void runThread(object o)
{
stopWatch = new Stopwatch();
stopWatch.Start();
Job currentJob;
epochHandler = new NeuronDotNet.Core.TrainingEpochEventHandler(Network_EndEpochEvent);
// Thread.CurrentThread.Name = o.ToString();
while (Thread.CurrentThread.IsAlive)
{
//Thread.CurrentThread.Name = o.ToString();
Job job = null;
lock (jobs)
{
if (jobs.Count > 0)
{
job = jobs.Dequeue();
}
Utils.Logger.Log("Jobs left: {0}", jobs.Count);
}
if (job == null)
{
changeThreadProgress(Int32.Parse(Thread.CurrentThread.Name), -1, -1, "No more jobs!");
return;
}
currentJob = job;
Optimiser optimiser = new Optimiser(job.Filename);
optimiser.Network.EndEpochEvent += epochHandler;
double mes = 1;
mes = optimiser.Optimise();
optimiser.Network.EndEpochEvent -= epochHandler;
}
changeThreadProgress(Int32.Parse(Thread.CurrentThread.Name), -1, -1, "No more jobs!");
}
private static void runThread(object o)
{
Job currentJob;
// Thread.CurrentThread.Name = o.ToString();
while (Thread.CurrentThread.IsAlive)
{
//Thread.CurrentThread.Name = o.ToString();
Job job = null;
lock (jobs)
{
if (jobs.Count > 0)
{
job = jobs.Dequeue();
}
}
if (job == null)
{
Utils.Logger.Log("Jobs done!");
return;
}
currentJob = job;
Utils.Logger.Log("Optimising job: " + job.Filename);
Optimiser optimiser = new Optimiser(job.Filename);
double mes = 1;
mes = optimiser.Optimise();
}
}