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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_GEMMLOWP_DATASET
#define ARM_COMPUTE_TEST_GEMMLOWP_DATASET
#include "utils/TypePrinter.h"
#include "arm_compute/core/TensorShape.h"
namespace arm_compute
{
namespace test
{
namespace datasets
{
class GEMMLowpDataset
{
public:
using type = std::tuple<TensorShape, TensorShape, TensorShape, int32_t, int32_t>;
struct iterator
{
iterator(std::vector<TensorShape>::const_iterator a_it,
std::vector<TensorShape>::const_iterator b_it,
std::vector<TensorShape>::const_iterator c_it,
std::vector<int32_t>::const_iterator a_offset_it,
std::vector<int32_t>::const_iterator b_offset_it)
: _a_it{ std::move(a_it) },
_b_it{ std::move(b_it) },
_c_it{ std::move(c_it) },
_a_offset_it{ std::move(a_offset_it) },
_b_offset_it{ std::move(b_offset_it) }
{
}
std::string description() const
{
std::stringstream description;
description << "A=" << *_a_it << ":";
description << "B=" << *_b_it << ":";
description << "C=" << *_c_it << ":";
description << "a_offset=" << *_a_offset_it << ":";
description << "b_offset=" << *_b_offset_it << ":";
return description.str();
}
GEMMLowpDataset::type operator*() const
{
return std::make_tuple(*_a_it, *_b_it, *_c_it, *_a_offset_it, *_b_offset_it);
}
iterator &operator++()
{
++_a_it;
++_b_it;
++_c_it;
++_a_offset_it;
++_b_offset_it;
return *this;
}
private:
std::vector<TensorShape>::const_iterator _a_it;
std::vector<TensorShape>::const_iterator _b_it;
std::vector<TensorShape>::const_iterator _c_it;
std::vector<int32_t>::const_iterator _a_offset_it;
std::vector<int32_t>::const_iterator _b_offset_it;
};
iterator begin() const
{
return iterator(_a_shapes.begin(), _b_shapes.begin(), _c_shapes.begin(), _a_offset.begin(), _b_offset.begin());
}
int size() const
{
return std::min(_a_shapes.size(), std::min(_b_shapes.size(), std::min(_c_shapes.size(), std::min(_a_offset.size(), _b_offset.size()))));
}
void add_config(TensorShape a, TensorShape b, TensorShape c, int32_t a_offset, int32_t b_offset)
{
_a_shapes.emplace_back(std::move(a));
_b_shapes.emplace_back(std::move(b));
_c_shapes.emplace_back(std::move(c));
_a_offset.emplace_back(std::move(a_offset));
_b_offset.emplace_back(std::move(b_offset));
}
protected:
GEMMLowpDataset() = default;
GEMMLowpDataset(GEMMLowpDataset &&) = default;
private:
std::vector<TensorShape> _a_shapes{};
std::vector<TensorShape> _b_shapes{};
std::vector<TensorShape> _c_shapes{};
std::vector<int32_t> _a_offset{};
std::vector<int32_t> _b_offset{};
};
} // namespace datasets
} // namespace test
} // namespace arm_compute
#endif /* ARM_COMPUTE_TEST_GEMMLOWP_DATASET */
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