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Diffstat (limited to 'training/optimize_test.cc')
-rw-r--r-- | training/optimize_test.cc | 118 |
1 files changed, 0 insertions, 118 deletions
diff --git a/training/optimize_test.cc b/training/optimize_test.cc deleted file mode 100644 index bff2ca03..00000000 --- a/training/optimize_test.cc +++ /dev/null @@ -1,118 +0,0 @@ -#include <cassert> -#include <iostream> -#include <sstream> -#include <boost/program_options/variables_map.hpp> -#include "optimize.h" -#include "online_optimizer.h" -#include "sparse_vector.h" -#include "fdict.h" - -using namespace std; - -double TestOptimizer(BatchOptimizer* opt) { - cerr << "TESTING NON-PERSISTENT OPTIMIZER\n"; - - // f(x,y) = 4x1^2 + x1*x2 + x2^2 + x3^2 + 6x3 + 5 - // df/dx1 = 8*x1 + x2 - // df/dx2 = 2*x2 + x1 - // df/dx3 = 2*x3 + 6 - vector<double> x(3); - vector<double> g(3); - x[0] = 8; - x[1] = 8; - x[2] = 8; - double obj = 0; - do { - g[0] = 8 * x[0] + x[1]; - g[1] = 2 * x[1] + x[0]; - g[2] = 2 * x[2] + 6; - obj = 4 * x[0]*x[0] + x[0] * x[1] + x[1]*x[1] + x[2]*x[2] + 6 * x[2] + 5; - opt->Optimize(obj, g, &x); - - cerr << x[0] << " " << x[1] << " " << x[2] << endl; - cerr << " obj=" << obj << "\td/dx1=" << g[0] << " d/dx2=" << g[1] << " d/dx3=" << g[2] << endl; - } while (!opt->HasConverged()); - return obj; -} - -double TestPersistentOptimizer(BatchOptimizer* opt) { - cerr << "\nTESTING PERSISTENT OPTIMIZER\n"; - // f(x,y) = 4x1^2 + x1*x2 + x2^2 + x3^2 + 6x3 + 5 - // df/dx1 = 8*x1 + x2 - // df/dx2 = 2*x2 + x1 - // df/dx3 = 2*x3 + 6 - vector<double> x(3); - vector<double> g(3); - x[0] = 8; - x[1] = 8; - x[2] = 8; - double obj = 0; - string state; - bool converged = false; - while (!converged) { - g[0] = 8 * x[0] + x[1]; - g[1] = 2 * x[1] + x[0]; - g[2] = 2 * x[2] + 6; - obj = 4 * x[0]*x[0] + x[0] * x[1] + x[1]*x[1] + x[2]*x[2] + 6 * x[2] + 5; - - { - if (state.size() > 0) { - istringstream is(state, ios::binary); - opt->Load(&is); - } - opt->Optimize(obj, g, &x); - ostringstream os(ios::binary); opt->Save(&os); state = os.str(); - - } - - cerr << x[0] << " " << x[1] << " " << x[2] << endl; - cerr << " obj=" << obj << "\td/dx1=" << g[0] << " d/dx2=" << g[1] << " d/dx3=" << g[2] << endl; - converged = opt->HasConverged(); - if (!converged) { - // now screw up the state (should be undone by Load) - obj += 2.0; - g[1] = -g[2]; - vector<double> x2 = x; - try { - opt->Optimize(obj, g, &x2); - } catch (...) { } - } - } - return obj; -} - -template <class O> -void TestOptimizerVariants(int num_vars) { - O oa(num_vars); - cerr << "-------------------------------------------------------------------------\n"; - cerr << "TESTING: " << oa.Name() << endl; - double o1 = TestOptimizer(&oa); - O ob(num_vars); - double o2 = TestPersistentOptimizer(&ob); - if (o1 != o2) { - cerr << oa.Name() << " VARIANTS PERFORMED DIFFERENTLY!\n" << o1 << " vs. " << o2 << endl; - exit(1); - } - cerr << oa.Name() << " SUCCESS\n"; -} - -using namespace std::tr1; - -void TestOnline() { - size_t N = 20; - double C = 1.0; - double eta0 = 0.2; - std::tr1::shared_ptr<LearningRateSchedule> r(new ExponentialDecayLearningRate(N, eta0, 0.85)); - //shared_ptr<LearningRateSchedule> r(new StandardLearningRate(N, eta0)); - CumulativeL1OnlineOptimizer opt(r, N, C, std::vector<int>()); - assert(r->eta(10) < r->eta(1)); -} - -int main() { - int n = 3; - TestOptimizerVariants<LBFGSOptimizer>(n); - TestOptimizerVariants<RPropOptimizer>(n); - TestOnline(); - return 0; -} - |