private IDictionary <int, RlmCyclecompleteArgs> RunOneSession(RlmNetwork network, IEnumerable <KeyValuePair <string, Resource> > resourceInputs, bool learn = true, bool showCycleOutput = false)
{
CycleOutputs.Clear();
SessionOutputs.Clear();
IDictionary <int, RlmCyclecompleteArgs> cycleOutputDic = new Dictionary <int, RlmCyclecompleteArgs>();
TrainingVariables["SessionScore"].Value = 0;
long sessId = network.SessionStart();
List <object> outputList = new List <object>();
//TODO: check later for multiple inputs
int min = 0;
int max = 0;
var resIn = resourceInputs.First();
Resource res = resIn.Value;
Dictionary <string, int> inputRange = GetInputRange(res);
min = inputRange["Min"];
max = inputRange["Max"];
bool usedExcludeSolutions = false;
for (int j = min; j <= max; j++)
{
RlmCyclecompleteArgs result;
List <long> excludeSolutions = null;
while (true)
{
//Populate input values
var invs = new List <RlmIOWithValue>();
foreach (var a in network.Inputs)
{
invs.Add(new RlmIOWithValue(a, j.ToString()));
CycleInputs[a.Name] = j;
}
//Build and run a new RlmCycle
var Cycle = new RlmCycle();
result = Cycle.RunCycle(network, sessId, invs, learn, excludeSolutions: excludeSolutions);
//TODO: check later for multiple outputs
var rlmOut = network.Outputs.First();
var value = result.CycleOutput.Outputs.First(b => b.Name == rlmOut.Name).Value;
if (!AllowDuplicates && !learn)
{
bool hasDup = false;
foreach (var rlmOutputs in SessionOutputs)
{
if (rlmOutputs.Value.Any(a => a.ToString() == value))
{
if (excludeSolutions == null)
{
excludeSolutions = new List <long>();
}
excludeSolutions.Add(result.CycleOutput.SolutionID);
hasDup = true;
System.Diagnostics.Debug.WriteLine("Duplicate found!");
break;
}
}
if (hasDup)
{
usedExcludeSolutions = true;
continue;
}
}
//set current rn and sl
cycleOutputDic[j] = result;
CycleOutputs[rlmOut.Name] = value;
outputList.Add(value);
SessionOutputs[rlmOut.Name] = outputList;
break;
}
double cycleScore = ScoreCycle();
if (showCycleOutput)
{
//if (j == min && PredictData.Count() > min)
//{
// PredictData.Clear();
//}
//// exposed cyclescore on predict
//PredictData.Add(cycleScore.ToString());
}
network.ScoreCycle(result.CycleOutput.CycleID, cycleScore);
TrainingVariables["CycleScore"].Value = 0;
}
double sessionScore = ScoreSession();
LastScore = sessionScore;
if (LastScore > HighScore)
{
HighScore = LastScore;
}
network.SessionEnd(sessionScore);
TraceLogObjectsIf(!learn && !usedExcludeSolutions && sessionScore < HighScore, $"{network.DatabaseName}_BestSolutions_InMemory", network.MemoryManager.BestSolutions.SelectMany(a => a.Value.Values));
TraceLog($"Score: {string.Format("{0:n}", sessionScore)}");
// exposed session data
//SessionData.Add(sessionScore.ToString());
return(cycleOutputDic);
}
