private void RefreshListBoxes(NN desired)
{
LayerTypes = new List <string>();
LayerCounts = new List <int>();
LayerLB.Items.Clear();
foreach (iLayer l in desired.Layers)
{
string name = null;
int len = l.Length;
if (l is PoolingLayer)
{
len = (l as PoolingLayer).PoolSize;
}
if (l is FullyConnectedLayer)
{
LayerTypes.Add("f"); name = "Fully Connected";
}
if (l is ConvolutionLayer)
{
LayerTypes.Add("c"); name = "Convolution"; len = (l as ConvolutionLayer).KernelSize;
}
if (l is PoolingLayer)
{
LayerTypes.Add("p"); name = "Pooling";
}
LayerCounts.Add(len);
LayerLB.Items.Add("[" + (LayerCounts.Count - 1).ToString() + "] " + name + ", " + len.ToString());
}
}
private void DefaultBtn_Click(object sender, EventArgs e)
{
LayerTypes = DefaultTypes();
LayerCounts = DefaultCounts();
NN newnn = ResetNN();
RefreshListBoxes(newnn);
}
private void Button3_Click(object sender, EventArgs e)
{
if (Run)
{
MessageBox.Show("Cannot reset while running"); return;
}
nn = ResetNN();
}
private NN ResetNN()
{
NN nn = new NN();
if (LayerTypes is null || LayerTypes.Count == 0)
{
LayerTypes = DefaultTypes();
LayerCounts = DefaultCounts();
}
nn.Init(GenerateLayers());
IO.Write(nn);
return(nn);
}
/// <summary>
/// Returns a NN from a file
/// </summary>
/// <param name="COG">[C]ritic [O]r [G]enerator</param>
/// <returns></returns>
public static NN Read()
{
NN nn = new NN();
nn.Layers = new List <iLayer>();
string[] text;
using (StreamReader sr = File.OpenText(WBPath))
{
text = sr.ReadToEnd().Split(',');
}
nn.NumLayers = int.Parse(text[0]);
int iterator = 1;
for (int i = 0; i < nn.NumLayers; i++)
{
string type = text[iterator]; iterator++;
//Pooling layer has no weights/biases
if (type == "p")
{
nn.Layers.Add(new PoolingLayer(int.Parse(text[iterator]), int.Parse(text[iterator + 1])));
iterator += 2; continue;
}
int LayerCount = int.Parse(text[iterator]); iterator++;
int InputLayerCount = int.Parse(text[iterator]); iterator++;
if (type == "f")
{
nn.Layers.Add(new FullyConnectedLayer(LayerCount, InputLayerCount));
}
if (type == "c")
{
nn.Layers.Add(new ConvolutionLayer((int)Math.Sqrt(LayerCount), InputLayerCount));
}
for (int j = 0; j < nn.Layers[i].Weights.GetLength(0); j++)
{
for (int jj = 0; jj < nn.Layers[i].Weights.GetLength(1); jj++)
{
nn.Layers[i].Weights[j, jj] = double.Parse(text[iterator]); iterator++;
}
if (i != nn.NumLayers - 1 && nn.Layers[i] is FullyConnectedLayer)
{
(nn.Layers[i] as FullyConnectedLayer).Biases[j] = double.Parse(text[iterator]); iterator++;
}
}
}
return(nn);
}
public Form1()
{
InitializeComponent();
//Various textboxes
Batchtxt.Text = BatchSize.ToString();
AlphaTxt.Text = NN.LearningRate.ToString();
SpecialDecay.Text = NN.RMSDecay.ToString();
Nesterov.Checked = NN.UseNesterov;
ConvStepsTxt.Text = ConvolutionLayer.StepSize.ToString();
//Special combobox
Special.Items.Add("None");
Special.Items.Add("RMSProp");
Special.Items.Add("Momentum");
//Special.Items.Add("ADAM");
Special.SelectedIndex = 1;
//Layer types combobox
LayerTypeCB.Items.Add("Fully Connected");
LayerTypeCB.Items.Add("Convolution");
LayerTypeCB.Items.Add("Pooling");
LayerTypeCB.SelectedIndex = 0;
//NN loading or reset if invalid
try
{
nn = IO.Read();
}
catch
{
MessageBox.Show("Failed to load data; reset to default");
nn = ResetNN();
}
RefreshListBoxes(nn);
if (LayerTypes.Count == 0)
{
nn = ResetNN();
}
}
/// <summary>
/// Saves a specified NN to a file
/// </summary>
/// <param name="nn">The specified NN</param>
/// <param name="COG">[C]ritic [O]r [G]enerator</param>
public static void Write(NN nn)
{
StreamWriter sw = new StreamWriter(new FileStream(WBPath, FileMode.Create, FileAccess.Write, FileShare.None));
sw.Write(nn.NumLayers + ",");
for (int i = 0; i < nn.NumLayers; i++)
{
string type = "f";
if (nn.Layers[i] is ConvolutionLayer)
{
type = "c";
}
if (nn.Layers[i] is PoolingLayer)
{
type = "p";
}
sw.Write(type + ",");
//Pooling layer has no weights
if (type == "p")
{
sw.Write((nn.Layers[i] as PoolingLayer).PoolSize + "," + nn.Layers[i].InputLength + ",");
continue;
}
sw.Write(nn.Layers[i].Length + "," + nn.Layers[i].InputLength + ",");
for (int j = 0; j < nn.Layers[i].Weights.GetLength(0); j++)
{
for (int jj = 0; jj < nn.Layers[i].Weights.GetLength(1); jj++)
{
sw.Write(nn.Layers[i].Weights[j, jj] + ",");
}
if (i != nn.NumLayers - 1 && nn.Layers[i] is FullyConnectedLayer)
{
sw.Write((nn.Layers[i] as FullyConnectedLayer).Biases[j] + ",");
}
}
}
sw.Close();
}
