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Fb fix pso memory #487

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Fb fix pso memory #487

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d9eb8ee
Keeping PSO variables at memory so that consecutive calls to evolve a…
Oct 5, 2021
e3b6d08
Refactoring: Move memory data to specific struct
Oct 5, 2021
003f435
Add PSO memory object serialization
Oct 6, 2021
e74abb3
Code Review: Replace population size type
Oct 6, 2021
c4ef9bf
Code Review: Header cleanup and build fixes
Oct 7, 2021
091c1f4
Code Review: Move m_V to memory
Oct 7, 2021
462e1c5
Replace broken paper link for genetic operators
Oct 7, 2021
9daa54f
Merge branch 'master' into fb-fix-pso-memory
darioizzo Apr 22, 2022
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16 changes: 15 additions & 1 deletion include/pagmo/algorithms/pso.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -31,6 +31,7 @@ see https://www.gnu.org/licenses/. */

#include <string>
#include <tuple>
#include <type_traits>
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#include <vector>

#include <pagmo/algorithm.hpp>
Expand Down Expand Up @@ -223,6 +224,18 @@ class PAGMO_DLL_PUBLIC pso
}

private:
struct memory {
using population_size_t = decltype(std::declval<population>().size());
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std::vector<vector_double> m_X;
std::vector<vector_double> m_lbX;
std::vector<vector_double> m_fit;
std::vector<vector_double> m_lbfit;
vector_double m_best_fit;
std::vector<std::vector<population_size_t>> m_neighb;
vector_double m_best_neighb;
};

// Object serialization
friend class boost::serialization::access;
template <typename Archive>
Expand Down Expand Up @@ -254,9 +267,10 @@ class PAGMO_DLL_PUBLIC pso
unsigned m_neighb_param;
// memory
bool m_memory;
mutable std::optional<pso::memory> m_memory_data;
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std::optional might be problematic because I don't think it is supported by the Boost.serialization library. If this is indeed the case, replacing it with boost::optional should be straightforward.

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I've changed this to boost::optional, so that I can use #include <boost/serialization/optional.hpp>. Worked as expected :)


// paricles' velocities
mutable std::vector<vector_double> m_V;
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mutable detail::random_engine_type m_e;
unsigned m_seed;
unsigned m_verbosity;
Expand Down
64 changes: 43 additions & 21 deletions src/algorithms/pso.cpp
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Expand Up @@ -179,12 +179,22 @@ population pso::evolve(population pop) const
}

// Copy the particle positions and their fitness
for (decltype(swarm_size) i = 0u; i < swarm_size; ++i) {
X[i] = pop.get_x()[i];
lbX[i] = pop.get_x()[i];
// If calling from memory, the positions from last run may not be the same as the best population
// so it is make a correction here
if (m_memory && m_memory_data) {
X = m_memory_data->m_X;
lbX = m_memory_data->m_lbX;

fit = m_memory_data->m_fit;
lbfit = m_memory_data->m_lbfit;
} else {
for (decltype(swarm_size) i = 0u; i < swarm_size; ++i) {
X[i] = pop.get_x()[i];
lbX[i] = pop.get_x()[i];

fit[i] = pop.get_f()[i];
lbfit[i] = pop.get_f()[i];
fit[i] = pop.get_f()[i];
lbfit[i] = pop.get_f()[i];
}
}

// Initialize the particle velocities if necessary
Expand All @@ -198,25 +208,31 @@ population pso::evolve(population pop) const
}

// Initialize the Swarm's topology
switch (m_neighb_type) {
case 1:
initialize_topology__gbest(pop, best_neighb, best_fit, neighb);
break;
case 3:
initialize_topology__von(neighb);
break;
case 4:
initialize_topology__adaptive_random(neighb);
// need to track improvements in best found fitness, to know when to rewire
best_fit = pop.get_f()[pop.best_idx()];
break;
case 2:
default:
initialize_topology__lbest(neighb);
if (m_memory && m_memory_data) {
neighb = m_memory_data->m_neighb;
best_fit = m_memory_data->m_best_fit;
best_neighb = m_memory_data->m_best_neighb;
} else {
switch (m_neighb_type) {
case 1:
initialize_topology__gbest(pop, best_neighb, best_fit, neighb);
break;
case 3:
initialize_topology__von(neighb);
break;
case 4:
initialize_topology__adaptive_random(neighb);
// need to track improvements in best found fitness, to know when to rewire
best_fit = pop.get_f()[pop.best_idx()];
break;
case 2:
default:
initialize_topology__lbest(neighb);
}
}
// auxiliary variables specific to the Fully Informed Particle Swarm variant
double acceleration_coefficient = m_eta1 + m_eta2;
double sum_forces;
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double sum_forces = 0.;

double r1 = 0.;
double r2 = 0.;
Expand Down Expand Up @@ -439,6 +455,12 @@ population pso::evolve(population pop) const
for (decltype(swarm_size) i = 0u; i < swarm_size; ++i) {
pop.set_xf(i, lbX[i], lbfit[i]);
}

// Keep memory variables only if asked for
if (m_memory) {
m_memory_data = pso::memory{X, lbX, fit, lbfit, best_fit, neighb, best_neighb};
}

return pop;
}

Expand Down
52 changes: 52 additions & 0 deletions tests/pso.cpp
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Expand Up @@ -134,6 +134,7 @@ BOOST_AUTO_TEST_CASE(evolve_test)
}
}
}

BOOST_AUTO_TEST_CASE(setters_getters_test)
{
pso user_algo{5000u, 0.79, 2., 2., 0.1, 5u, 2u, 4u, false, 23u};
Expand Down Expand Up @@ -184,3 +185,54 @@ BOOST_AUTO_TEST_CASE(serialization_test)
BOOST_CHECK_CLOSE(std::get<5>(before_log[i]), std::get<5>(after_log[i]), 1e-8);
}
}

BOOST_AUTO_TEST_CASE(pso_memory_test)
{
// We check here that when memory is true calling evolve(pop) two times on 1 gen
// is the same as calling 1 time evolve with 2 gens
auto omega = 0.5d;
auto eta1 = 0.5d;
auto eta2 = 0.5d;
auto max_vel = 0.5d;
auto neighb_param = 4u;
auto seed = 42u;
auto pop_size = 10u;

for (auto variant = 1u; variant <= 6; ++variant) {
for (auto neighb_type = 1u; neighb_type <= 4; ++neighb_type) {
auto log1 = ([&]() {
auto n_generations = 1u;
auto memory = true;
pso user_algo{n_generations, omega, eta1, eta2, max_vel, variant, neighb_type, neighb_param, memory, seed};
user_algo.set_verbosity(1u);
problem prob{rosenbrock{25u}};
population pop{prob, pop_size, seed};
pop = user_algo.evolve(pop);
pop = user_algo.evolve(pop);
pop = user_algo.evolve(pop);
return user_algo.get_log();
})();

auto log2 = ([&]() {
auto n_generations = 3u;
auto memory = false;
pso user_algo{n_generations, omega, eta1, eta2, max_vel, variant, neighb_type, neighb_param, memory, seed};
user_algo.set_verbosity(1u);
problem prob{rosenbrock{25u}};
population pop{prob, pop_size, seed};
pop = user_algo.evolve(pop);
return user_algo.get_log();
})();

// indexes 0 (Gen) and 1 (Fevals) may be different
// Check index 2 (gbest)
BOOST_CHECK_CLOSE(std::get<2>(log1[0]), std::get<2>(log2[2]), 1e-8);
// Check index 3 (Mean Vel.)
BOOST_CHECK_CLOSE(std::get<3>(log1[0]), std::get<3>(log2[2]), 1e-8);
// Check index 4 (Mean lbest)
BOOST_CHECK_CLOSE(std::get<4>(log1[0]), std::get<4>(log2[2]), 1e-8);
// Check index 5 (Avg. Dist.)
BOOST_CHECK_CLOSE(std::get<5>(log1[0]), std::get<5>(log2[2]), 1e-8);
}
}
}