void TrainLoop()
{
int[] inputs = new int[_network.InputLength];
int output = _rand.Next() % _network.OutputLength;
for (int i = 0; i < inputs.Length; i++)
{
inputs [i] = _rand.Next() % 100;
}
inputs[0] = _rand.Next() % 2;
if (inputs [0] > 0.5)
{
output = 0;
}
_network.Train(inputs, output, null, 0.005f);
_loopsCount++;
CompositionRoot.Instance.ExecuteInMainThread(() => {
_loopsCountLabel.text = _loopsCount.ToString();
});
}
public void OnToggleTrainPressed()
{
_isTraining = !_isTraining;
if (!_isTraining)
{
return;
}
// Train thread.
Thread thread = new Thread(new ThreadStart(() => {
while (_isTraining)
{
TrainingDecisionModel currTraining = _trainingModels[_trainingsCount % _trainingModels.Count];
float currSpeed = 0.0005f; //*currTraining.RewardPercent*0.01f;
_decider.Train(currTraining.Inputs, currTraining.Output, currTraining.Options, currSpeed);
_trainingsCount++;
CompositionRoot.Instance.ExecuteInMainThread(() => {
_performedTrainingsCount.text = _trainingsCount.ToString();
});
}
}));
thread.Start();
// Calc success thread.
Thread thread2 = new Thread(new ThreadStart(() => {
while (_isTraining)
{
float error = GetError();
System.Threading.Thread.Sleep(300);
CompositionRoot.Instance.ExecuteInMainThread(() => {
_error.text = error.ToString("00.0000");
Debug.Log("success updated, success = " + error.ToString());
});
}
}));
thread2.Start();
}
