargeWinogradFilterTransformDataset final : public WinogradFilterTransformDataset
{
public:
LargeWinogradFilterTransformDataset()
{
add_config(TensorShape(3U, 3U, 32U, 64U), true);
add_config(TensorShape(3U, 3U, 51U, 13U), true);
add_config(TensorShape(3U, 3U, 53U, 47U), true);
add_config(TensorShape(3U, 3U, 128U, 384U), true);
}
};
} // namespace datasets
} // namespace test
} // namespace arm_compute
#endif /* ARM_COMPUTE_TEST_WINOGRAD_FILTER_TRANSFORM_DATASET */
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