142 lines
5.3 KiB
C++
142 lines
5.3 KiB
C++
/*
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* Copyright (c) 2018 Arm Limited.
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*
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* SPDX-License-Identifier: MIT
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to
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* deal in the Software without restriction, including without limitation the
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* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
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* sell copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*/
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#ifndef ARM_COMPUTE_TEST_RNN_LAYER_DATASET
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#define ARM_COMPUTE_TEST_RNN_LAYER_DATASET
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#include "utils/TypePrinter.h"
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#include "arm_compute/core/TensorShape.h"
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#include "arm_compute/core/Types.h"
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namespace arm_compute
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{
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namespace test
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{
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namespace datasets
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{
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class RNNLayerDataset
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{
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public:
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using type = std::tuple<TensorShape, TensorShape, TensorShape, TensorShape, TensorShape, ActivationLayerInfo>;
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struct iterator
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{
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iterator(std::vector<TensorShape>::const_iterator src_it,
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std::vector<TensorShape>::const_iterator weights_it,
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std::vector<TensorShape>::const_iterator recurrent_weights_it,
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std::vector<TensorShape>::const_iterator biases_it,
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std::vector<TensorShape>::const_iterator dst_it,
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std::vector<ActivationLayerInfo>::const_iterator infos_it)
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: _src_it{ std::move(src_it) },
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_weights_it{ std::move(weights_it) },
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_recurrent_weights_it{ std::move(recurrent_weights_it) },
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_biases_it{ std::move(biases_it) },
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_dst_it{ std::move(dst_it) },
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_infos_it{ std::move(infos_it) }
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{
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}
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std::string description() const
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{
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std::stringstream description;
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description << "In=" << *_src_it << ":";
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description << "Weights=" << *_weights_it << ":";
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description << "Biases=" << *_biases_it << ":";
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description << "Out=" << *_dst_it;
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return description.str();
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}
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RNNLayerDataset::type operator*() const
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{
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return std::make_tuple(*_src_it, *_weights_it, *_recurrent_weights_it, *_biases_it, *_dst_it, *_infos_it);
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}
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iterator &operator++()
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{
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++_src_it;
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++_weights_it;
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++_recurrent_weights_it;
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++_biases_it;
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++_dst_it;
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++_infos_it;
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return *this;
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}
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private:
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std::vector<TensorShape>::const_iterator _src_it;
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std::vector<TensorShape>::const_iterator _weights_it;
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std::vector<TensorShape>::const_iterator _recurrent_weights_it;
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std::vector<TensorShape>::const_iterator _biases_it;
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std::vector<TensorShape>::const_iterator _dst_it;
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std::vector<ActivationLayerInfo>::const_iterator _infos_it;
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};
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iterator begin() const
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{
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return iterator(_src_shapes.begin(), _weight_shapes.begin(), _recurrent_weight_shapes.begin(), _bias_shapes.begin(), _dst_shapes.begin(), _infos.begin());
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}
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int size() const
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{
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return std::min(_src_shapes.size(), std::min(_weight_shapes.size(), std::min(_recurrent_weight_shapes.size(), std::min(_bias_shapes.size(), std::min(_dst_shapes.size(), _infos.size())))));
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}
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void add_config(TensorShape src, TensorShape weights, TensorShape recurrent_weights, TensorShape biases, TensorShape dst, ActivationLayerInfo info)
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{
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_src_shapes.emplace_back(std::move(src));
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_weight_shapes.emplace_back(std::move(weights));
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_recurrent_weight_shapes.emplace_back(std::move(recurrent_weights));
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_bias_shapes.emplace_back(std::move(biases));
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_dst_shapes.emplace_back(std::move(dst));
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_infos.emplace_back(std::move(info));
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}
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protected:
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RNNLayerDataset() = default;
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RNNLayerDataset(RNNLayerDataset &&) = default;
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private:
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std::vector<TensorShape> _src_shapes{};
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std::vector<TensorShape> _weight_shapes{};
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std::vector<TensorShape> _recurrent_weight_shapes{};
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std::vector<TensorShape> _bias_shapes{};
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std::vector<TensorShape> _dst_shapes{};
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std::vector<ActivationLayerInfo> _infos{};
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};
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class SmallRNNLayerDataset final : public RNNLayerDataset
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{
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public:
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SmallRNNLayerDataset()
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{
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add_config(TensorShape(128U, 16U), TensorShape(128U, 32U), TensorShape(32U, 32U), TensorShape(32U), TensorShape(32U, 16U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
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}
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};
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} // namespace datasets
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} // namespace test
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} // namespace arm_compute
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#endif /* ARM_COMPUTE_TEST_RNN_LAYER_DATASET */
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