/******************************************************************************* * * MIT License * * Copyright (C) 2022-2025 Advanced Micro Devices, Inc. All rights reserved. * * 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. * *******************************************************************************/ #pragma once #include #include #include #include #include #include #include #include #include #include #include namespace TensileLite { /** * \ingroup SolutionLibrary * * Uses a small neural network to rank solutions for a given size. */ template struct MLPClassificationLibrary : public SolutionLibrary { using MLPNet = MLPClassification::MLPNet; using SolutionFeatures = std::vector>>; using ProblemFeatures = std::vector>>; std::map> solutionmap; std::shared_ptr model; SolutionFeatures solFeatures; ProblemFeatures probFeatures; mutable std::atomic lastFindTopRetAll = false; static std::string Type() { return "MLPClassification"; } virtual std::string type() const override { return Type(); } virtual std::string description() const override { if(model == nullptr) return concatenate(type(), ", MLPNet: nullptr"); else return concatenate(type(), ": ", model->description()); } virtual std::shared_ptr getSolutionByIndex(MyProblem const& problem, Hardware const& hardware, const int index) const override { const bool experimental = Debug::Instance().useExperimentalSelection(); if(!experimental) { // If the experimental library mode is not on treat it like it asserted out return nullptr; } // ; auto indexMatch = solutionmap.find(index); if(indexMatch != solutionmap.end()) return indexMatch->second; return nullptr; } virtual std::shared_ptr findBestSolution(MyProblem const& problem, Hardware const& hardware, double* fitness = nullptr) const override { SolutionVector solutions = findTopSolutions(problem, hardware, 1); std::shared_ptr solution = nullptr; if(solutions.size() > 0) solution = solutions[0]; return solution; } virtual SolutionSet findAllSolutions(MyProblem const& problem, Hardware const& hardware, SolutionLibrarySearchType searchType = SolutionLibrarySearchType::DEFAULT) const override { const bool experimental = Debug::Instance().useExperimentalSelection(); if(!experimental) { // Skip the search for solutions if the environment variable // that enables the experimental method is not set SolutionSet rv; return rv; } SolutionSet rv; for(auto const& row : solutionmap) rv.insert(row.second); return rv; } virtual SolutionVector findTopSolutions(MyProblem const& problem, Hardware const& hardware, int numSolutions) const override { std::vector problemkey = ProblemKey::keyForProblem, MyProblem, float>( problem, this->probFeatures); auto logits = model->predict(problemkey); assert(logits.size() == solutionmap.size()); std::vector*>> solution_ranking; solution_ranking.reserve(solutionmap.size()); for(auto& s : solutionmap) solution_ranking.emplace_back(logits[s.second->libraryLogicIndex], (std::shared_ptr*)(&s.second)); SolutionVector rv; int numToSort = std::min(numSolutions, int(solution_ranking.size())); rv.reserve(numToSort); auto it = solution_ranking.begin(), it_end = solution_ranking.end(); while(it != it_end && numToSort) { std::partial_sort(it, it + numToSort, it_end, std::greater{}); for(; it != it + numToSort; it++) if((*((*it->second)->problemPredicate))(problem)) { rv.emplace_back(*it->second); numToSort--; } } // can't reach the requested number, means findTop already done its best lastFindTopRetAll = (rv.size() < numSolutions); return rv; } virtual bool lastFindTopAlreadyRetAll() const override { return lastFindTopRetAll; } virtual SolutionSet findAllSolutionsGroupedGemm(std::vector const& problems, Hardware const& hardware, SolutionLibrarySearchType searchType = SolutionLibrarySearchType::DEFAULT) const override { const bool experimental = Debug::Instance().useExperimentalSelection(); if(!experimental) { // Skip the search for solutions if the environment variable // that enables the experimental method is not set SolutionSet rv; return rv; } SolutionSet rv; for(auto const& row : solutionmap) rv.insert(row.second); return rv; } }; } // namespace TensileLite