[yul-phaser] Population: Evaluate fitness immediately when an individual is added or modified

- This removes the explicit evaluation phase.
- Fitness is no longer optional in Individual
This commit is contained in:
cameel 2020-02-05 16:18:53 +01:00 committed by Kamil Śliwak
parent 66fdc1c374
commit 76842ac3fd
3 changed files with 32 additions and 64 deletions

View File

@ -42,19 +42,6 @@ using namespace boost::unit_test::framework;
namespace solidity::phaser::test
{
namespace
{
bool fitnessNotSet(Individual const& individual)
{
return !individual.fitness.has_value();
}
bool fitnessSet(Individual const& individual)
{
return individual.fitness.has_value();
}
}
class PopulationFixture
{
protected:
@ -94,7 +81,7 @@ BOOST_AUTO_TEST_CASE(isFitter_should_return_false_for_identical_individuals)
BOOST_TEST(!isFitter(Individual{Chromosome("acT"), 0}, Individual{Chromosome("acT"), 0}));
}
BOOST_FIXTURE_TEST_CASE(constructor_should_copy_chromosomes_and_not_compute_fitness, PopulationFixture)
BOOST_FIXTURE_TEST_CASE(constructor_should_copy_chromosomes_and_compute_fitness, PopulationFixture)
{
vector<Chromosome> chromosomes = {
Chromosome::makeRandom(5),
@ -106,8 +93,8 @@ BOOST_FIXTURE_TEST_CASE(constructor_should_copy_chromosomes_and_not_compute_fitn
BOOST_TEST(population.individuals()[0].chromosome == chromosomes[0]);
BOOST_TEST(population.individuals()[1].chromosome == chromosomes[1]);
auto fitnessNotSet = [](auto const& individual){ return !individual.fitness.has_value(); };
BOOST_TEST(all_of(population.individuals().begin(), population.individuals().end(), fitnessNotSet));
BOOST_TEST(population.individuals()[0].fitness == m_fitnessMetric->evaluate(population.individuals()[0].chromosome));
BOOST_TEST(population.individuals()[1].fitness == m_fitnessMetric->evaluate(population.individuals()[1].chromosome));
}
BOOST_FIXTURE_TEST_CASE(makeRandom_should_get_chromosome_lengths_from_specified_generator, PopulationFixture)
@ -181,22 +168,13 @@ BOOST_FIXTURE_TEST_CASE(makeRandom_should_return_population_with_random_chromoso
BOOST_TEST(abs(meanSquaredError(samples, expectedValue) - variance) < variance * relativeTolerance);
}
BOOST_FIXTURE_TEST_CASE(makeRandom_should_not_compute_fitness, PopulationFixture)
BOOST_FIXTURE_TEST_CASE(makeRandom_should_compute_fitness, PopulationFixture)
{
auto population = Population::makeRandom(m_fitnessMetric, 3, 5, 10);
BOOST_TEST(all_of(population.individuals().begin(), population.individuals().end(), fitnessNotSet));
}
BOOST_FIXTURE_TEST_CASE(run_should_evaluate_fitness, PopulationFixture)
{
stringstream output;
auto population = Population::makeRandom(m_fitnessMetric, 5, 5, 10);
assert(all_of(population.individuals().begin(), population.individuals().end(), fitnessNotSet));
population.run(1, output);
BOOST_TEST(all_of(population.individuals().begin(), population.individuals().end(), fitnessSet));
BOOST_TEST(population.individuals()[0].fitness == m_fitnessMetric->evaluate(population.individuals()[0].chromosome));
BOOST_TEST(population.individuals()[1].fitness == m_fitnessMetric->evaluate(population.individuals()[1].chromosome));
BOOST_TEST(population.individuals()[2].fitness == m_fitnessMetric->evaluate(population.individuals()[2].chromosome));
}
BOOST_FIXTURE_TEST_CASE(run_should_not_make_fitness_of_top_chromosomes_worse, PopulationFixture)
@ -220,12 +198,10 @@ BOOST_FIXTURE_TEST_CASE(run_should_not_make_fitness_of_top_chromosomes_worse, Po
{
population.run(1, output);
BOOST_TEST(population.individuals().size() == 5);
BOOST_TEST(fitnessSet(population.individuals()[0]));
BOOST_TEST(fitnessSet(population.individuals()[1]));
size_t currentTopFitness[2] = {
population.individuals()[0].fitness.value(),
population.individuals()[1].fitness.value(),
population.individuals()[0].fitness,
population.individuals()[1].fitness,
};
BOOST_TEST(currentTopFitness[0] <= initialTopFitness[0]);
BOOST_TEST(currentTopFitness[1] <= initialTopFitness[1]);

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@ -41,11 +41,7 @@ ostream& operator<<(ostream& _stream, Population const& _population);
ostream& phaser::operator<<(ostream& _stream, Individual const& _individual)
{
_stream << "Fitness: ";
if (_individual.fitness.has_value())
_stream << _individual.fitness.value();
else
_stream << "<NONE>";
_stream << "Fitness: " << _individual.fitness;
_stream << ", optimisations: " << _individual.chromosome;
return _stream;
@ -53,12 +49,10 @@ ostream& phaser::operator<<(ostream& _stream, Individual const& _individual)
bool phaser::isFitter(Individual const& a, Individual const& b)
{
assert(a.fitness.has_value() && b.fitness.has_value());
return (
(a.fitness.value() < b.fitness.value()) ||
(a.fitness.value() == b.fitness.value() && a.chromosome.length() < b.chromosome.length()) ||
(a.fitness.value() == b.fitness.value() && a.chromosome.length() == b.chromosome.length() && toString(a.chromosome) < toString(b.chromosome))
(a.fitness < b.fitness) ||
(a.fitness == b.fitness && a.chromosome.length() < b.chromosome.length()) ||
(a.fitness == b.fitness && a.chromosome.length() == b.chromosome.length() && toString(a.chromosome) < toString(b.chromosome))
);
}
@ -68,11 +62,11 @@ Population Population::makeRandom(
function<size_t()> _chromosomeLengthGenerator
)
{
vector<Individual> individuals;
vector<Chromosome> chromosomes;
for (size_t i = 0; i < _size; ++i)
individuals.push_back({Chromosome::makeRandom(_chromosomeLengthGenerator())});
chromosomes.push_back(Chromosome::makeRandom(_chromosomeLengthGenerator()));
return Population(move(_fitnessMetric), move(individuals));
return Population(move(_fitnessMetric), move(chromosomes));
}
Population Population::makeRandom(
@ -91,12 +85,10 @@ Population Population::makeRandom(
void Population::run(optional<size_t> _numRounds, ostream& _outputStream)
{
doEvaluation();
for (size_t round = 0; !_numRounds.has_value() || round < _numRounds.value(); ++round)
{
doMutation();
doSelection();
doEvaluation();
_outputStream << "---------- ROUND " << round << " ----------" << endl;
_outputStream << *this;
@ -134,20 +126,14 @@ void Population::doMutation()
// TODO: Implement mutation and crossover
}
void Population::doEvaluation()
{
for (auto& individual: m_individuals)
if (!individual.fitness.has_value())
individual.fitness = m_fitnessMetric->evaluate(individual.chromosome);
}
void Population::doSelection()
{
m_individuals = sortedIndividuals(move(m_individuals));
randomizeWorstChromosomes(m_individuals, m_individuals.size() / 2);
randomizeWorstChromosomes(*m_fitnessMetric, m_individuals, m_individuals.size() / 2);
}
void Population::randomizeWorstChromosomes(
FitnessMetric const& _fitnessMetric,
vector<Individual>& _individuals,
size_t _count
)
@ -158,25 +144,29 @@ void Population::randomizeWorstChromosomes(
auto individual = _individuals.begin() + (_individuals.size() - _count);
for (; individual != _individuals.end(); ++individual)
{
*individual = {Chromosome::makeRandom(binomialChromosomeLength(MaxChromosomeLength))};
auto chromosome = Chromosome::makeRandom(binomialChromosomeLength(MaxChromosomeLength));
size_t fitness = _fitnessMetric.evaluate(chromosome);
*individual = {move(chromosome), fitness};
}
}
vector<Individual> Population::chromosomesToIndividuals(
FitnessMetric const& _fitnessMetric,
vector<Chromosome> _chromosomes
)
{
vector<Individual> individuals;
for (auto& chromosome: _chromosomes)
individuals.push_back({move(chromosome)});
{
size_t fitness = _fitnessMetric.evaluate(chromosome);
individuals.push_back({move(chromosome), fitness});
}
return individuals;
}
vector<Individual> Population::sortedIndividuals(vector<Individual> _individuals)
{
assert(all_of(_individuals.begin(), _individuals.end(), [](auto& i){ return i.fitness.has_value(); }));
sort(_individuals.begin(), _individuals.end(), isFitter);
return _individuals;
}

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@ -46,7 +46,7 @@ namespace solidity::phaser
struct Individual
{
Chromosome chromosome;
std::optional<size_t> fitness = std::nullopt;
size_t fitness;
bool operator==(Individual const& _other) const { return fitness == _other.fitness && chromosome == _other.chromosome; }
bool operator!=(Individual const& _other) const { return !(*this == _other); }
@ -67,6 +67,7 @@ bool isFitter(Individual const& a, Individual const& b);
* An individual is a sequence of optimiser steps represented by a @a Chromosome instance.
* Individuals are stored together with a fitness value that can be computed by the fitness metric
* associated with the population.
* The fitness is computed using the metric as soon as an individual is inserted into the population.
*/
class Population
{
@ -78,8 +79,8 @@ public:
std::vector<Chromosome> _chromosomes = {}
):
Population(
std::move(_fitnessMetric),
chromosomesToIndividuals(std::move(_chromosomes))
_fitnessMetric,
chromosomesToIndividuals(*_fitnessMetric, std::move(_chromosomes))
) {}
static Population makeRandom(
@ -114,14 +115,15 @@ private:
m_individuals{std::move(_individuals)} {}
void doMutation();
void doEvaluation();
void doSelection();
static void randomizeWorstChromosomes(
FitnessMetric const& _fitnessMetric,
std::vector<Individual>& _individuals,
size_t _count
);
static std::vector<Individual> chromosomesToIndividuals(
FitnessMetric const& _fitnessMetric,
std::vector<Chromosome> _chromosomes
);
static std::vector<Individual> sortedIndividuals(std::vector<Individual> _individuals);