void BuildNetwork() { int[] layers=new int[] { 841,1014,1250,100,10 }; LayerConnector[] map=new LayerConnector[] { new ConvolutionAuto(5,6,1,3), new ConvolutionAuto(5,50,6,1), new FullLayerConnector(), new FullLayerConnector() }; ConvolutionalTopology topology=new ConvolutionalTopology(layers,1,map,new HyperbolicTangent()); ConvolutionalGenerator generator=new ConvolutionalGenerator(); Network=generator.Create(topology); Network.LearnFactor=0.0005; Network.Reset(-0.1,0.1); }
private void button3_Click(object sender,EventArgs e) { OpenFileDialog dlg = new OpenFileDialog(); dlg.CheckFileExists=true; dlg.CheckPathExists=true; dlg.Filter="xml files (*.xml)|*.xml"; dlg.Multiselect=false; if (dlg.ShowDialog()==DialogResult.OK) { ConvolutionalXMLSerializer serializer=new ConvolutionalXMLSerializer(); Network=serializer.Deserialize(XDocument.Load(dlg.FileName)); Network.LearnFactor=0.0005; Loaded=true; } }
public XDocument Serialize(ConvolutionalNetwork network) { return new XDocument(new XElement("root", new XElement("layers",network.Structure.Layers.Length.ToString()), GetElements(network.Structure))); }
public void TSSetUp() { int[] layers=new int[] { 1024, //32x32 input image 4704, //6 @ 28x28 convolution 1176, //6 @ 14x14 subsampling 1600, //16 @ 10x10 convolution 400, //16 @ 5x5 subsampling 120, // 120x1x1 convolution! 84, //full 10 //full }; LayerConnector[] map=new LayerConnector[] { new ConvolutionAuto(5,6,1,4), new SubSampling(6), new Convolution(5,16,6,4,GetSchema()), new SubSampling(16), new ConvolutionAuto(5,120,16,0), new FullLayerConnector(), new FullLayerConnector() }; ConvolutionalTopology topology=new ConvolutionalTopology(layers,1,map); ConvolutionalGenerator generator=new ConvolutionalGenerator(); Network=generator.Create(topology); }
public XDocument Serialize(ConvolutionalNetwork network) { return(new XDocument(new XElement("root", new XElement("layers", network.Structure.Layers.Length.ToString()), GetElements(network.Structure)))); }