public ConvolutionalTopology(int[] layers,double? bias,LayerConnector[] map,IContinuousActivator func)
{
Utility.Verify(layers,l => l!=null && l.All(x => x>0),"Invalid layers array");
Utility.Verify(map,m => m.Length==layers.Length-1,"Invalid Map");
Utility.Verify(func,f => f!=null,"Invalid func");
Layers=layers;
Bias=bias;
Map=map;
Func=func;
}
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);
}
public ConvolutionalTopology(int[] layers,double? bias,LayerConnector[] map)
: this(layers,bias,map,new Sigmoid())
{
}
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);
}
