Merge remote-tracking branch 'refs/remotes/origin/main'

main
Brett 2025-04-06 21:28:19 -04:00
commit d8c7a27214
20 changed files with 1300 additions and 1190 deletions

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@ -240,244 +240,7 @@
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<option name="/Default/CodeInspection/Highlighting/InspectionSeverities/=CppWrongSlashesInIncludeDirective/@EntryIndexRemoved" />
<option name="/Default/CodeInspection/Highlighting/InspectionSeverities/=CppEnforceNestedNamespacesStyle/@EntryIndexRemoved" />
<option name="/Default/CodeInspection/Highlighting/InspectionSeverities/=CppEnforceTypeAliasCodeStyle/@EntryIndexRemoved" />
<option name="/Default/CodeInspection/Highlighting/InspectionSeverities/=CppEnforceFunctionDeclarationStyle/@EntryIndexRemoved" />
<option name="/Default/CodeInspection/Highlighting/InspectionSeverities/=CppMemberInitializersOrder/@EntryIndexRemoved" />
<option name="/Default/CodeInspection/Highlighting/InspectionSeverities/=CppEnforceOverridingFunctionStyle/@EntryIndexRemoved" />
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<option name="/Default/CodeInspection/Highlighting/InspectionSeverities/=CppUseAuto/@EntryIndexRemoved" />
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<option name="/Default/CodeInspection/Highlighting/InspectionSeverities/=CppEnforceCVQualifiersPlacement/@EntryIndexRemoved" />
<option name="/Default/CodeInspection/Highlighting/InspectionSeverities/=CppEnforceCVQualifiersOrder/@EntryIndexRemoved" />
<option name="/Default/CodeInspection/Highlighting/InspectionSeverities/=CppUnnecessaryWhitespace/@EntryIndexRemoved" />
<option name="/Default/CodeInspection/Highlighting/InspectionSeverities/=CppTabsAreDisallowed/@EntryIndexRemoved" />
<option name="/Default/CodeInspection/Highlighting/InspectionSeverities/=CppDFAConstantConditions/@EntryIndexRemoved" />
<option name="/Default/CodeInspection/Highlighting/InspectionSeverities/=CppDFANullDereference/@EntryIndexRemoved" />
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<option name="/Default/CodeInspection/Highlighting/InspectionSeverities/=CppDFALoopConditionNotUpdated/@EntryIndexRemoved" />
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<option name="/Default/CodeInspection/Highlighting/InspectionSeverities/=CppDFAConstantParameter/@EntryIndexRemoved" />
<option name="/Default/CodeInspection/Highlighting/InspectionSeverities/=CppDFAConstantFunctionResult/@EntryIndexRemoved" />
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<option name="/Default/CodeInspection/Highlighting/InspectionSeverities/=CppDFAEndlessLoop/@EntryIndexRemoved" />
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<option name="/Default/CodeInspection/Highlighting/InspectionSeverities/=CppDFAUnusedValue/@EntryIndexRemoved" />
<option name="/Default/CodeInspection/Highlighting/InspectionSeverities/=CppDFAUnreadVariable/@EntryIndexRemoved" />
<option name="/Default/CodeInspection/Highlighting/InspectionSeverities/=CppDFATimeOver/@EntryIndexRemoved" />
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<option name="/Default/CodeStyle/Naming/CppNaming/Rules/=Class_0020and_0020struct_0020fields/@EntryIndexedValue" value="&lt;NamingElement Priority=&quot;11&quot;&gt;&lt;Descriptor Static=&quot;Indeterminate&quot; Constexpr=&quot;Indeterminate&quot; Const=&quot;Indeterminate&quot; Volatile=&quot;Indeterminate&quot; Accessibility=&quot;NOT_APPLICABLE&quot;&gt;&lt;type Name=&quot;class field&quot; /&gt;&lt;type Name=&quot;struct field&quot; /&gt;&lt;/Descriptor&gt;&lt;Policy Inspect=&quot;True&quot; WarnAboutPrefixesAndSuffixes=&quot;False&quot; Prefix=&quot;m_&quot; Suffix=&quot;&quot; Style=&quot;aa_bb&quot; /&gt;&lt;/NamingElement&gt;" type="string" />
</component>
</project>

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@ -27,7 +27,7 @@ macro(compile_options target_name)
sanitizers(${target_name})
endmacro()
project(blt-gp VERSION 0.3.32)
project(blt-gp VERSION 0.4.9)
include(CTest)
@ -122,5 +122,6 @@ if (${BUILD_GP_TESTS})
blt_add_project(blt-symbolic-regression tests/symbolic_regression_test.cpp test)
blt_add_project(blt-drop tests/drop_test.cpp test)
blt_add_project(blt-drop-2-type tests/2_type_drop_test.cpp test)
endif ()

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@ -1,4 +1,4 @@
#!/usr/bin/python3
#!python3
import subprocess

View File

@ -20,189 +20,208 @@
#define BLT_GP_EXAMPLE_SYMBOLIC_REGRESSION_H
#include "examples_base.h"
#include <blt/std/logging.h>
#include <blt/logging/logging.h>
#include <blt/format/format.h>
#include <iostream>
namespace blt::gp::example
{
class symbolic_regression_t : public example_base_t
{
public:
struct context
{
float x, y;
};
class symbolic_regression_t : public example_base_t
{
public:
struct context
{
float x, y;
};
private:
bool fitness_function(const tree_t& current_tree, fitness_t& fitness, size_t) const
{
constexpr static double value_cutoff = 1.e15;
for (auto& fitness_case : training_cases)
{
const auto diff = std::abs(fitness_case.y - current_tree.get_evaluation_value<float>(fitness_case));
if (diff < value_cutoff)
{
fitness.raw_fitness += diff;
if (diff <= 0.01)
fitness.hits++;
}
else
fitness.raw_fitness += value_cutoff;
}
fitness.standardized_fitness = fitness.raw_fitness;
fitness.adjusted_fitness = (1.0 / (1.0 + fitness.standardized_fitness));
return static_cast<size_t>(fitness.hits) == training_cases.size();
}
private:
bool fitness_function(const tree_t& current_tree, fitness_t& fitness, size_t) const
{
constexpr static double value_cutoff = 1.e15;
for (auto& fitness_case : training_cases)
{
BLT_GP_UPDATE_CONTEXT(fitness_case);
const auto diff = std::abs(fitness_case.y - current_tree.get_evaluation_value<float>(fitness_case));
if (diff < value_cutoff)
{
fitness.raw_fitness += diff;
if (diff <= 0.01)
fitness.hits++;
} else
fitness.raw_fitness += value_cutoff;
}
fitness.standardized_fitness = fitness.raw_fitness;
fitness.adjusted_fitness = (1.0 / (1.0 + fitness.standardized_fitness));
return static_cast<size_t>(fitness.hits) == training_cases.size();
}
static float example_function(const float x)
{
return x * x * x * x + x * x * x + x * x + x;
}
static float example_function(const float x)
{
return x * x * x * x + x * x * x + x * x + x;
}
public:
template <typename SEED>
symbolic_regression_t(SEED seed, const prog_config_t& config): example_base_t{std::forward<SEED>(seed), config}
{
BLT_INFO("Starting BLT-GP Symbolic Regression Example");
BLT_DEBUG("Setup Fitness cases");
for (auto& fitness_case : training_cases)
{
constexpr float range = 10;
constexpr float half_range = range / 2.0;
const auto x = program.get_random().get_float(-half_range, half_range);
const auto y = example_function(x);
fitness_case = {x, y};
}
public:
template <typename SEED>
symbolic_regression_t(SEED seed, const prog_config_t& config): example_base_t{std::forward<SEED>(seed), config}
{
BLT_INFO("Starting BLT-GP Symbolic Regression Example");
BLT_DEBUG("Setup Fitness cases");
for (auto& fitness_case : training_cases)
{
constexpr float range = 10;
constexpr float half_range = range / 2.0;
const auto x = program.get_random().get_float(-half_range, half_range);
const auto y = example_function(x);
fitness_case = {x, y};
}
fitness_function_ref = [this](const tree_t& t, fitness_t& f, const size_t i)
{
return fitness_function(t, f, i);
};
}
fitness_function_ref = [this](const tree_t& t, fitness_t& f, const size_t i) {
return fitness_function(t, f, i);
};
}
void setup_operations()
{
BLT_DEBUG("Setup Types and Operators");
static operation_t add{[](const float a, const float b) { return a + b; }, "add"};
static operation_t sub([](const float a, const float b) { return a - b; }, "sub");
static operation_t mul([](const float a, const float b) { return a * b; }, "mul");
static operation_t pro_div([](const float a, const float b) { return b == 0.0f ? 0.0f : a / b; }, "div");
static operation_t op_sin([](const float a) { return std::sin(a); }, "sin");
static operation_t op_cos([](const float a) { return std::cos(a); }, "cos");
static operation_t op_exp([](const float a) { return std::exp(a); }, "exp");
static operation_t op_log([](const float a) { return a <= 0.0f ? 0.0f : std::log(a); }, "log");
static auto lit = operation_t([this]()
{
return program.get_random().get_float(-1.0f, 1.0f);
}, "lit").set_ephemeral();
void setup_operations()
{
BLT_DEBUG("Setup Types and Operators");
static operation_t add{
// this is the function used by the operation
[](const float a, const float b) {
return a + b;
},
// this name is optional and is used if you print an individual
"add"
};
static operation_t sub([](const float a, const float b) {
return a - b;
}, "sub");
static operation_t mul([](const float a, const float b) {
return a * b;
}, "mul");
static operation_t pro_div([](const float a, const float b) {
return b == 0.0f ? 0.0f : a / b;
}, "div");
static operation_t op_sin([](const float a) {
return std::sin(a);
}, "sin");
static operation_t op_cos([](const float a) {
return std::cos(a);
}, "cos");
static operation_t op_exp([](const float a) {
return std::exp(a);
}, "exp");
static operation_t op_log([](const float a) {
return a <= 0.0f ? 0.0f : std::log(a);
}, "log");
static auto lit = operation_t([this]() {
return program.get_random().get_float(-1.0f, 1.0f);
}, "lit").set_ephemeral();
static operation_t op_x([](const context& context)
{
return context.x;
}, "x");
static operation_t op_x([](const context& context) {
return context.x;
}, "x");
operator_builder<context> builder{};
builder.build(add, sub, mul, pro_div, op_sin, op_cos, op_exp, op_log, lit, op_x);
program.set_operations(builder.grab());
}
operator_builder<context> builder{};
builder.build(add, sub, mul, pro_div, op_sin, op_cos, op_exp, op_log, lit, op_x);
program.set_operations(builder.grab());
}
void generate_initial_population()
{
BLT_DEBUG("Generate Initial Population");
static auto sel = select_tournament_t{};
if (crossover_sel == nullptr)
crossover_sel = &sel;
if (mutation_sel == nullptr)
mutation_sel = &sel;
if (reproduction_sel == nullptr)
reproduction_sel = &sel;
program.generate_population(program.get_typesystem().get_type<float>().id(), fitness_function_ref, *crossover_sel, *mutation_sel,
*reproduction_sel);
}
void generate_initial_population()
{
BLT_DEBUG("Generate Initial Population");
static auto sel = select_tournament_t{};
if (crossover_sel == nullptr)
crossover_sel = &sel;
if (mutation_sel == nullptr)
mutation_sel = &sel;
if (reproduction_sel == nullptr)
reproduction_sel = &sel;
program.generate_initial_population(program.get_typesystem().get_type<float>().id());
program.setup_generational_evaluation(fitness_function_ref, *crossover_sel,
*mutation_sel, *reproduction_sel);
}
void run_generation_loop()
{
BLT_DEBUG("Begin Generation Loop");
while (!program.should_terminate())
{
#ifdef BLT_TRACK_ALLOCATIONS
void run_generation_loop()
{
BLT_DEBUG("Begin Generation Loop");
while (!program.should_terminate())
{
#ifdef BLT_TRACK_ALLOCATIONS
auto cross = crossover_calls.start_measurement();
auto mut = mutation_calls.start_measurement();
auto repo = reproduction_calls.start_measurement();
#endif
BLT_TRACE("------------{Begin Generation %ld}------------", program.get_current_generation());
BLT_TRACE("Creating next generation");
program.create_next_generation();
BLT_TRACE("Move to next generation");
program.next_generation();
BLT_TRACE("Evaluate Fitness");
program.evaluate_fitness();
const auto& stats = program.get_population_stats();
BLT_TRACE("Avg Fit: %lf, Best Fit: %lf, Worst Fit: %lf, Overall Fit: %lf",
stats.average_fitness.load(std::memory_order_relaxed), stats.best_fitness.load(std::memory_order_relaxed),
stats.worst_fitness.load(std::memory_order_relaxed), stats.overall_fitness.load(std::memory_order_relaxed));
#ifdef BLT_TRACK_ALLOCATIONS
#endif
BLT_TRACE("------------\\{Begin Generation {}}------------", program.get_current_generation());
BLT_TRACE("Creating next generation");
program.create_next_generation();
BLT_TRACE("Move to next generation");
program.next_generation();
BLT_TRACE("Evaluate Fitness");
program.evaluate_fitness();
const auto& stats = program.get_population_stats();
BLT_TRACE("Avg Fit: {:0.6f}, Best Fit: {:0.6f}, Worst Fit: {:0.6f}, Overall Fit: {:0.6f}", stats.average_fitness.load(std::memory_order_relaxed),
stats.best_fitness.load(std::memory_order_relaxed), stats.worst_fitness.load(std::memory_order_relaxed),
stats.overall_fitness.load(std::memory_order_relaxed));
#ifdef BLT_TRACK_ALLOCATIONS
crossover_calls.stop_measurement(cross);
mutation_calls.stop_measurement(mut);
reproduction_calls.stop_measurement(repo);
const auto total = (cross.get_call_difference() * 2) + mut.get_call_difference() + repo.get_call_difference();
BLT_TRACE("Calls Crossover: %ld, Mutation %ld, Reproduction %ld; %ld", cross.get_call_difference(), mut.get_call_difference(), repo.get_call_difference(), total);
BLT_TRACE("Value Crossover: %ld, Mutation %ld, Reproduction %ld; %ld", cross.get_value_difference(), mut.get_value_difference(), repo.get_value_difference(), (cross.get_value_difference() * 2 + mut.get_value_difference() + repo.get_value_difference()) - total);
#endif
BLT_TRACE("----------------------------------------------");
std::cout << std::endl;
}
}
BLT_TRACE("Calls Crossover: {}, Mutation {}, Reproduction {}; {}", cross.get_call_difference(), mut.get_call_difference(), repo.get_call_difference(), total);
BLT_TRACE("Value Crossover: {}, Mutation {}, Reproduction {}; {}", cross.get_value_difference(), mut.get_value_difference(), repo.get_value_difference(), (cross.get_value_difference() * 2 + mut.get_value_difference() + repo.get_value_difference()) - total);
#endif
BLT_TRACE("----------------------------------------------");
std::cout << std::endl;
}
}
auto get_and_print_best()
{
const auto best = program.get_best_individuals<3>();
auto get_and_print_best()
{
const auto best = program.get_best_individuals<3>();
BLT_INFO("Best approximations:");
for (auto& i_ref : best)
{
auto& i = i_ref.get();
BLT_DEBUG("Fitness: %lf, stand: %lf, raw: %lf", i.fitness.adjusted_fitness, i.fitness.standardized_fitness, i.fitness.raw_fitness);
i.tree.print(std::cout);
std::cout << "\n";
}
BLT_INFO("Best approximations:");
for (auto& i_ref : best)
{
auto& i = i_ref.get();
BLT_DEBUG("Fitness: {:0.6f}, stand: {:0.6f}, raw: {:0.6f}", i.fitness.adjusted_fitness, i.fitness.standardized_fitness, i.fitness.raw_fitness);
i.tree.print(std::cout);
std::cout << "\n";
}
return best;
}
return best;
}
void print_stats() const
{
// TODO: make stats helper
const auto& stats = program.get_population_stats();
BLT_INFO("Stats:");
BLT_INFO("Average fitness: %lf", stats.average_fitness.load());
BLT_INFO("Best fitness: %lf", stats.best_fitness.load());
BLT_INFO("Worst fitness: %lf", stats.worst_fitness.load());
BLT_INFO("Overall fitness: %lf", stats.overall_fitness.load());
}
void print_stats() const
{
// TODO: make stats helper
const auto& stats = program.get_population_stats();
BLT_INFO("Stats:");
BLT_INFO("Average fitness: {:0.6f}", stats.average_fitness.load());
BLT_INFO("Best fitness: {:0.6f}", stats.best_fitness.load());
BLT_INFO("Worst fitness: {:0.6f}", stats.worst_fitness.load());
BLT_INFO("Overall fitness: {:0.6f}", stats.overall_fitness.load());
}
void execute()
{
setup_operations();
void execute()
{
setup_operations();
generate_initial_population();
generate_initial_population();
run_generation_loop();
run_generation_loop();
get_and_print_best();
get_and_print_best();
print_stats();
}
print_stats();
}
[[nodiscard]] const auto& get_training_cases() const
{
return training_cases;
}
[[nodiscard]] const auto& get_training_cases() const
{
return training_cases;
}
private:
std::array<context, 200> training_cases{};
};
private:
std::array<context, 200> training_cases{};
};
}
#endif //BLT_GP_EXAMPLE_SYMBOLIC_REGRESSION_H

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@ -20,7 +20,7 @@
#define BLT_GP_ALLOCATOR_H
#include <blt/std/types.h>
#include <blt/std/logging.h>
#include <blt/logging/logging.h>
#include <blt/gp/util/trackers.h>
#include <cstdlib>
#include <vector>

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@ -63,9 +63,10 @@ namespace blt::gp
template<typename T>
static void call_drop(stack_allocator& read_allocator, const size_t offset)
{
if constexpr (blt::gp::detail::has_func_drop_v<T>)
if constexpr (blt::gp::detail::has_func_drop_v<detail::remove_cv_ref<T>>)
{
auto [type, ptr] = read_allocator.access_pointer<detail::remove_cv_ref<T>>(offset);
// type is not ephemeral, so we must drop it.
if (!ptr.bit(0))
type.drop();
}
@ -200,7 +201,7 @@ namespace blt::gp
[[nodiscard]] bool return_has_ephemeral_drop() const
{
return detail::has_func_drop_v<Return>;
return detail::has_func_drop_v<detail::remove_cv_ref<Return>>;
}
operator_id id = -1;

File diff suppressed because it is too large Load Diff

View File

@ -61,16 +61,16 @@ namespace blt::gp
{
for (size_t i = 0; i < config.elites; i++)
{
if (ind.value.fitness.adjusted_fitness >= values[i].second)
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.index == values[j].first)
if (ind.first == values[j].first)
doesnt_contain = false;
}
if (doesnt_contain)
values[i] = {ind.index, ind.value.fitness.adjusted_fitness};
values[i] = {ind.first, ind.second.fitness.adjusted_fitness};
break;
}
}

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@ -21,21 +21,16 @@
#include <blt/std/types.h>
#include <blt/std/bump_allocator.h>
#include <blt/std/assert.h>
#include <blt/std/logging.h>
#include <blt/logging/logging.h>
#include <blt/std/allocator.h>
#include <blt/std/ranges.h>
#include <blt/meta/meta.h>
#include <blt/gp/fwdecl.h>
#include <blt/gp/util/trackers.h>
#include <blt/gp/util/meta.h>
#include <blt/gp/allocator.h>
#include <utility>
#include <stdexcept>
#include <cstdlib>
#include <memory>
#include <type_traits>
#include <cstring>
#include <iostream>
namespace blt::gp
{
@ -87,7 +82,7 @@ namespace blt::gp
static constexpr size_t aligned_size() noexcept
{
const auto bytes = detail::aligned_size(sizeof(NO_REF_T<T>));
if constexpr (blt::gp::detail::has_func_drop_v<T>)
if constexpr (blt::gp::detail::has_func_drop_v<gp::detail::remove_cv_ref<T>>)
return bytes + detail::aligned_size(sizeof(std::atomic_uint64_t*));
return bytes;
}
@ -179,7 +174,7 @@ namespace blt::gp
const auto ptr = static_cast<char*>(allocate_bytes_for_size(aligned_size<NO_REF>()));
std::memcpy(ptr, &t, sizeof(NO_REF));
if constexpr (gp::detail::has_func_drop_v<T>)
if constexpr (gp::detail::has_func_drop_v<gp::detail::remove_cv_ref<T>>)
{
new(ptr + sizeof(NO_REF)) mem::pointer_storage<std::atomic_uint64_t>{nullptr};
}

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@ -166,7 +166,7 @@ namespace blt::gp
~evaluation_ref()
{
if constexpr (detail::has_func_drop_v<T>)
if constexpr (detail::has_func_drop_v<detail::remove_cv_ref<T>>)
{
if (m_value.get() != nullptr)
{

View File

@ -48,7 +48,7 @@ namespace blt::gp
template <typename T>
static type make_type(const type_id id)
{
return type(stack_allocator::aligned_size<T>(), id, blt::type_string<T>(), detail::has_func_drop_v<T>);
return type(stack_allocator::aligned_size<T>(), id, blt::type_string<T>(), detail::has_func_drop_v<detail::remove_cv_ref<T>>);
}
[[nodiscard]] size_t size() const

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@ -17,7 +17,7 @@
*/
#include <blt/gp/generators.h>
#include <blt/gp/program.h>
#include <blt/std/logging.h>
#include <blt/logging/logging.h>
#include <stack>
namespace blt::gp

View File

@ -26,36 +26,36 @@ namespace blt::gp
static advanced_mutation_t s_mutator;
static crossover_t s_crossover;
static ramped_half_initializer_t s_init;
prog_config_t::prog_config_t(): mutator(s_mutator), crossover(s_crossover), pop_initializer(s_init)
{
}
prog_config_t::prog_config_t(const std::reference_wrapper<population_initializer_t>& popInitializer):
mutator(s_mutator), crossover(s_crossover), pop_initializer(popInitializer)
{}
prog_config_t::prog_config_t(size_t populationSize, const std::reference_wrapper<population_initializer_t>& popInitializer):
population_size(populationSize), mutator(s_mutator), crossover(s_crossover), pop_initializer(popInitializer)
{}
prog_config_t::prog_config_t(size_t populationSize):
population_size(populationSize), mutator(s_mutator), crossover(s_crossover), pop_initializer(s_init)
{}
random_t& gp_program::get_random() const
{
thread_local static blt::gp::random_t random_engine{seed_func()};
return random_engine;
}
stack_allocator::Allocator& stack_allocator::get_allocator()
{
static Allocator allocator;
return allocator;
}
void gp_program::create_threads()
{
#ifdef BLT_TRACK_ALLOCATIONS

View File

@ -20,12 +20,12 @@
namespace blt::gp
{
void select_best_t::pre_process(gp_program&, population_t& pop)
void select_best_t::pre_process(gp_program&, population_t&)
{
std::sort(pop.begin(), pop.end(), [](const auto& a, const auto& b)
{
return a.fitness.adjusted_fitness > b.fitness.adjusted_fitness;
});
// std::sort(pop.begin(), pop.end(), [](const auto& a, const auto& b)
// {
// return a.fitness.adjusted_fitness > b.fitness.adjusted_fitness;
// });
index = 0;
}
@ -35,19 +35,19 @@ namespace blt::gp
return pop.get_individuals()[index.fetch_add(1, std::memory_order_relaxed) % size].tree;
}
void select_worst_t::pre_process(gp_program&, population_t& pop)
void select_worst_t::pre_process(gp_program&, population_t&)
{
std::sort(pop.begin(), pop.end(), [](const auto& a, const auto& b)
{
return a.fitness.adjusted_fitness < b.fitness.adjusted_fitness;
});
// std::sort(pop.begin(), pop.end(), [](const auto& a, const auto& b)
// {
// return a.fitness.adjusted_fitness < b.fitness.adjusted_fitness;
// });
index = 0;
}
const tree_t& select_worst_t::select(gp_program&, const population_t& pop)
{
const auto size = pop.get_individuals().size();
return pop.get_individuals()[index.fetch_add(1, std::memory_order_relaxed) % size].tree;
return pop.get_individuals()[(size - 1) - (index.fetch_add(1, std::memory_order_relaxed) % size)].tree;
}
const tree_t& select_random_t::select(gp_program& program, const population_t& pop)

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@ -145,15 +145,34 @@ namespace blt::gp
size_t mutation_t::mutate_point(gp_program& program, tree_t& c, const tree_t::subtree_point_t node) const
{
auto& new_tree = tree_t::get_thread_local(program);
#if BLT_DEBUG_LEVEL >= 2
auto previous_size = new_tree.size();
auto previous_bytes = new_tree.total_value_bytes();
#endif
config.generator.get().generate(new_tree, {program, node.type, config.replacement_min_depth, config.replacement_max_depth});
#if BLT_DEBUG_LEVEL >= 2
const auto old_op = c.get_operator(node.pos);
if (!new_tree.check(detail::debug::context_ptr))
{
BLT_ERROR("Mutate point new tree check failed!");
BLT_ERROR("Old Op: {} got replaced with New Op: {}", program.get_name(old_op.id()).value_or("Unknown"),
program.get_name(new_tree.get_operator(0).id()).value_or("Unknown"));
BLT_ERROR("Tree started with size: {} and bytes: {}", previous_size, previous_bytes);
throw std::runtime_error("Mutate Point tree check failed");
}
#endif
c.replace_subtree(node, new_tree);
// this will check to make sure that the tree is in a correct and executable state. it requires that the evaluation is context free!
#if BLT_DEBUG_LEVEL >= 2
const auto new_op = c.get_operator(node.pos);
if (!c.check(detail::debug::context_ptr))
{
print_mutate_stats();
BLT_ERROR("Old Op: {} got replaced with New Op: {}", program.get_name(old_op.id()).value_or("Unknown"),
program.get_name(new_op.id()).value_or("Unknown"));
throw std::runtime_error("Mutate Point tree check failed");
}
#endif

View File

@ -18,7 +18,7 @@
#include <blt/gp/tree.h>
#include <blt/gp/stack.h>
#include <blt/std/assert.h>
#include <blt/std/logging.h>
#include <blt/logging/logging.h>
#include <blt/gp/program.h>
#include <stack>
@ -501,6 +501,7 @@ namespace blt::gp
tree_t& tree_t::get_thread_local(gp_program& program)
{
thread_local tree_t tree{program};
tree.clear(program);
return tree;
}
@ -544,8 +545,8 @@ namespace blt::gp
if (bytes_expected != bytes_size)
{
BLT_ERROR_STREAM << "Stack state: " << values.size() << "\n";
BLT_ERROR("Child tree bytes %ld vs expected %ld, difference: %ld", bytes_size, bytes_expected,
BLT_ERROR("Stack state: {}", values.size());
BLT_ERROR("Child tree bytes {} vs expected {}, difference: {}", bytes_size, bytes_expected,
static_cast<ptrdiff_t>(bytes_expected) - static_cast<ptrdiff_t>(bytes_size));
BLT_ERROR("Amount of bytes in stack doesn't match the number of bytes expected for the operations");
return false;
@ -588,18 +589,18 @@ namespace blt::gp
if (v1 != v2)
{
const auto vd = std::abs(v1 - v2);
BLT_ERROR("found %ld bytes expected %ld bytes, total difference: %ld", v1, v2, vd);
BLT_ERROR("Total Produced %ld || Total Consumed %ld || Total Difference %ld", total_produced, total_consumed,
BLT_ERROR("found {} bytes expected {} bytes, total difference: {}", v1, v2, vd);
BLT_ERROR("Total Produced {} || Total Consumed {} || Total Difference {}", total_produced, total_consumed,
std::abs(static_cast<blt::ptrdiff_t>(total_produced) - static_cast<blt::ptrdiff_t>(total_consumed)));
return false;
}
}
catch (std::exception& e)
{
BLT_ERROR("Exception occurred \"%s\"", e.what());
BLT_ERROR("Total Produced %ld || Total Consumed %ld || Total Difference %ld", total_produced, total_consumed,
BLT_ERROR("Exception occurred \"{}\"", e.what());
BLT_ERROR("Total Produced {} || Total Consumed {} || Total Difference {}", total_produced, total_consumed,
std::abs(static_cast<blt::ptrdiff_t>(total_produced) - static_cast<blt::ptrdiff_t>(total_consumed)));
BLT_ERROR("We failed at index %lu", index);
BLT_ERROR("We failed at index {}", index);
return false;
}
return true;

View File

@ -16,7 +16,7 @@
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
#include <blt/gp/util/trackers.h>
#include <blt/std/logging.h>
#include <blt/logging/logging.h>
#include "blt/format/format.h"
#include <numeric>

194
tests/2_type_drop_test.cpp Normal file
View File

@ -0,0 +1,194 @@
/*
* <Short Description>
* Copyright (C) 2025 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 <https://www.gnu.org/licenses/>.
*/
#include "../examples/symbolic_regression.h"
#include <blt/gp/program.h>
#include <blt/logging/logging.h>
using namespace blt::gp;
std::atomic_uint64_t normal_construct = 0;
std::atomic_uint64_t ephemeral_construct = 0;
std::atomic_uint64_t normal_drop = 0;
std::atomic_uint64_t ephemeral_drop = 0;
std::atomic_uint64_t max_allocated = 0;
struct drop_type
{
float* m_value;
bool ephemeral = false;
drop_type() : m_value(new float(0))
{
++normal_construct;
}
explicit drop_type(const float silly) : m_value(new float(silly))
{
++normal_construct;
}
explicit drop_type(const float silly, bool) : m_value(new float(silly)), ephemeral(true)
{
// BLT_TRACE("Constructor with value %f", silly);
++ephemeral_construct;
}
[[nodiscard]] float value() const
{
return *m_value;
}
void drop() const
{
if (ephemeral)
{
std::cout << ("Ephemeral drop") << std::endl;
++ephemeral_drop;
}
else
++normal_drop;
delete m_value;
}
friend std::ostream& operator<<(std::ostream& os, const drop_type& dt)
{
os << dt.m_value;
return os;
}
};
struct context
{
float x, y;
};
prog_config_t config = prog_config_t()
.set_initial_min_tree_size(2)
.set_initial_max_tree_size(6)
.set_elite_count(2)
.set_crossover_chance(0.8)
.set_mutation_chance(0.1)
.set_reproduction_chance(0.1)
.set_max_generations(50)
.set_pop_size(500)
.set_thread_count(1);
example::symbolic_regression_t regression{691ul, config};
operation_t add{[](const drop_type a, const drop_type b) { return drop_type{a.value() + b.value()}; }, "add"};
operation_t addf{[](const float a, const float b) { return a + b; }, "addf"};
operation_t sub([](const drop_type a, const drop_type b) { return drop_type{a.value() - b.value()}; }, "sub");
operation_t subf([](const float a, const float b) { return a - b; }, "subf");
operation_t mul([](const drop_type a, const drop_type b) { return drop_type{a.value() * b.value()}; }, "mul");
operation_t mulf([](const float a, const float b) { return a * b; }, "mulf");
operation_t pro_div([](const drop_type a, const drop_type b) { return drop_type{b.value() == 0.0f ? 0.0f : a.value() / b.value()}; }, "div");
operation_t pro_divf([](const float a, const float b) { return b == 0.0f ? 0.0f : a / b; }, "divf");
operation_t op_sin([](const drop_type a) { return drop_type{std::sin(a.value())}; }, "sin");
operation_t op_sinf([](const float a) { return std::sin(a); }, "sinf");
operation_t op_cos([](const drop_type a) { return drop_type{std::cos(a.value())}; }, "cos");
operation_t op_cosf([](const float a) { return std::cos(a); }, "cosf");
operation_t op_exp([](const drop_type a) { return drop_type{std::exp(a.value())}; }, "exp");
operation_t op_expf([](const float a) { return std::exp(a); }, "expf");
operation_t op_log([](const drop_type a) { return drop_type{a.value() <= 0.0f ? 0.0f : std::log(a.value())}; }, "log");
operation_t op_logf([](const float a) { return a <= 0.0f ? 0.0f : std::log(a); }, "logf");
operation_t op_tof([](const drop_type a) { return a.value(); }, "to_f");
operation_t op_todrop([](const float a) { return drop_type{a}; }, "to_drop");
operation_t op_mixed_input([](const drop_type a, const float f)
{
return a.value() + f;
}, "mixed_input");
auto lit = operation_t([]()
{
return drop_type{regression.get_program().get_random().get_float(-1.0f, 1.0f), true};
}, "lit").set_ephemeral();
auto litf = operation_t([]()
{
return regression.get_program().get_random().get_float(-1.0f, 1.0f);
}, "litf").set_ephemeral();
operation_t op_x([](const context& context)
{
return drop_type{context.x};
}, "x");
operation_t op_xf([](const context& context)
{
return context.x;
}, "xf");
bool fitness_function(const tree_t& current_tree, fitness_t& fitness, size_t)
{
if (normal_construct - normal_drop > max_allocated)
max_allocated = normal_construct - normal_drop;
constexpr static double value_cutoff = 1.e15;
for (auto& fitness_case : regression.get_training_cases())
{
BLT_GP_UPDATE_CONTEXT(fitness_case);
auto val = current_tree.get_evaluation_ref<drop_type>(fitness_case);
const auto diff = std::abs(fitness_case.y - val.get().value());
if (diff < value_cutoff)
{
fitness.raw_fitness += diff;
if (diff <= 0.01)
fitness.hits++;
}
else
fitness.raw_fitness += value_cutoff;
}
fitness.standardized_fitness = fitness.raw_fitness;
fitness.adjusted_fitness = (1.0 / (1.0 + fitness.standardized_fitness));
return static_cast<size_t>(fitness.hits) == regression.get_training_cases().size();
}
int main()
{
operator_builder<context> builder{};
builder.build(add, sub, mul, pro_div, op_sin, op_cos, op_exp, op_log, op_mixed_input, lit, op_x, addf, subf, mulf, pro_divf, op_sinf, op_cosf,
op_expf, op_logf,
litf, op_xf, op_tof, op_todrop);
regression.get_program().set_operations(builder.grab());
auto& program = regression.get_program();
static auto sel = select_tournament_t{};
program.generate_initial_population(program.get_typesystem().get_type<drop_type>().id());
program.setup_generational_evaluation(fitness_function, sel, sel, sel);
while (!program.should_terminate())
{
BLT_TRACE("---------------\\{Begin Generation {}}---------------", program.get_current_generation());
BLT_TRACE("Creating next generation");
program.create_next_generation();
BLT_TRACE("Move to next generation");
program.next_generation();
BLT_TRACE("Evaluate Fitness");
program.evaluate_fitness();
}
// program.get_best_individuals<1>()[0].get().tree.print(program, std::cout, true, true);
regression.get_program().get_current_pop().clear();
regression.get_program().next_generation();
regression.get_program().get_current_pop().clear();
BLT_TRACE("Created {} times", normal_construct.load());
BLT_TRACE("Dropped {} times", normal_drop.load());
BLT_TRACE("Ephemeral created {} times", ephemeral_construct.load());
BLT_TRACE("Ephemeral dropped {} times", ephemeral_drop.load());
BLT_TRACE("Max allocated {} times", max_allocated.load());
}

View File

@ -17,7 +17,7 @@
*/
#include "../examples/symbolic_regression.h"
#include <blt/gp/program.h>
#include <blt/std/logging.h>
#include <blt/logging/logging.h>
using namespace blt::gp;
@ -140,10 +140,11 @@ int main()
auto& program = regression.get_program();
static auto sel = select_tournament_t{};
program.generate_population(program.get_typesystem().get_type<drop_type>().id(), fitness_function, sel, sel, sel);
program.generate_initial_population(program.get_typesystem().get_type<drop_type>().id());
program.setup_generational_evaluation(fitness_function, sel, sel, sel);
while (!program.should_terminate())
{
BLT_TRACE("---------------{Begin Generation %lu}---------------", program.get_current_generation());
BLT_TRACE("---------------\\{Begin Generation {}}---------------", program.get_current_generation());
BLT_TRACE("Creating next generation");
program.create_next_generation();
BLT_TRACE("Move to next generation");
@ -158,10 +159,10 @@ int main()
regression.get_program().next_generation();
regression.get_program().get_current_pop().clear();
BLT_TRACE("Created %ld times", normal_construct.load());
BLT_TRACE("Dropped %ld times", normal_drop.load());
BLT_TRACE("Ephemeral created %ld times", ephemeral_construct.load());
BLT_TRACE("Ephemeral dropped %ld times", ephemeral_drop.load());
BLT_TRACE("Max allocated %ld times", max_allocated.load());
BLT_TRACE("Created {} times", normal_construct.load());
BLT_TRACE("Dropped {} times", normal_drop.load());
BLT_TRACE("Ephemeral created {} times", ephemeral_construct.load());
BLT_TRACE("Ephemeral dropped {} times", ephemeral_drop.load());
BLT_TRACE("Max allocated {} times", max_allocated.load());
}

View File

@ -19,6 +19,7 @@
#include <fstream>
#include <array>
#include <sstream>
#include <blt/profiling/profiler_v2.h>
static const auto SEED_FUNC = [] { return std::random_device()(); };
@ -56,7 +57,7 @@ void run(const blt::gp::prog_config_t& config)
auto mut = mutation_calls.start_measurement();
auto repo = reproduction_calls.start_measurement();
#endif
BLT_TRACE("------------{Begin Generation %ld}------------", program.get_current_generation());
BLT_TRACE("------------\\{Begin Generation {}}------------", program.get_current_generation());
BLT_TRACE("Creating next generation");
BLT_START_INTERVAL("Symbolic Regression", "Create Next Generation");
program.create_next_generation();
@ -71,7 +72,7 @@ void run(const blt::gp::prog_config_t& config)
BLT_END_INTERVAL("Symbolic Regress", "Evaluate Fitness");
BLT_START_INTERVAL("Symbolic Regress", "Fitness Print");
const auto& stats = program.get_population_stats();
BLT_TRACE("Avg Fit: %lf, Best Fit: %lf, Worst Fit: %lf, Overall Fit: %lf",
BLT_TRACE("Avg Fit: {}, Best Fit: {}, Worst Fit: {}, Overall Fit: {}",
stats.average_fitness.load(std::memory_order_relaxed), stats.best_fitness.load(std::memory_order_relaxed),
stats.worst_fitness.load(std::memory_order_relaxed), stats.overall_fitness.load(std::memory_order_relaxed));
BLT_END_INTERVAL("Symbolic Regress", "Fitness Print");
@ -123,17 +124,8 @@ void do_run()
.set_pop_size(population_sizes)
.set_thread_count(0);
BLT_INFO_STREAM << "Run: Crossover (";
BLT_INFO_STREAM << crossover_chance;
BLT_INFO_STREAM << ") Mutation (";
BLT_INFO_STREAM << mutation_chance;
BLT_INFO_STREAM << ") Reproduction (";
BLT_INFO_STREAM << reproduction_chance;
BLT_INFO_STREAM << ") Elite (";
BLT_INFO_STREAM << elite_amount;
BLT_INFO_STREAM << ") Population Size (";
BLT_INFO_STREAM << population_sizes;
BLT_INFO_STREAM << ")" << "\n";
BLT_INFO("Run: Crossover ({}) Mutation ({}) Reproduction ({}) Elite ({}) Population Size ({})", crossover_chance,
mutation_chance, reproduction_chance, elite_amount, population_sizes);
run(config);
results << "Run: Crossover (";
@ -190,10 +182,10 @@ inline void there(blt::size_t)
int main()
{
// blt::gp::thread_manager_t threads{
// std::thread::hardware_concurrency(), blt::gp::task_builder_t<test>::make_callable(
// blt::gp::task_t{test::hello, hello},
// blt::gp::task_t{test::there, there}
// )
// std::thread::hardware_concurrency(), blt::gp::task_builder_t<test>::make_callable(
// blt::gp::task_t{test::hello, hello},
// blt::gp::task_t{test::there, there}
// )
// };
// threads.add_task(test::hello);
@ -202,7 +194,7 @@ int main()
// threads.add_task(test::there);
// while (threads.has_tasks_left())
// threads.execute();
// threads.execute();
for (int i = 0; i < 1; i++)
do_run();