private static void MNISTTrainNetwork(FeedforwardNeuralNetwork fnn, TrainingExample[] trainingExamples, TrainingExample[] testExamples)
{
Console.WriteLine("\nBeginning neural network training procedure.\n");
Console.WriteLine("Enter desired number of epochs.");
string epochsStr = Console.ReadLine();
int epochs = Convert.ToInt32(epochsStr);
do
{
Console.WriteLine("Please wait for training cycle to complete...");
var timer = Stopwatch.StartNew();
fnn.TrainEpochs(trainingExamples, epochs);
Console.WriteLine("Training cycle completed in " + timer.Elapsed + ".");
Console.WriteLine("Test network? Enter Y for yes or anything else for no.");
string inputStr = Console.ReadLine();
char input = Convert.ToChar(inputStr);
if (input == 'Y')
{
MNISTTestNetwork(fnn, testExamples);
}
Console.WriteLine("Continue training? Enter 0 for no or a valid number of epochs for yes.");
epochsStr = Console.ReadLine();
epochs = Convert.ToInt32(epochsStr);
} while (epochs > 0);
}
public static void DecimalBinaryExample()
{
int[] layers = new int[] { 2, 5, 4 };
FeedforwardNeuralNetwork fnn = new FeedforwardNeuralNetwork(layers, 1.0F, 0.1F);
DecimalBinaryTestNetwork(fnn);
Matrix[] expectedOutputs = { new Matrix(new float[4, 1] {
{ 1 },
{ 0 },
{ 0 },
{ 0 }
}),
new Matrix(new float[4, 1] {
{ 0 },
{ 1 },
{ 0 },
{ 0 }
}),
new Matrix(new float[4, 1] {
{ 0 },
{ 0 },
{ 1 },
{ 0 }
}),
new Matrix(new float[4, 1] {
{ 0 },
{ 0 },
{ 0 },
{ 1 }
}) };
Matrix[] inputs = { new Matrix(new float[2, 1] {
{ 0 },
{ 0 }
}),
new Matrix(new float[2, 1] {
{ 0 },
{ 1 }
}),
new Matrix(new float[2, 1] {
{ 1 },
{ 0 }
}),
new Matrix(new float[2, 1] {
{ 1 },
{ 1 }
}) };
TrainingExample[] examples = new TrainingExample[4];
for (int i = 0; i < 4; ++i)
{
examples[i] = new TrainingExample(inputs[i], expectedOutputs[i]);
}
fnn.TrainEpochs(examples, 1000);
DecimalBinaryTestNetwork(fnn);
}
public static void DecimalBinaryExample()
{
int[] layers = new int[] { 2, 5, 4 };
FeedforwardNeuralNetwork fnn = new FeedforwardNeuralNetwork(layers, 1.0F, 0.1F);
DecimalBinaryTestNetwork(fnn);
Matrix[] expectedOutputs = { new Matrix(new float[4,1]{ {1},
{0},
{0},
{0}}),
new Matrix(new float[4,1]{ {0},
{1},
{0},
{0}}),
new Matrix(new float[4,1]{ {0},
{0},
{1},
{0}}),
new Matrix(new float[4,1]{ {0},
{0},
{0},
{1}})};
Matrix[] inputs = { new Matrix(new float[2,1]{ {0},
{0}}),
new Matrix(new float[2,1]{ {0},
{1}}),
new Matrix(new float[2,1]{ {1},
{0}}),
new Matrix(new float[2,1]{ {1},
{1}})};
TrainingExample[] examples = new TrainingExample[4];
for (int i = 0; i < 4; ++i) {
examples[i] = new TrainingExample(inputs[i], expectedOutputs[i]);
}
fnn.TrainEpochs(examples, 1000);
DecimalBinaryTestNetwork(fnn);
}
private static void MNISTTrainNetwork(FeedforwardNeuralNetwork fnn, TrainingExample[] trainingExamples, TrainingExample[] testExamples)
{
Console.WriteLine("\nBeginning neural network training procedure.\n");
Console.WriteLine("Enter desired number of epochs.");
string epochsStr = Console.ReadLine();
int epochs = Convert.ToInt32(epochsStr);
do {
Console.WriteLine("Please wait for training cycle to complete...");
var timer = Stopwatch.StartNew();
fnn.TrainEpochs(trainingExamples, epochs);
Console.WriteLine("Training cycle completed in " + timer.Elapsed + ".");
Console.WriteLine("Test network? Enter Y for yes or anything else for no.");
string inputStr = Console.ReadLine();
char input = Convert.ToChar(inputStr);
if (input == 'Y') {
MNISTTestNetwork(fnn, testExamples);
}
Console.WriteLine("Continue training? Enter 0 for no or a valid number of epochs for yes.");
epochsStr = Console.ReadLine();
epochs = Convert.ToInt32(epochsStr);
} while (epochs > 0);
}
