136 lines
4.5 KiB
C++
136 lines
4.5 KiB
C++
/*
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* Copyright (c) 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_SPACE_TO_DEPTH_LAYER_DATASET
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#define ARM_COMPUTE_TEST_SPACE_TO_DEPTH_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 SpaceToDepthLayerDataset
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{
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public:
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using type = std::tuple<TensorShape, TensorShape, int32_t>;
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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 dst_it,
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std::vector<int>::const_iterator block_shape_it)
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: _src_it{ std::move(src_it) },
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_dst_it{ std::move(dst_it) },
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_block_shape_it{ std::move(block_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=" << *_src_it << ":";
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description << "Out=" << *_dst_it;
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description << "BlockShape=" << *_block_shape_it << ":";
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return description.str();
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}
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SpaceToDepthLayerDataset::type operator*() const
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{
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return std::make_tuple(*_src_it, *_dst_it, *_block_shape_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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++_dst_it;
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++_block_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 _src_it;
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std::vector<TensorShape>::const_iterator _dst_it;
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std::vector<int32_t>::const_iterator _block_shape_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(), _dst_shapes.begin(), _block_shape.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(_dst_shapes.size(), _block_shape.size()));
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}
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void add_config(TensorShape src, TensorShape dst, int32_t block_shape)
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{
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_src_shapes.emplace_back(std::move(src));
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_dst_shapes.emplace_back(std::move(dst));
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_block_shape.emplace_back(std::move(block_shape));
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}
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protected:
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SpaceToDepthLayerDataset() = default;
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SpaceToDepthLayerDataset(SpaceToDepthLayerDataset &&) = default;
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private:
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std::vector<TensorShape> _src_shapes{};
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std::vector<TensorShape> _dst_shapes{};
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std::vector<int32_t> _block_shape{};
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};
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class SmallSpaceToDepthLayerDataset final : public SpaceToDepthLayerDataset
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{
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public:
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SmallSpaceToDepthLayerDataset()
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{
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add_config(TensorShape(2U, 2U, 1U, 1U), TensorShape(1U, 1U, 4U, 1U), 2);
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add_config(TensorShape(6U, 2U, 1U, 1U), TensorShape(3U, 1U, 4U, 1U), 2);
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add_config(TensorShape(2U, 4U, 2U, 1U), TensorShape(1U, 2U, 8U, 1U), 2);
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add_config(TensorShape(2U, 6U, 1U, 2U), TensorShape(1U, 3U, 4U, 2U), 2);
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add_config(TensorShape(6U, 8U, 1U, 1U), TensorShape(3U, 4U, 4U, 1U), 2);
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add_config(TensorShape(6U, 8U, 15U, 5U), TensorShape(3U, 4U, 60U, 5U), 2);
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}
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};
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class LargeSpaceToDepthLayerDataset final : public SpaceToDepthLayerDataset
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{
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public:
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LargeSpaceToDepthLayerDataset()
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{
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add_config(TensorShape(128U, 64U, 2U, 1U), TensorShape(64U, 32U, 8U, 1U), 2);
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add_config(TensorShape(512U, 64U, 2U, 4U), TensorShape(256U, 32U, 8U, 4U), 2);
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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_SPACE_TO_DEPTH_LAYER_DATASET */
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