public void OnTrainNeuralNetwork()
{
if (LocalImageCollection.Count == 0)
{
MessageBox.Show("Немає зображень в локальному списку для тестування!", "Додайте зображення");
return;
}
this.GraphData.ClearDataCollection();
trainingTaskCancellationToken = new CancellationTokenSource();
trainingTaskCancellationToken.Token.Register(() =>
{
});
if (NeuralNetwork == null)
{
MessageBox.Show("Нейронна мережа несумісна", "Помилка нейронної мережі");
return;
}
UpdateParametersFromNeuralNetwork();
this.TrainingNeuralNetwork = true;
var trainingProgressMessage = "Тренування в прогресі. Будь ласка, зачекайте... ";
Task task = new Task(() => {
App.Current.Dispatcher.Invoke(() =>
{
this.StatusMessage = trainingProgressMessage;
this.TrainingNeuralNetwork = true;
foreach (var localImage in LocalImageCollection)
{
localImage.TrainingInProgress = true;
localImage.TestFailed = false;
localImage.TestPassed = false;
}
});
var imagesOnEachPage = NeuralNetwork.GetBatchSubSize();
var totalPages = (int)Math.Ceiling((double)LocalImageCollection.Count / (double)imagesOnEachPage);
foreach (var mainIteration in Enumerable.Range(1, MaxIterations))
{
double avrageIterationError = 0;
App.Current.Dispatcher.Invoke(() =>
{
Randomizer.Shuffle(LocalImageCollection);
});
foreach (var currentPage in Enumerable.Range(1, totalPages))
{
double averagePageError = 0;
var currentPageImages = LocalImageCollection.ToPagedList(currentPage, imagesOnEachPage);
(var batchInputs, var batchOutputs) = GetBatchDataFromImages(currentPageImages);
int batchTrainCounter = 0;
NeuralNetwork.BatchTrain(batchInputs, batchOutputs, MaxIterationsOnEachPage, (currentError, pageIteration, message) => {
this.StatusMessage = $"{trainingProgressMessage} Повідомлення: {message}; Ітерація: {mainIteration}; Сторінка: {currentPage}/{totalPages}; Ітерація сторінки: {pageIteration}; Помилка: {currentError}";
foreach (var localImage in currentPageImages)
{
localImage.TrainedIterations = (pageIteration) * (mainIteration);
localImage.TrainingInProgress = true;
}
if (currentError <= StopPageTrainingErrorRate || pageIteration > MaxIterationsOnEachPage)
{
NeuralNetwork.StopBatchTraining();
}
GraphData.AddDataPoint(currentError);
averagePageError += currentError;
batchTrainCounter++;
});
averagePageError /= (double)batchTrainCounter;
GraphData.AddPageChanged();
avrageIterationError += averagePageError;
GC.Collect();
}
GraphData.AddIterationChanged();
avrageIterationError /= totalPages;
if (avrageIterationError < StopIterationTrainingErrorRate)
{
break;
}
}
App.Current.Dispatcher.Invoke(() =>
{
this.StatusMessage = trainingProgressMessage;
});
}, trainingTaskCancellationToken.Token);
task.Start();
task.ContinueWith((t) => {
App.Current.Dispatcher.Invoke(() =>
{
this.StatusMessage = "Готово";
this.TrainingNeuralNetwork = false;
foreach (var localImage in LocalImageCollection)
{
localImage.TrainingInProgress = false;
}
});
});
}
public void OnTrainNeuralNetwork()
{
if (LocalImageCollection.Count == 0)
{
MessageBox.Show("No Images in Local Image List to Train With!", "Add Local Images");
return;
}
this.GraphData.ClearDataCollection();
trainingTaskCancellationToken = new CancellationTokenSource();
trainingTaskCancellationToken.Token.Register(() =>
{
});
if (NeuralNetwork == null)
{
MessageBox.Show("Neural Network Incompatible", "Error in Neural Network");
return;
}
UpdateParametersFromNeuralNetwork();
this.TrainingNeuralNetwork = true;
var trainingProgressMessage = "Training in Progress. Please Wait... ";
Task task = new Task(() => {
App.Current.Dispatcher.Invoke(() =>
{
this.StatusMessage = trainingProgressMessage;
this.TrainingNeuralNetwork = true;
foreach (var localImage in LocalImageCollection)
{
localImage.TrainingInProgress = true;
localImage.TestFailed = false;
localImage.TestPassed = false;
}
});
var imagesOnEachPage = NeuralNetwork.GetBatchSubSize();
var totalPages = (int)Math.Ceiling((double)LocalImageCollection.Count / (double)imagesOnEachPage);
foreach (var mainIteration in Enumerable.Range(1, MaxIterations))
{
double avrageIterationError = 0;
App.Current.Dispatcher.Invoke(() =>
{
Randomizer.Shuffle(LocalImageCollection);
});
foreach (var currentPage in Enumerable.Range(1, totalPages))
{
double averagePageError = 0;
var currentPageImages = LocalImageCollection.ToPagedList(currentPage, imagesOnEachPage);
(var batchInputs, var batchOutputs) = GetBatchDataFromImages(currentPageImages);
int batchTrainCounter = 0;
NeuralNetwork.BatchTrain(batchInputs, batchOutputs, MaxIterationsOnEachPage, (currentError, pageIteration, message) => {
this.StatusMessage = $"{trainingProgressMessage} Message: {message}; Iteration: {mainIteration}; Page: {currentPage}/{totalPages}; Page Iteration: {pageIteration}; Error: {currentError}";
foreach (var localImage in currentPageImages)
{
localImage.TrainedIterations = (pageIteration) * (mainIteration);
localImage.TrainingInProgress = true;
}
if (currentError <= StopPageTrainingErrorRate || pageIteration > MaxIterationsOnEachPage)
{
NeuralNetwork.StopBatchTraining();
}
GraphData.AddDataPoint(currentError);
averagePageError += currentError;
batchTrainCounter++;
});
averagePageError /= (double)batchTrainCounter;
GraphData.AddPageChanged();
avrageIterationError += averagePageError;
GC.Collect();
}
GraphData.AddIterationChanged();
avrageIterationError /= totalPages;
if (avrageIterationError < StopIterationTrainingErrorRate)
{
break;
}
}
App.Current.Dispatcher.Invoke(() =>
{
this.StatusMessage = trainingProgressMessage;
});
}, trainingTaskCancellationToken.Token);
task.Start();
task.ContinueWith((t) => {
App.Current.Dispatcher.Invoke(() =>
{
this.StatusMessage = "Ready";
this.TrainingNeuralNetwork = false;
foreach (var localImage in LocalImageCollection)
{
localImage.TrainingInProgress = false;
}
});
});
}