public NNPreTrainedHeuristic(MyNN nnSolve, IRepresentation representationSolve, double?confLevel, bool l2Loss)
{
this.nnSolve = nnSolve;
this.representationSolve = representationSolve;
this.confLevel = confLevel;
this.l2Loss = l2Loss;
}
public NNBayesHeuristic(IRepresentation representationSolve, IRepresentation representationUncert, int numHiddenSolve, int numOutputSolve, int?numHiddenUncert, float dropout, bool l2Loss) : base()
{
this.l2Loss = l2Loss;
this.beta = 0.05F;
float minBeta = 0.00001F;
this.q = 0.95;
this.representationSolve = representationSolve;
this.representationUncert = representationUncert;
nnSolve = new MyNN(new int[] { representationSolve.NumInputs, numHiddenSolve, numOutputSolve }, memoryBufferMaxRecords, l2Loss, dropout);
nnUncert = null;
if (numHiddenUncert != null)
{
nnUncert = new NNBayes(new int[] { representationUncert.NumInputs, (int)numHiddenUncert, 1 });
}
this.confLevel = null;
this.updateBeta = true;
this.betaDiscountFactor = (float)Math.Pow(minBeta / beta, 1F / Global.NITER);
this.reduceUncertFactor = 0.8;
}
public static void TestAdmissibility(int run, string runType, int nnIndex, double?confLevel)
{
string nnFileName = string.Format(Global.NNFN, nnIndex);
string outputFileName = string.Format(Global.TESTADMISFN, confLevel == null ? "" : confLevel.ToString());
string nnLoadPath = string.Format(Global.RUNPATH, run, runType, nnFileName);
string csvWritePath = string.Format(Global.RUNPATH, run, runType, outputFileName);
CSVWriter csvWriter = new CSVWriter(csvWritePath, ',');
MyNN nnSolve = MyNN.Load(nnLoadPath);
TestDomainData[] data = ReadTestDomainData(Global.TESTTASKPATH);
IHeuristic heuristic = new NNPreTrainedHeuristic(nnSolve, representationSolve, confLevel, true);
SolveTestData(heuristic, data, csvWriter, null);
double sumExpanded = 0;
double sumGenerated = 0;
double sumOptimal = 0;
double sumCost = 0;
double sumSubOpt = 0;
for (int i = 0; i < data.Length; i++)
{
TestDomainData testDomainData = data[i];
sumExpanded += testDomainData.SolvedExpanded;
sumGenerated += testDomainData.SolvedGenerated;
sumOptimal += testDomainData.OptimalCost;
sumCost += testDomainData.SolvedCost;
sumSubOpt += testDomainData.SolvedCost / (double)testDomainData.OptimalCost;
}
Console.WriteLine("-----");
Console.WriteLine(sumExpanded / data.Length);
Console.WriteLine(sumGenerated / data.Length);
Console.WriteLine(sumOptimal / data.Length);
Console.WriteLine(sumCost / data.Length);
Console.WriteLine((sumSubOpt / data.Length) - 1);
csvWriter.Write();
}
public static void TestEfficiency(int run, string runType, int nnIndex, TestDomainData[][] testData)
{
string csvWritePath = string.Format(Global.RUNPATH, run, runType, Global.TESTEFFICFN);
string csvSummWritePath = string.Format(Global.RUNPATH, run, runType, Global.TESTEFFICFNSUMM);
CSVWriter csvWriter = new CSVWriter(csvWritePath, ',');
CSVWriter csvSummWriter = new CSVWriter(csvSummWritePath, ',');
int timeout = 60000;
string nnFileName = string.Format(Global.NNFN, nnIndex);
string nnLoadPath = string.Format(Global.RUNPATH, run, runType, nnFileName);
MyNN nnSolve = MyNN.Load(nnLoadPath);
for (int i = 0; i < testData.GetLength(0); i++)
{
csvWriter.Add(i.ToString());
csvWriter.EndLine();
csvWriter.Write();
csvWriter.Clear();
IHeuristic heuristic = new NNPreTrainedHeuristic(nnSolve, representationSolve, null, true);
int numSolved = SolveTestData(heuristic, testData[i], csvWriter, timeout);
csvSummWriter.Add(i.ToString());
csvSummWriter.Add(numSolved.ToString());
csvSummWriter.EndLine();
csvSummWriter.Write();
csvSummWriter.Clear();
}
}
