#pragma once /* * Copyright (C) 2024 Brett Terpstra * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef BLT_GP_SELECTION_H #define BLT_GP_SELECTION_H #include #include #include #include #include #include "blt/format/format.h" #include namespace blt::gp { struct selector_args { gp_program& program; const population_t& current_pop; population_stats& current_stats; prog_config_t& config; random_t& random; }; constexpr inline auto perform_elitism = [](const selector_args& args, population_t& next_pop) { auto& [program, current_pop, current_stats, config, random] = args; if (config.elites > 0 && current_pop.get_individuals().size() >= config.elites) { static thread_local tracked_vector> values; values.clear(); for (blt::size_t i = 0; i < config.elites; i++) values.emplace_back(i, current_pop.get_individuals()[i].fitness.adjusted_fitness); for (const auto& ind : blt::enumerate(current_pop.get_individuals())) { for (blt::size_t i = 0; i < config.elites; i++) { if (ind.second.fitness.adjusted_fitness >= values[i].second) { bool doesnt_contain = true; for (blt::size_t j = 0; j < config.elites; j++) { if (ind.first == values[j].first) doesnt_contain = false; } if (doesnt_contain) values[i] = {ind.first, ind.second.fitness.adjusted_fitness}; break; } } } for (blt::size_t i = 0; i < config.elites; i++) next_pop.get_individuals()[i].copy_fast(current_pop.get_individuals()[values[i].first].tree); return config.elites; } return 0ul; }; inline std::atomic parent_fitness = 0; inline std::atomic child_fitness = 0; template constexpr inline auto default_next_pop_creator = []( selector_args& args, Crossover& crossover_selection, Mutation& mutation_selection, Reproduction& reproduction_selection, tree_t& c1, tree_t* c2, const std::function& test_fitness_func) { auto& [program, current_pop, current_stats, config, random] = args; switch (random.get_i32(0, 3)) { case 0: if (c2 == nullptr) return 0; // everyone gets a chance once per loop. if (random.choice(config.crossover_chance)) { #ifdef BLT_TRACK_ALLOCATIONS auto state = tracker.start_measurement_thread_local(); #endif // crossover const tree_t* p1; const tree_t* p2; double parent_val = 0; do { p1 = &crossover_selection.select(program, current_pop); p2 = &crossover_selection.select(program, current_pop); fitness_t fitness1; fitness_t fitness2; test_fitness_func(*p1, fitness1, 0); test_fitness_func(*p2, fitness2, 0); parent_val = fitness1.adjusted_fitness + fitness2.adjusted_fitness; // BLT_TRACE("%ld> P1 Fit: %lf, P2 Fit: %lf", val, fitness1.adjusted_fitness, fitness2.adjusted_fitness); c1.copy_fast(*p1); c2->copy_fast(*p2); crossover_calls.value(1); } while (!config.crossover.get().apply(program, *p1, *p2, c1, *c2)); fitness_t fitness1; fitness_t fitness2; test_fitness_func(c1, fitness1, 0); test_fitness_func(*c2, fitness2, 0); const auto child_val = fitness1.adjusted_fitness + fitness2.adjusted_fitness; auto old_parent_val = parent_fitness.load(std::memory_order_relaxed); while (!parent_fitness.compare_exchange_weak(old_parent_val, old_parent_val + parent_val, std::memory_order_relaxed, std::memory_order_relaxed)) { } auto old_child_val = child_fitness.load(std::memory_order_relaxed); while (!child_fitness.compare_exchange_weak(old_child_val, old_child_val + child_val, std::memory_order_relaxed, std::memory_order_relaxed)) { } // BLT_TRACE("%ld> C1 Fit: %lf, C2 Fit: %lf", val, fitness1.adjusted_fitness, fitness2.adjusted_fitness); #ifdef BLT_TRACK_ALLOCATIONS tracker.stop_measurement_thread_local(state); crossover_calls.call(); if (state.getAllocatedByteDifference() != 0) { crossover_allocations.call(state.getAllocatedByteDifference()); crossover_allocations.set_value(std::max(crossover_allocations.get_value(), state.getAllocatedByteDifference())); } #endif return 2; } break; case 1: if (random.choice(config.mutation_chance)) { #ifdef BLT_TRACK_ALLOCATIONS auto state = tracker.start_measurement_thread_local(); #endif // mutation const tree_t* p; do { p = &mutation_selection.select(program, current_pop); c1.copy_fast(*p); mutation_calls.value(1); } while (!config.mutator.get().apply(program, *p, c1)); #ifdef BLT_TRACK_ALLOCATIONS tracker.stop_measurement_thread_local(state); mutation_calls.call(); if (state.getAllocationDifference() != 0) { mutation_allocations.call(state.getAllocatedByteDifference()); mutation_allocations.set_value(std::max(mutation_allocations.get_value(), state.getAllocatedByteDifference())); } #endif return 1; } break; case 2: if (config.reproduction_chance > 0 && random.choice(config.reproduction_chance)) { #ifdef BLT_TRACK_ALLOCATIONS auto state = tracker.start_measurement_thread_local(); #endif // reproduction c1.copy_fast(reproduction_selection.select(program, current_pop)); #ifdef BLT_TRACK_ALLOCATIONS tracker.stop_measurement_thread_local(state); reproduction_calls.call(); reproduction_calls.value(1); if (state.getAllocationDifference() != 0) { reproduction_allocations.call(state.getAllocatedByteDifference()); reproduction_allocations.set_value(std::max(reproduction_allocations.get_value(), state.getAllocatedByteDifference())); } #endif return 1; } break; default: #if BLT_DEBUG_LEVEL > 0 BLT_ABORT("This is not possible!"); #else BLT_UNREACHABLE; #endif } return 0; }; class selection_t { public: /** * @param program gp program to select with, used in randoms * @param pop population to select from * @param stats the populations statistics * @return */ virtual const tree_t& select(gp_program& program, const population_t& pop) = 0; /** * Is run once on a single thread before selection begins. allows you to preprocess the generation for fitness metrics. * TODO a method for parallel execution */ virtual void pre_process(gp_program&, population_t&) { } virtual ~selection_t() = default; }; class select_best_t final : public selection_t { public: void pre_process(gp_program&, population_t&) override; const tree_t& select(gp_program& program, const population_t& pop) override; private: std::atomic_uint64_t index = 0; }; class select_worst_t final : public selection_t { public: void pre_process(gp_program&, population_t&) override; const tree_t& select(gp_program& program, const population_t& pop) override; private: std::atomic_uint64_t index = 0; }; class select_random_t final : public selection_t { public: const tree_t& select(gp_program& program, const population_t& pop) override; }; class select_tournament_t final : public selection_t { public: explicit select_tournament_t(const size_t selection_size = 3): selection_size(selection_size) { if (selection_size == 0) BLT_ABORT("Unable to select with this size. Must select at least 1 individual_t!"); } const tree_t& select(gp_program& program, const population_t& pop) override; private: const size_t selection_size; }; class select_fitness_proportionate_t final : public selection_t { public: const tree_t& select(gp_program& program, const population_t& pop) override; }; } #endif //BLT_GP_SELECTION_H