144 lines
5.6 KiB
C++
144 lines
5.6 KiB
C++
/*
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* Copyright (c) 2018-2019 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_ROI_ALIGN_LAYER_DATASET
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#define ARM_COMPUTE_TEST_ROI_ALIGN_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 ROIDataset
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{
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public:
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using type = std::tuple<TensorShape, ROIPoolingLayerInfo, TensorShape>;
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struct iterator
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{
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iterator(std::vector<TensorShape>::const_iterator tensor_shape_it,
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std::vector<ROIPoolingLayerInfo>::const_iterator infos_it,
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std::vector<TensorShape>::const_iterator rois_shape_it)
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: _tensor_shape_it{ std::move(tensor_shape_it) },
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_infos_it{ std::move(infos_it) },
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_rois_shape_it{ std::move(rois_shape_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=" << *_tensor_shape_it << ":";
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description << "Info=" << *_infos_it << ":";
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description << "ROIS=" << *_rois_shape_it;
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return description.str();
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}
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ROIDataset::type operator*() const
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{
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return std::make_tuple(*_tensor_shape_it, *_infos_it, *_rois_shape_it);
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}
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iterator &operator++()
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{
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++_tensor_shape_it;
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++_infos_it;
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++_rois_shape_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 _tensor_shape_it;
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std::vector<ROIPoolingLayerInfo>::const_iterator _infos_it;
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std::vector<TensorShape>::const_iterator _rois_shape_it;
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};
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iterator begin() const
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{
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return iterator(_tensor_shapes.begin(), _infos.begin(), _rois_shape.begin());
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}
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int size() const
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{
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return std::min(std::min(_tensor_shapes.size(), _infos.size()), _rois_shape.size());
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}
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void add_config(TensorShape tensor_shape, ROIPoolingLayerInfo info, TensorShape rois_shape)
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{
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_tensor_shapes.emplace_back(std::move(tensor_shape));
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_infos.emplace_back(std::move(info));
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_rois_shape.emplace_back(std::move(rois_shape));
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}
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protected:
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ROIDataset() = default;
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ROIDataset(ROIDataset &&) = default;
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private:
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std::vector<TensorShape> _tensor_shapes{};
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std::vector<ROIPoolingLayerInfo> _infos{};
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std::vector<TensorShape> _rois_shape{};
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};
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class SmallROIDataset final : public ROIDataset
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{
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public:
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SmallROIDataset()
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{
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add_config(TensorShape(50U, 47U, 1U, 1U), ROIPoolingLayerInfo(7U, 7U, 1.f / 4.f), TensorShape(5U, 1U));
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add_config(TensorShape(50U, 47U, 3U, 4U), ROIPoolingLayerInfo(7U, 7U, 1.f / 4.f), TensorShape(5U, 1U));
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add_config(TensorShape(50U, 47U, 3U, 1U), ROIPoolingLayerInfo(7U, 7U, 1.f / 4.f), TensorShape(5U, 10U));
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add_config(TensorShape(50U, 47U, 10U, 1U), ROIPoolingLayerInfo(7U, 7U, 1.f / 4.f), TensorShape(5U, 80U));
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//Spatial Scale 1/4
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add_config(TensorShape(50U, 47U, 80U, 4U), ROIPoolingLayerInfo(7U, 7U, 1.f / 4.f), TensorShape(5U, 80U));
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add_config(TensorShape(50U, 47U, 3U, 1U), ROIPoolingLayerInfo(9U, 9U, 1.f / 4.f), TensorShape(5U, 40U));
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add_config(TensorShape(50U, 47U, 10U, 1U), ROIPoolingLayerInfo(9U, 9U, 1.f / 4.f), TensorShape(5U, 80U));
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add_config(TensorShape(50U, 47U, 80U, 8U), ROIPoolingLayerInfo(9U, 9U, 1.f / 4.f), TensorShape(5U, 80U));
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//Spatial Scale 1/8
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add_config(TensorShape(50U, 47U, 80U, 4U), ROIPoolingLayerInfo(7U, 7U, 1.f / 8.f), TensorShape(5U, 80U));
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add_config(TensorShape(50U, 47U, 3U, 1U), ROIPoolingLayerInfo(9U, 9U, 1.f / 8.f), TensorShape(5U, 40U));
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add_config(TensorShape(50U, 47U, 10U, 1U), ROIPoolingLayerInfo(9U, 9U, 1.f / 8.f), TensorShape(5U, 80U));
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add_config(TensorShape(50U, 47U, 80U, 8U), ROIPoolingLayerInfo(9U, 9U, 1.f / 8.f), TensorShape(5U, 80U));
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//Spatial Scale 1/16
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add_config(TensorShape(50U, 47U, 80U, 4U), ROIPoolingLayerInfo(7U, 7U, 1.f / 16.f), TensorShape(5U, 80U));
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add_config(TensorShape(50U, 47U, 3U, 1U), ROIPoolingLayerInfo(9U, 9U, 1.f / 16.f), TensorShape(5U, 40U));
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add_config(TensorShape(50U, 47U, 10U, 1U), ROIPoolingLayerInfo(9U, 9U, 1.f / 16.f), TensorShape(5U, 80U));
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add_config(TensorShape(50U, 47U, 80U, 8U), ROIPoolingLayerInfo(9U, 9U, 1.f / 16.f), TensorShape(5U, 80U));
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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_ROI_ALIGN_LAYER_DATASET */
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