public bool Load(int validationSize = 0, Boolean dataAugmentation = false)
{
Directory.CreateDirectory(mnistFolder);
var trainingLabelFilePath = Path.Combine(mnistFolder, trainingLabelFile);
var trainingImageFilePath = Path.Combine(mnistFolder, trainingImageFile);
var testingLabelFilePath = Path.Combine(mnistFolder, testingLabelFile);
var testingImageFilePath = Path.Combine(mnistFolder, testingImageFile);
// Download Mnist files if needed
Console.WriteLine("Downloading Mnist training files...");
DownloadFile(urlMnist + trainingLabelFile, trainingLabelFilePath);
DownloadFile(urlMnist + trainingImageFile, trainingImageFilePath);
Console.WriteLine("Downloading Mnist testing files...");
DownloadFile(urlMnist + testingLabelFile, testingLabelFilePath);
DownloadFile(urlMnist + testingImageFile, testingImageFilePath);
// Load data
Console.WriteLine("Loading the datasets...");
var train_images = MnistReader.Load(trainingLabelFilePath, trainingImageFilePath);
var testing_images = MnistReader.Load(testingLabelFilePath, testingImageFilePath);
if (dataAugmentation)
{
train_images = (new ImageTransformation()).DataAugmentation(train_images);
}
var validation_images = train_images.GetRange(train_images.Count - validationSize, validationSize);
train_images = train_images.GetRange(0, train_images.Count - validationSize);
if (train_images.Count == 0 || testing_images.Count == 0 || (validationSize > 0 && validation_images.Count == 0))
{
Console.WriteLine("Missing Mnist training/testing files.");
Console.ReadKey();
return(false);
}
this.Train = new DataSet(train_images);
this.Test = new DataSet(testing_images);
this.Validation = new DataSet(validation_images);
return(true);
}
private void MnistDemo()
{
Directory.CreateDirectory(mnistFolder);
string trainingLabelFilePath = Path.Combine(mnistFolder, trainingLabelFile);
string trainingImageFilePath = Path.Combine(mnistFolder, trainingImageFile);
string testingLabelFilePath = Path.Combine(mnistFolder, testingLabelFile);
string testingImageFilePath = Path.Combine(mnistFolder, testingImageFile);
// Download Mnist files if needed
Console.WriteLine("Downloading Mnist training files...");
DownloadFile(urlMnist + trainingLabelFile, trainingLabelFilePath);
DownloadFile(urlMnist + trainingImageFile, trainingImageFilePath);
Console.WriteLine("Downloading Mnist testing files...");
DownloadFile(urlMnist + testingLabelFile, testingLabelFilePath);
DownloadFile(urlMnist + testingImageFile, testingImageFilePath);
// Load data
Console.WriteLine("Loading the datasets...");
this.training = MnistReader.Load(trainingLabelFilePath, trainingImageFilePath);
this.testing = MnistReader.Load(testingLabelFilePath, testingImageFilePath);
if (this.training.Count == 0 || this.testing.Count == 0)
{
Console.WriteLine("Missing Mnist training/testing files.");
Console.ReadKey();
return;
}
// Create network
this.net = new Net();
this.net.AddLayer(new InputLayer(24, 24, 1));
this.net.AddLayer(new ConvLayer(5, 5, 8)
{
Stride = 1, Pad = 2
});
this.net.AddLayer(new ReluLayer());
this.net.AddLayer(new PoolLayer(2, 2)
{
Stride = 2
});
this.net.AddLayer(new ConvLayer(5, 5, 16)
{
Stride = 1, Pad = 2
});
this.net.AddLayer(new ReluLayer());
this.net.AddLayer(new PoolLayer(3, 3)
{
Stride = 3
});
this.net.AddLayer(new FullyConnLayer(10));
this.net.AddLayer(new SoftmaxLayer(10));
this.trainer = new AdadeltaTrainer(this.net)
{
BatchSize = 20,
L2Decay = 0.001,
};
Console.WriteLine("Convolutional neural network learning...[Press any key to stop]");
do
{
var sample = this.SampleTrainingInstance();
this.Step(sample);
} while (!Console.KeyAvailable);
}
private void MnistDemo()
{
Directory.CreateDirectory(mnistFolder);
string trainingLabelFilePath = Path.Combine(mnistFolder, trainingLabelFile);
string trainingImageFilePath = Path.Combine(mnistFolder, trainingImageFile);
string testingLabelFilePath = Path.Combine(mnistFolder, testingLabelFile);
string testingImageFilePath = Path.Combine(mnistFolder, testingImageFile);
// Download Mnist files if needed
Console.WriteLine("Downloading Mnist training files...");
DownloadFile(urlMnist + trainingLabelFile, trainingLabelFilePath);
DownloadFile(urlMnist + trainingImageFile, trainingImageFilePath);
Console.WriteLine("Downloading Mnist testing files...");
DownloadFile(urlMnist + testingLabelFile, testingLabelFilePath);
DownloadFile(urlMnist + testingImageFile, testingImageFilePath);
// Load data
Console.WriteLine("Loading the datasets...");
this.training = MnistReader.Load(trainingLabelFilePath, trainingImageFilePath).Where(p => numbers.Contains(p.Label)).ToList();
this.testing = MnistReader.Load(testingLabelFilePath, testingImageFilePath).Where(p => numbers.Contains(p.Label)).ToList();
if (this.training.Count == 0 || this.testing.Count == 0)
{
Console.WriteLine("Missing Mnist training/testing files.");
Console.ReadKey();
return;
}
Console.WriteLine($"datasets training: {this.training.Count}, testing: {this.testing.Count}");
//ExtractImages();
var netFile = Path.Combine(mnistFolder, $"net{string.Join("", numbers)}.bin");
if (File.Exists(netFile))
{
Console.WriteLine($"load {netFile}?");
if (Console.ReadKey(true).Key == ConsoleKey.Enter)
{
Console.WriteLine($"loading...");
this.net = Net.Load(netFile);
}
}
if (this.net == null)
{
this.net = new Net();
this.net.AddLayer(new InputLayer(24, 24, 1));
this.net.AddLayer(new ConvLayer(5, 5, 8)
{
Stride = 1, Pad = 2
});
this.net.AddLayer(new ReluLayer());
//this.net.AddLayer(new PoolLayer(2, 2) { Stride = 2 });
this.net.AddLayer(new ConvLayer(5, 5, 16)
{
Stride = 1, Pad = 2
});
this.net.AddLayer(new ReluLayer());
//this.net.AddLayer(new PoolLayer(3, 3) { Stride = 3 });
this.net.AddLayer(new FullyConnLayer(numbers.Length));
//this.net.AddLayer(new DropOutLayer());
this.net.AddLayer(new SoftmaxLayer(numbers.Length));
}
this.trainer = new AdadeltaTrainer(this.net)
{
BatchSize = 20,
L2Decay = 0.001,
};
Console.WriteLine($"limit cpu cores to 1?");
if (Console.ReadKey(true).Key == ConsoleKey.Enter)
{
using (Process Proc = Process.GetCurrentProcess())
{
long AffinityMask = (long)Proc.ProcessorAffinity;
AffinityMask = 1;
Proc.ProcessorAffinity = (IntPtr)AffinityMask;
}
}
Console.WriteLine("Training...[Press any key to stop]");
bool ok = false;
while (!ok)
{
do
{
var sample = this.SampleTrainingInstance();
ok = this.Step(sample);
}while (!ok && !Console.KeyAvailable);
if (!ok)
{
Console.ReadKey(true);
}
Console.WriteLine($"stop? [ENTER: continue]");
ok = !(Console.ReadKey(true).Key == ConsoleKey.Enter);
}
Console.WriteLine($"save {netFile}?");
if (Console.ReadKey(true).Key == ConsoleKey.Enter)
{
var f = Path.Combine(mnistFolder, netFile);
Console.WriteLine($"saving...");
net.Save(f);
}
Console.WriteLine("done.");
Console.ReadKey();
}
