3 #include "searchtuner.h"
8 AutoTuner::AutoTuner(uint _budget) :
12 void AutoTuner::addProblem(CSolver *solver) {
16 long long AutoTuner::evaluate(CSolver * problem, SearchTuner *tuner) {
17 CSolver * copy=problem->clone();
18 copy->setTuner(tuner);
19 int result = copy->startEncoding();
20 long long elapsedTime=copy->getElapsedTime();
21 long long encodeTime=copy->getEncodeTime();
22 long long solveTime=copy->getSolveTime();
23 long long metric=elapsedTime;
24 model_print("Elapsed Time: %llu\n", elapsedTime);
25 model_print("Encode Time: %llu\n", encodeTime);
26 model_print("Solve Time: %llu\n", solveTime);
31 double AutoTuner::evaluateAll(SearchTuner *tuner) {
33 for(uint i=0;i<solvers.getSize();i++) {
34 CSolver * problem=solvers.get(i);
35 double score=evaluate(problem, tuner);
38 return pow(product, 1/((double)solvers.getSize()));
41 SearchTuner * AutoTuner::mutateTuner(SearchTuner * oldTuner, uint k) {
42 SearchTuner *newTuner=oldTuner->copyUsed();
43 uint numSettings=oldTuner->getSize();
44 double factor=0.3;//Adjust this factor...
45 uint settingsToMutate=(uint)(factor*(((double)numSettings) * (budget - k))/(budget));
46 if (settingsToMutate < 1)
48 model_print("Mutating %u settings\n", settingsToMutate);
49 while(settingsToMutate-- != 0) {
50 newTuner->randomMutate();
56 void AutoTuner::tune() {
57 SearchTuner * bestTuner = NULL;
58 double bestScore=DBL_MAX;
60 SearchTuner * oldTuner=new SearchTuner();
61 double base_temperature=evaluateAll(oldTuner);
62 double oldScore=base_temperature;
64 for (uint i=0;i<budget;i++) {
65 SearchTuner *newTuner=mutateTuner(oldTuner, i);
66 double newScore=evaluateAll(newTuner);
67 newTuner->printUsed();
68 model_print("Received score %f\n", newScore);
69 double scoreDiff=newScore - oldScore; //smaller is better
70 if (newScore < bestScore) {
71 if (bestTuner != NULL)
74 bestTuner = newTuner->copyUsed();
81 double currTemp=base_temperature * (((double)budget - i) / budget);
82 acceptanceP = exp(-scoreDiff / currTemp);
84 double ran = ((double)random()) / RAND_MAX;
85 if (ran <= acceptanceP) {
93 model_print("Best tuner:\n");
95 model_print("Received score %f\n", bestScore);
96 if (bestTuner != NULL)