/* * Copyright (c) 2018-2019 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_PRIORBOX_LAYER_DATASET #define ARM_COMPUTE_TEST_PRIORBOX_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 PriorBoxLayerDataset { public: using type = std::tuple; struct iterator { iterator(std::vector::const_iterator src_it, std::vector::const_iterator infos_it) : _src_it{ std::move(src_it) }, _infos_it{ std::move(infos_it) } { } std::string description() const { std::stringstream description; description << "In=" << *_src_it << ":"; description << "Info=" << *_infos_it << ":"; return description.str(); } PriorBoxLayerDataset::type operator*() const { return std::make_tuple(*_src_it, *_infos_it); } iterator &operator++() { ++_src_it; ++_infos_it; return *this; } private: std::vector::const_iterator _src_it; std::vector::const_iterator _infos_it; }; iterator begin() const { return iterator(_src_shapes.begin(), _infos.begin()); } int size() const { return std::min(_src_shapes.size(), _infos.size()); } void add_config(TensorShape src, PriorBoxLayerInfo info) { _src_shapes.emplace_back(std::move(src)); _infos.emplace_back(std::move(info)); } protected: PriorBoxLayerDataset() = default; PriorBoxLayerDataset(PriorBoxLayerDataset &&) = default; private: std::vector _src_shapes{}; std::vector _infos{}; }; class SmallPriorBoxLayerDataset final : public PriorBoxLayerDataset { public: SmallPriorBoxLayerDataset() { std::vector min_val = { 30.f }; std::vector var = { 0.1, 0.1, 0.2, 0.2 }; std::vector max_val = { 60.f }; std::vector aspect_ratio = { 2.f }; std::array steps = { { 8.f, 8.f } }; add_config(TensorShape(4U, 4U), PriorBoxLayerInfo(min_val, var, 0.5f, true, false, max_val, aspect_ratio, Coordinates2D{ 8, 8 }, steps)); } }; class LargePriorBoxLayerDataset final : public PriorBoxLayerDataset { public: LargePriorBoxLayerDataset() { std::vector min_val = { 30.f }; std::vector var = { 0.1, 0.1, 0.2, 0.2 }; std::vector max_val = { 60.f }; std::vector aspect_ratio = { 2.f }; std::array steps = { { 8.f, 8.f } }; add_config(TensorShape(150U, 245U, 4U, 12U), PriorBoxLayerInfo(min_val, var, 0.5f, true, false, max_val, aspect_ratio, Coordinates2D{ 8, 8 }, steps)); } }; } // namespace datasets } // namespace test } // namespace arm_compute #endif /* ARM_COMPUTE_TEST_PRIORBOX_LAYER_DATASET */