public void Start(TrainingOptions options)
{
if (state == SessionState.Stopped)
{
History.Add("Training Starting", status, options);
string[] inputColumns = AdaptiveSystem.Interface.GetNames(InputOutput.Input);
string[] outputColumns = AdaptiveSystem.Interface.GetNames(InputOutput.Output);
object dataInput = DataSource.GetData(inputColumns, DataSourceSet.Training);
object dataOutput = DataSource.GetData(outputColumns, DataSourceSet.Training);
AdaptiveSystem.Preprocess.Apply(dataInput);
AdaptiveSystem.Postprocess.Reverse(dataOutput);
TrainingThreadParameters parameters = new TrainingThreadParameters();
parameters.Options = this.Options.Copy();
//parameters.Inputs = convert(dataInput);
//parameters.Outputs = convert(dataOutput);
backgroundWorker.RunWorkerAsync(parameters);
}
else if (state == SessionState.Paused)
{
History.Add("Training Resumed", status);
state = SessionState.Running;
}
}
private void backgroundWorker_DoWork(object sender, DoWorkEventArgs e)
{
TrainingThreadParameters parameters = (TrainingThreadParameters)e.Argument;
TrainingOptions options = parameters.Options;
double[][] inputs = parameters.Inputs;
double[][] outputs = parameters.Outputs;
//Create Teacher
BackPropagationLearning networkTeacher = new BackPropagationLearning(activationNetwork);
networkTeacher.LearningRate = options.LearningRate1;
networkTeacher.Momentum = options.Momentum;
//Start Training
bool stop = false;
bool complete = false;
int lastStatusEpoch = 0;
int lastSaveEpoch = 0;
int lastValidateEpoch = 0;
backgroundWorker.ReportProgress(0, BackgroundWorkerUpdate.Starting);
#region Main Training Loop
while (!stop)
{
// Run training epoch
status.TrainingError = networkTeacher.RunEpoch(inputs, outputs);
if (options.Validate && status.Epoch >= lastValidateEpoch + options.ValidateEpochs)
{
status.ValidationError = networkTeacher.MeasureEpochError(inputs, outputs);
}
// Adjust Training Rate
if (options.ChangeLearningRate)
{
networkTeacher.LearningRate = options.LearningRate2;
}
// Register Savepoint
if (options.MarkSavepoints &&
status.Epoch >= lastSaveEpoch + options.MarkSavepointsEpochs)
{
backgroundWorker.ReportProgress(0, BackgroundWorkerUpdate.NetworkSave);
lastSaveEpoch = status.Epoch;
}
// Progress Indicator
if (options.ReportProgress &&
status.Epoch >= lastStatusEpoch + options.ReportProgressEpochs)
{
if (options.Limit == TrainingOptions.TrainingLimit.ByError)
{
if (status.TrainingError != 0) // Check to avoid division by zero
{
status.Progress = Math.Max(Math.Min((int)((options.LimitByError * 100) / status.TrainingError), 100), 0);
}
}
else if (options.Limit == TrainingOptions.TrainingLimit.ByEpoch)
{
if (status.Epoch != 0) // Check to avoid division by zero
{
status.Progress = Math.Max(Math.Min((int)((status.Epoch * 100) / options.LimitByEpochs), 100), 0);
}
}
backgroundWorker.ReportProgress(0, BackgroundWorkerUpdate.Progress);
lastStatusEpoch = status.Epoch;
}
// Increment epoch counter
++status.Epoch;
if (options.Delay)
{
// Sleep thread according to specified delay
System.Threading.Thread.Sleep(options.DelayMilliseconds);
}
// Check stop conditions
if ((options.Limit == TrainingOptions.TrainingLimit.ByError &&
status.TrainingError <= options.LimitByError) ||
(options.Limit == TrainingOptions.TrainingLimit.ByEpoch &&
status.Epoch >= options.LimitByEpochs))
{
complete = true;
stop = true;
}
// Check for cancellation requests
if (backgroundWorker.CancellationPending)
{
e.Cancel = true;
stop = true;
}
while (state == SessionState.Paused)
{
System.Threading.Thread.Sleep(1000);
}
} // End main training loop
#endregion
// Do a last update before exiting the thread
if (complete)
{
backgroundWorker.ReportProgress(0, BackgroundWorkerUpdate.Completed);
}
else
{
backgroundWorker.ReportProgress(0, BackgroundWorkerUpdate.Progress);
}
}