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Fixes in neural animation example

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This commit is contained in:
Nikita Lisitsa 2021-01-15 22:43:06 +03:00
parent 25e0480805
commit 63e2d226d2
1 changed files with 9 additions and 9 deletions
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18
examples/animation_2d.cpp
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@ -673,7 +673,7 @@ struct animation_2d_app
} mode = mode::train; } mode = mode::train;
std::vector<controller> population; std::vector<controller> population;
std::size_t const population_size = 16; std::size_t const population_size = 256;
std::size_t const max_train_frames = 10.f / physics.dt; std::size_t const max_train_frames = 10.f / physics.dt;
std::size_t const max_train_variations = 1; std::size_t const max_train_variations = 1;
float const position_variation_amplitude = 0.f; float const position_variation_amplitude = 0.f;
@ -683,13 +683,12 @@ struct animation_2d_app
std::size_t const max_train_iterations = 1024*8; std::size_t const max_train_iterations = 1024*8;
float const randomize_amplitude = 10.f; float const randomize_amplitude = 10.f;
static constexpr auto mutation_amplitude = [](float t){ return 10.f * geom::lerp(1.f, 0.01f, t); }; static constexpr auto mutation_amplitude = [](float t){ return 10.f * geom::lerp(1.f, 0.01f, t); };
// static constexpr auto mutation_amplitude = [](float){ return 0.00001f; };
float best_score = 0.f; float best_score = 0.f;
bool const warm_start = false; bool const warm_start = false;
bool const enable_testing = true; bool const enable_testing = true;
bool testing_control = true; bool testing_control = true;
std::string const cache_location = "/home/lisyarus/runner"; std::string const cache_location = "./runner";
std::size_t test_id = 0; std::size_t test_id = 0;
std::vector<float> test_speeds; std::vector<float> test_speeds;
@ -1201,17 +1200,18 @@ void animation_2d_app::do_train()
} }
std::vector<std::pair<float, std::size_t>> scores(population.size()); std::vector<std::pair<float, std::size_t>> scores(population.size());
std::vector<psemek::async::future<void>> futures; std::atomic<std::size_t> finished_count{0};
for (std::size_t i = 0; i < population.size(); ++i) for (std::size_t i = 0; i < population.size(); ++i)
{ {
futures.push_back(bg.dispatch([&, i, rng = rng]() mutable { bg.dispatch([&, i, rng = rng]() mutable {
scores[i] = {eval_score(population[i], rng), i}; scores[i] = {eval_score(population[i], rng), i};
})); ++finished_count;
});
} }
// bg.wait(); bg.wait();
// while (trained.load() != population.size());
bg.wait_all(futures.begin(), futures.end()).get(); if (finished_count.load() != population.size())
throw std::runtime_error("bg.wait() didn't wait for all tasks to finish");
std::sort(scores.begin(), scores.end(), [](auto const & p1, auto const & p2){ return p1.first > p2.first; }); std::sort(scores.begin(), scores.end(), [](auto const & p1, auto const & p2){ return p1.first > p2.first; });