public TrainAndTestPage(NeuralNetRunType runtype, NeuralNet neuralnet, MNISTDataManager mnistdata)
{
// Define GUI
// Page properties
Title = string.Format("{0} Net", runtype.ToString().ToUpperFirstOnly());
BackgroundColor = Color.SteelBlue;
Padding = new Thickness(Application.Current.MainPage.Width * 0.05, Application.Current.MainPage.Height * 0.05);
// Label for description
Label description = new Label
{
Text = string.Format("Please define the number of data sets from the MNIST {0} data base to be used for {0}ing. Each data set represents one digit. The {0} data base holds about {1:N0} data sets in total.", runtype.ToString(), mnistdata.CountData),
Margin = new Thickness(0, 0, 0, Application.Current.MainPage.Height * 0.075)
};
// Label for number of training / testing sets used
Label label_useddatasets = new Label
{
Text = String.Format("{0:N0} data set{1} selected", mnistdata.UsedDataSets, mnistdata.UsedDataSets == 0 ? "" : "s"),
Margin = new Thickness(0, 0, 0, Application.Current.MainPage.Height * 0.075)
};
// Slider for number of data sets used for training / testing
Slider slider_useddatasets = new Slider(1, mnistdata.CountData, mnistdata.UsedDataSets);
slider_useddatasets.ValueChanged += (s, e) =>
{
mnistdata.UsedDataSets = (int)e.NewValue;
label_useddatasets.Text = String.Format("{0:N0} data set{1} selected", mnistdata.UsedDataSets, mnistdata.UsedDataSets == 0 ? "" : "s");
};
// Progress bar
ProgressBar progressbar = new ProgressBar {
Progress = 0
};
// Label for showing progress
Label label_progress = new Label
{
Text = "Currently no calculation running",
};
// Button to start training / testing
Button button = new Button
{
Text = string.Format("Start {0}ing", runtype.ToString().ToUpperFirstOnly()),
WidthRequest = Application.Current.MainPage.Width * 0.5,
HeightRequest = Application.Current.MainPage.Height * 0.10
};
// Define page
Content = new ScrollView
{
Content = new StackLayout
{
Children =
{
description,
label_useddatasets,
slider_useddatasets,
button,
progressbar,
label_progress
}
}
};
// Button event
// Here training and test sessions are executed
button.Clicked += async(s, e) =>
{
// Check if another calculation is currently running
if (activerun == true)
{
var answer = await DisplayAlert("Warning", "Do you want to stop current calculation?", "Yes", "No");
if (answer)
{
endrun = true;
}
return;
}
// Check if selected data set is big
if (mnistdata.UsedDataSets > mnistdata.UsedDataSetsWarning)
{
bool answer = await DisplayAlert("Warning", "Please be aware that big data sets effect run time. Continue?", "Yes", "No");
if (!answer)
{
return;
}
}
// Set activerun and endrun flags
activerun = true;
endrun = false;
// Disable Back button
NavigationPage.SetHasBackButton(this, false);
// Rename Button to Stop
button.Text = string.Format("Stop {0}ing", runtype.ToString().ToUpperFirstOnly());
// Define parameters for progress bar calculation (increase bar 100 times or each 20 runs)
int progresssteps = Math.Max(100, mnistdata.UsedDataSets / 20);
int progressspan = (int)Math.Ceiling((double)mnistdata.UsedDataSets / progresssteps);
// Counter for training / testing runs
int i = 0;
// Initialize progress bar
label_progress.Text = i.ToString() + " / " + mnistdata.UsedDataSets.ToString();
await progressbar.ProgressTo((double)i / mnistdata.UsedDataSets, 1, Easing.Linear);
// Train neural net
if (runtype == NeuralNetRunType.train)
{
while (i < mnistdata.UsedDataSets && endrun == false)
{
// Counter for runs in progress step
int j = 0;
// Training loop for one progress step done as task
await Task.Run(() =>
{
while (j < progressspan && i < mnistdata.UsedDataSets)
{
// Train net with data set i
neuralnet.Train(mnistdata.Input(i), mnistdata.Output(i));
j++;
i++;
}
// Remember number of training data sets
neuralnet.TrainingDataCounter += j;
});
// Update progress bar
label_progress.Text = i.ToString() + " / " + mnistdata.UsedDataSets.ToString();
await progressbar.ProgressTo((double)i / mnistdata.UsedDataSets, 1, Easing.Linear);
}
// Show mesage
await DisplayAlert("Result", string.Format("Neural net trained with {0:N0} data sets", i), "OK");
}
if (runtype == NeuralNetRunType.test)
{
// Setup scorecard for capturing test results
// digittotal counts all trained figures, digitcorrect the ones that are identified correctly
Vector <double> digittotal = Vector <double> .Build.Dense(10);
Vector <double> digitcorrect = Vector <double> .Build.Dense(10);
// Testing loop
while (i < mnistdata.UsedDataSets && endrun == false)
{
// Counter for runs in progress step
int j = 0;
// Testing loop for one progress step done as task
await Task.Run(() =>
{
while (j < progressspan && i < mnistdata.UsedDataSets)
{
// Increase counter for testet digit (0..9)
int number = mnistdata.Number(i);
digittotal[number]++;
// Ask net
Vector <double> answer = neuralnet.Query(mnistdata.Input(i));
// Check if it's correct
if (answer.AbsoluteMaximumIndex() == number)
{
digitcorrect[number]++;
}
j++;
i++;
}
// Remember number of training data sets
neuralnet.TrainingDataCounter += j;
});
// Update progress bar
label_progress.Text = i.ToString() + " / " + mnistdata.UsedDataSets.ToString();
await progressbar.ProgressTo((double)i / mnistdata.UsedDataSets, 1, Easing.Linear);
}
// Remeber performance result
neuralnet.Performance.Add(digitcorrect.Sum() / digittotal.Sum());
// Show test results
await Navigation.PushAsync(new ResultsMNISTPage(neuralnet, mnistdata, digittotal, digitcorrect));
}
// Reset progress bar
label_progress.Text = "Currently no calculation running";
await progressbar.ProgressTo(0.0, 250, Easing.Linear);
// Rename Button to Start
button.Text = string.Format("Start {0}ing", runtype.ToString().ToUpperFirstOnly());
// Enable Back button
NavigationPage.SetHasBackButton(this, true);
// Cancel activerun flag
activerun = false;
};
}
public ResultsDetailsPage(NeuralNet neuralnet, MNISTDataManager mnistdata)
{
// Save parameters
this.neuralnet = neuralnet;
this.mnistdata = mnistdata;
// Define GUI
// Page properties
Title = "Details";
BackgroundColor = Color.SteelBlue;
Padding = new Thickness(Application.Current.MainPage.Width * 0.05, Application.Current.MainPage.Height * 0.05);
// Step 1: Generate initial collection of pictures from MNIST database (buffersize elements)
pictures = new ObservableCollection <CarouselItem>();
AddPictures(0);
// Step 2: Generate data template (just a Image with data binding to CarouselItem class)
DataTemplate template = new DataTemplate(() =>
{
Image image = new Image();
image.SetBinding(Image.SourceProperty, "Picture");
return(image);
});
// Step 3: Generate carousel view
var myCarousel = new CarouselViewControl();
myCarousel.Position = 0; //default
myCarousel.ItemsSource = pictures;
myCarousel.ItemTemplate = template;
myCarousel.InterPageSpacing = 2;
myCarousel.Orientation = CarouselViewOrientation.Horizontal;
myCarousel.ShowIndicators = false;
myCarousel.HorizontalOptions = LayoutOptions.FillAndExpand;
myCarousel.VerticalOptions = LayoutOptions.FillAndExpand;
// Define labels
labelheadline = new Label();
labeldigitcorrect = new Label();
labeldigitanswernet = new Label
{
HorizontalOptions = LayoutOptions.FillAndExpand,
HeightRequest = Application.Current.MainPage.Height * 0.1,
VerticalTextAlignment = TextAlignment.Center
};
SetLabels(0);
// Step 4: Build page
Content = new ScrollView
{
Content = new StackLayout
{
Children = { labelheadline, labeldigitcorrect, myCarousel, labeldigitanswernet },
Spacing = Application.Current.MainPage.Height * 0.05
}
};
// Update page when image is swiped
myCarousel.PositionSelected += (s, e) =>
{
// Add new pictures if user has reached end of carousel
// KNOWN ERROR: When end is reached the wrong picture is displayed (first picture of uploaded data)
// Warning: stepping through all MINST data may yield to memory problems
if (myCarousel.Position == pictures.Count - 1)
{
AddPictures(myCarousel.Position + 1);
}
// Update label
SetLabels(myCarousel.Position);
};
}
public ResultsMNISTPage(NeuralNet neuralnet, MNISTDataManager mnistdata, Vector <double> digittotal, Vector <double> digitcorrect)
{
// Define GUI
// Page properties
Title = "Results";
BackgroundColor = Color.SteelBlue;
Padding = new Thickness(Application.Current.MainPage.Width * 0.05, Application.Current.MainPage.Height * 0.05);
// Define styles for labels in grid
var labelgridStyle = new Style(typeof(Label))
{
Setters =
{
new Setter {
Property = Label.TextColorProperty, Value = Color.GhostWhite
},
new Setter {
Property = Label.BackgroundColorProperty, Value = Color.SteelBlue
},
new Setter {
Property = Label.HorizontalOptionsProperty, Value = LayoutOptions.FillAndExpand
},
new Setter {
Property = Label.HorizontalTextAlignmentProperty, Value = TextAlignment.Center
},
new Setter {
Property = Label.VerticalOptionsProperty, Value = LayoutOptions.FillAndExpand
},
new Setter {
Property = Label.VerticalTextAlignmentProperty, Value = TextAlignment.Center
}
}
};
var labelgridhighlightStyle = new Style(typeof(Label))
{
BasedOn = labelgridStyle,
Setters =
{
new Setter {
Property = Label.TextColorProperty, Value = Color.GhostWhite
},
new Setter {
Property = Label.BackgroundColorProperty, Value = Color.DarkOrange
},
new Setter {
Property = Label.FontAttributesProperty, Value = FontAttributes.Bold
}
}
};
var labelgridheadlineStyle = new Style(typeof(Label))
{
BasedOn = labelgridStyle,
Setters =
{
new Setter {
Property = Label.TextColorProperty, Value = Color.SteelBlue
},
new Setter {
Property = Label.BackgroundColorProperty, Value = Color.GhostWhite
},
new Setter {
Property = Label.FontAttributesProperty, Value = FontAttributes.Bold
}
}
};
// Define 11x3 grid for representing results
Grid grid = new Grid();
grid.BackgroundColor = Color.GhostWhite;
grid.ColumnSpacing = 1;
grid.RowSpacing = 1;
grid.Padding = new Thickness(1);
grid.HorizontalOptions = LayoutOptions.FillAndExpand;
grid.VerticalOptions = LayoutOptions.FillAndExpand;
for (int i = 0; i < 4; i++)
{
grid.ColumnDefinitions.Add(new ColumnDefinition {
Width = new GridLength(1, GridUnitType.Star)
});
}
for (int i = 0; i < 12; i++)
{
grid.RowDefinitions.Add(new RowDefinition {
Height = new GridLength(1, GridUnitType.Star)
});
}
// Add headlines to grid
grid.Children.Add(new Label {
Text = "Digit", Style = labelgridheadlineStyle
}, 0, 0);
grid.Children.Add(new Label {
Text = "Total", Style = labelgridheadlineStyle
}, 1, 0);
grid.Children.Add(new Label {
Text = "Correct", Style = labelgridheadlineStyle
}, 2, 0);
grid.Children.Add(new Label {
Text = "in %", Style = labelgridheadlineStyle
}, 3, 0);
// Add results for each digit to grid
for (int i = 0; i < 10; i++)
{
grid.Children.Add(new Label {
Text = i.ToString(), Style = labelgridStyle
}, 0, i + 1);
grid.Children.Add(new Label {
Text = String.Format("{0:N0}", digittotal[i]), Style = labelgridStyle
}, 1, i + 1);
grid.Children.Add(new Label {
Text = String.Format("{0:N0}", digitcorrect[i]), Style = labelgridStyle
}, 2, i + 1);
grid.Children.Add(new Label {
Text = String.Format("{0:P0}", digittotal[i] > 0 ? digitcorrect[i] / digittotal[i] : 0), Style = labelgridStyle
}, 3, i + 1);
}
// Add sum to grid
grid.Children.Add(new Label {
Text = "Sum", Style = labelgridhighlightStyle
}, 0, 11);
grid.Children.Add(new Label {
Text = String.Format("{0:N0}", digittotal.Sum()), Style = labelgridhighlightStyle
}, 1, 11);
grid.Children.Add(new Label {
Text = String.Format("{0:N0}", digitcorrect.Sum()), Style = labelgridhighlightStyle
}, 2, 11);
grid.Children.Add(new Label {
Text = String.Format("{0:P0}", digitcorrect.Sum() / digittotal.Sum()), Style = labelgridhighlightStyle
}, 3, 11);
// Define button for details
Button button = new Button
{
Text = "Details",
WidthRequest = Application.Current.MainPage.Width * 0.8,
HeightRequest = Application.Current.MainPage.Height * 0.10,
VerticalOptions = LayoutOptions.Center,
};
// Show page with detailed results for each digit
button.Clicked += (s, e) =>
{
if (messageflag == false)
{
DisplayAlert("Information", "Look at the details by swiping left and right.", "OK");
messageflag = true;
}
Navigation.PushAsync(new ResultsDetailsPage(neuralnet, mnistdata));
};
// Define page
Content = new ScrollView
{
Content = new StackLayout
{
Children = { grid, button },
Spacing = Application.Current.MainPage.Height * 0.05
}
};
}
