156 lines
5.8 KiB
C++
156 lines
5.8 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_COL2IM_DATASET
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#define ARM_COMPUTE_TEST_COL2IM_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 Col2ImLayerDataset
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{
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public:
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using type = std::tuple<TensorShape, unsigned int, unsigned int, unsigned int>;
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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<unsigned int>::const_iterator convolved_width_it,
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std::vector<unsigned int>::const_iterator convolved_height_it,
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std::vector<unsigned int>::const_iterator num_groups_it)
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: _src_it{ std::move(src_it) },
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_convolved_width_it{ std::move(convolved_width_it) },
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_convolved_height_it{ std::move(convolved_height_it) },
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_num_groups_it{ std::move(num_groups_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 << "ConvolvedWidth=" << *_convolved_width_it << ":";
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description << "ConvolvedHeight=" << *_convolved_height_it << ":";
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description << "NumGroups=" << *_num_groups_it;
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return description.str();
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}
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Col2ImLayerDataset::type operator*() const
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{
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return std::make_tuple(*_src_it, *_convolved_width_it, *_convolved_height_it, *_num_groups_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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++_convolved_width_it;
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++_convolved_height_it;
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++_num_groups_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<unsigned int>::const_iterator _convolved_width_it;
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std::vector<unsigned int>::const_iterator _convolved_height_it;
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std::vector<unsigned int>::const_iterator _num_groups_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(), _convolved_widths.begin(), _convolved_heights.begin(), _num_groups.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(_convolved_widths.size(), std::min(_convolved_heights.size(), _num_groups.size())));
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}
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void add_config(TensorShape src, unsigned int convolved_width, unsigned int convolved_height, unsigned int info)
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{
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_src_shapes.emplace_back(std::move(src));
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_convolved_widths.emplace_back(std::move(convolved_width));
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_convolved_heights.emplace_back(std::move(convolved_height));
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_num_groups.emplace_back(std::move(info));
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}
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protected:
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Col2ImLayerDataset() = default;
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Col2ImLayerDataset(Col2ImLayerDataset &&) = default;
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private:
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std::vector<TensorShape> _src_shapes{};
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std::vector<unsigned int> _convolved_widths{};
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std::vector<unsigned int> _convolved_heights{};
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std::vector<unsigned int> _num_groups{};
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};
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/** Dataset containing small grouped col2im shapes. */
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class SmallGroupedCol2ImLayerDataset final : public Col2ImLayerDataset
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{
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public:
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SmallGroupedCol2ImLayerDataset()
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{
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add_config(TensorShape(10U, 12U, 1U, 1U), 3U, 4U, 1U);
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add_config(TensorShape(12U, 30U, 1U, 2U), 5U, 6U, 1U);
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add_config(TensorShape(12U, 30U, 4U, 1U), 5U, 6U, 1U);
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add_config(TensorShape(10U, 12U, 2U, 4U), 3U, 4U, 2U);
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add_config(TensorShape(10U, 12U, 2U, 4U), 3U, 4U, 2U);
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add_config(TensorShape(8U, 16U, 3U, 1U), 4U, 4U, 3U);
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add_config(TensorShape(8U, 16U, 3U, 3U), 4U, 4U, 3U);
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add_config(TensorShape(12U, 20U, 4U, 1U), 5U, 4U, 4U);
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add_config(TensorShape(12U, 20U, 4U, 3U, 2U), 5U, 4U, 4U);
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}
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};
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/** Dataset containing large grouped col2im shapes. */
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class LargeGroupedCol2ImLayerDataset final : public Col2ImLayerDataset
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{
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public:
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LargeGroupedCol2ImLayerDataset()
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{
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add_config(TensorShape(233U, 280U, 1U, 55U), 14U, 20U, 1U);
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add_config(TensorShape(333U, 280U, 1U, 77U), 14U, 20U, 1U);
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add_config(TensorShape(333U, 280U, 77U, 1U), 14U, 20U, 1U);
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add_config(TensorShape(120U, 300U, 8U, 3U), 20U, 15U, 8U);
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add_config(TensorShape(233U, 300U, 8U, 3U, 2U), 20U, 15U, 8U);
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add_config(TensorShape(333U, 280U, 12U, 5U), 20U, 14U, 12U);
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add_config(TensorShape(177U, 300U, 12U, 5U), 15U, 20U, 12U);
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add_config(TensorShape(450U, 400U, 16U, 5U), 20U, 20U, 16U);
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add_config(TensorShape(220U, 400U, 16U, 5U), 20U, 20U, 16U);
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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_COL2IM_DATASET */
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