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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_LSTM_LAYER_DATASET
#define ARM_COMPUTE_TEST_LSTM_LAYER_DATASET
#include "utils/TypePrinter.h"
#include "arm_compute/core/TensorShape.h"
#include "arm_compute/core/Types.h"
namespace arm_compute
{
namespace test
{
namespace datasets
{
class LSTMLayerDataset
{
public:
using type = std::tuple<TensorShape, TensorShape, TensorShape, TensorShape, TensorShape, TensorShape, TensorShape, ActivationLayerInfo, float, float>;
struct iterator
{
iterator(std::vector<TensorShape>::const_iterator src_it,
std::vector<TensorShape>::const_iterator input_weights_it,
std::vector<TensorShape>::const_iterator recurrent_weights_it,
std::vector<TensorShape>::const_iterator cells_bias_it,
std::vector<TensorShape>::const_iterator output_cell_it,
std::vector<TensorShape>::const_iterator dst_it,
std::vector<TensorShape>::const_iterator scratch_it,
std::vector<ActivationLayerInfo>::const_iterator infos_it,
std::vector<float>::const_iterator cell_threshold_it,
std::vector<float>::const_iterator projection_threshold_it)
: _src_it{ std::move(src_it) },
_input_weights_it{ std::move(input_weights_it) },
_recurrent_weights_it{ std::move(recurrent_weights_it) },
_cells_bias_it{ std::move(cells_bias_it) },
_output_cell_it{ std::move(output_cell_it) },
_dst_it{ std::move(dst_it) },
_scratch_it{ std::move(scratch_it) },
_infos_it{ std::move(infos_it) },
_cell_threshold_it{ std::move(cell_threshold_it) },
_projection_threshold_it{ std::move(projection_threshold_it) }
{
}
std::string description() const
{
std::stringstream description;
description << "In=" << *_src_it << ":";
description << "InputWeights=" << *_input_weights_it << ":";
description << "RecurrentWeights=" << *_recurrent_weights_it << ":";
description << "Biases=" << *_cells_bias_it << ":";
description << "Scratch=" << *_scratch_it << ":";
description << "Out=" << *_dst_it;
return description.str();
}
LSTMLayerDataset::type operator*() const
{
return std::make_tuple(*_src_it, *_input_weights_it, *_recurrent_weights_it, *_cells_bias_it, *_output_cell_it, *_dst_it, *_scratch_it, *_infos_it, *_cell_threshold_it, *_projection_threshold_it);
}
iterator &operator++()
{
++_src_it;
++_input_weights_it;
++_recurrent_weights_it;
++_cells_bias_it;
++_output_cell_it;
++_dst_it;
++_scratch_it;
++_infos_it;
++_cell_threshold_it;
++_projection_threshold_it;
return *this;
}
private:
std::vector<TensorShape>::const_iterator _src_it;
std::vector<TensorShape>::const_iterator _input_weights_it;
std::vector<TensorShape>::const_iterator _recurrent_weights_it;
std::vector<TensorShape>::const_iterator _cells_bias_it;
std::vector<TensorShape>::const_iterator _output_cell_it;
std::vector<TensorShape>::const_iterator _dst_it;
std::vector<TensorShape>::const_iterator _scratch_it;
std::vector<ActivationLayerInfo>::const_iterator _infos_it;
std::vector<float>::const_iterator _cell_threshold_it;
std::vector<float>::const_iterator _projection_threshold_it;
};
iterator begin() const
{
return iterator(_src_shapes.begin(), _input_weights_shapes.begin(), _recurrent_weights_shapes.begin(), _cell_bias_shapes.begin(), _output_cell_shapes.begin(), _dst_shapes.begin(),
_scratch_shapes.begin(), _infos.begin(), _cell_threshold.begin(), _projection_threshold.begin());
}
int size() const
{
return std::min(_src_shapes.size(), std::min(_input_weights_shapes.size(), std::min(_recurrent_weights_shapes.size(), std::min(_cell_bias_shapes.size(), std::min(_output_cell_shapes.size(),
std::min(_dst_shapes.size(), std::min(_scratch_shapes.size(), std::min(_cell_threshold.size(), std::min(_projection_threshold.size(), _infos.size())))))))));
}
void add_config(TensorShape src, TensorShape input_weights, TensorShape recurrent_weights, TensorShape cell_bias_weights, TensorShape output_cell_state, TensorShape dst, TensorShape scratch,
ActivationLayerInfo info, float cell_threshold, float projection_threshold)
{
_src_shapes.emplace_back(std::move(src));
_input_weights_shapes.emplace_back(std::move(input_weights));
_recurrent_weights_shapes.emplace_back(std::move(recurrent_weights));
_cell_bias_shapes.emplace_back(std::move(cell_bias_weights));
_output_cell_shapes.emplace_back(std::move(output_cell_state));
_dst_shapes.emplace_back(std::move(dst));
_scratch_shapes.emplace_back(std::move(scratch));
_infos.emplace_back(std::move(info));
_cell_threshold.emplace_back(std::move(cell_threshold));
_projection_threshold.emplace_back(std::move(projection_threshold));
}
protected:
LSTMLayerDataset() = default;
LSTMLayerDataset(LSTMLayerDataset &&) = default;
private:
std::vector<TensorShape> _src_shapes{};
std::vector<TensorShape> _input_weights_shapes{};
std::vector<TensorShape> _recurrent_weights_shapes{};
std::vector<TensorShape> _cell_bias_shapes{};
std::vector<TensorShape> _output_cell_shapes{};
std::vector<TensorShape> _dst_shapes{};
std::vector<TensorShape> _scratch_shapes{};
std::vector<ActivationLayerInfo> _infos{};
std::vector<float> _cell_threshold{};
std::vector<float> _projection_threshold{};
};
class SmallLSTMLayerDataset final : public LSTMLayerDataset
{
public:
SmallLSTMLayerDataset()
{
add_config(TensorShape(8U), TensorShape(8U, 16U), TensorShape(16U, 16U), TensorShape(16U), TensorShape(16U), TensorShape(16U), TensorShape(64U),
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), 0.05f, 0.93f);
add_config(TensorShape(8U, 2U), TensorShape(8U, 16U), TensorShape(16U, 16U), TensorShape(16U), TensorShape(16U, 2U), TensorShape(16U, 2U), TensorShape(64U, 2U),
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), 0.05f, 0.93f);
add_config(TensorShape(8U, 2U), TensorShape(8U, 16U), TensorShape(16U, 16U), TensorShape(16U), TensorShape(16U, 2U), TensorShape(16U, 2U), TensorShape(48U, 2U),
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), 0.05f, 0.93f);
}
};
} // namespace datasets
} // namespace test
} // namespace arm_compute
#endif /* ARM_COMPUTE_TEST_LSTM_LAYER_DATASET */
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