void MainLogic::update()
{
if(DataMgr->m_isActive)
{
CLayer::update();
charUpdate();
bulletUpdate();
itemUpdate();
boxUpdate();
//플래그 업데이트
FlagOn();
if(m_pPlayer->getPos().x > 600)
setPos(ccp(-m_pPlayer->getPos().x + 600, getPos().y));
DataMgr->stageUpdate();
}
}
inline double ParallelSGD<ExponentialBackoff>::Optimize(
mlpack::svd::RegularizedSVDFunction<arma::mat>& function,
arma::mat& iterate)
{
double overallObjective = DBL_MAX;
double lastObjective;
// The order in which the functions will be visited.
arma::Col<size_t> visitationOrder = arma::linspace<arma::Col<size_t>>(0,
(function.NumFunctions() - 1), function.NumFunctions());
const arma::mat data = function.Dataset();
// Iterate till the objective is within tolerance or the maximum number of
// allowed iterations is reached. If maxIterations is 0, this will iterate
// till convergence.
for (size_t i = 1; i != maxIterations; ++i)
{
// Calculate the overall objective.
lastObjective = overallObjective;
overallObjective = 0;
#pragma omp parallel for reduction(+:overallObjective)
for (omp_size_t j = 0; j < (omp_size_t) function.NumFunctions(); ++j)
{
overallObjective += function.Evaluate(iterate, j);
}
// Output current objective function.
mlpack::Log::Info << "Parallel SGD: iteration " << i << ", objective "
<< overallObjective << "." << std::endl;
if (std::isnan(overallObjective) || std::isinf(overallObjective))
{
mlpack::Log::Warn << "Parallel SGD: converged to " << overallObjective
<< "; terminating with failure. Try a smaller step size?"
<< std::endl;
return overallObjective;
}
if (std::abs(lastObjective - overallObjective) < tolerance)
{
mlpack::Log::Info << "SGD: minimized within tolerance " << tolerance
<< "; terminating optimization." << std::endl;
return overallObjective;
}
// Get the stepsize for this iteration
double stepSize = decayPolicy.StepSize(i);
if (shuffle) // Determine order of visitation.
std::shuffle(visitationOrder.begin(), visitationOrder.end(),
mlpack::math::randGen);
#pragma omp parallel
{
// Each processor gets a subset of the instances.
// Each subset is of size threadShareSize.
size_t threadId = 0;
#ifdef HAS_OPENMP
threadId = omp_get_thread_num();
#endif
for (size_t j = threadId * threadShareSize;
j < (threadId + 1) * threadShareSize && j < visitationOrder.n_elem;
++j)
{
const size_t numUsers = function.NumUsers();
// Indices for accessing the the correct parameter columns.
const size_t user = data(0, visitationOrder[j]);
const size_t item = data(1, visitationOrder[j]) + numUsers;
// Prediction error for the example.
const double rating = data(2, visitationOrder[j]);
double ratingError = rating - arma::dot(iterate.col(user),
iterate.col(item));
double lambda = function.Lambda();
arma::mat userUpdate = stepSize * (lambda * iterate.col(user) -
ratingError * iterate.col(item));
arma::mat itemUpdate = stepSize * (lambda * iterate.col(item) -
ratingError * iterate.col(user));
// Gradient is non-zero only for the parameter columns corresponding to
// the example.
for (size_t i = 0; i < iterate.n_rows; ++i)
{
#pragma omp atomic
iterate(i, user) -= userUpdate(i);
#pragma omp atomic
iterate(i, item) -= itemUpdate(i);
}
}
}
}
mlpack::Log::Info << "\n Parallel SGD terminated with objective : "
<< overallObjective << std::endl;
return overallObjective;
}
