public LayerVisialize(FeatureMapsLayer featureMapsLayer)
{
this.layerMaps = new List <>();
this.featureMapsLayer = featureMapsLayer;
this.mapDimensions = featureMapsLayer.MapDimensions;
initWeights();
}
//JAVA TO C# CONVERTER WARNING: 'final' parameters are not allowed in .NET:
//ORIGINAL LINE: public Builder withConvolutionLayer(final org.neuroph.nnet.comp.Dimension2D kernelDimension, int numberOfMaps, Class transferFunction)
public virtual Builder withConvolutionLayer(comp.Dimension2D kernelDimension, int numberOfMaps, Type transferFunction)
{
FeatureMapsLayer prevLayer = LastFeatureMapLayer;
ConvolutionalLayer convolutionLayer = new ConvolutionalLayer(prevLayer, kernelDimension, numberOfMaps, transferFunction);
network.addLayer(convolutionLayer);
ConvolutionalUtils.fullConnectMapLayers(prevLayer, convolutionLayer);
return(this);
}
public virtual Builder withPoolingLayer(int width, int height)
{
FeatureMapsLayer lastLayer = LastFeatureMapLayer;
PoolingLayer poolingLayer = new PoolingLayer(lastLayer, new comp.Dimension2D(width, height));
network.addLayer(poolingLayer);
ConvolutionalUtils.fullConnectMapLayers(lastLayer, poolingLayer);
return(this);
}
public virtual Builder withConvolutionLayer(int kernelWidth, int kernelHeight, int numberOfMaps)
{
FeatureMapsLayer prevLayer = LastFeatureMapLayer;
ConvolutionalLayer convolutionLayer = new ConvolutionalLayer(prevLayer, new comp.Dimension2D(kernelWidth, kernelHeight), numberOfMaps);
network.addLayer(convolutionLayer);
ConvolutionalUtils.fullConnectMapLayers(prevLayer, convolutionLayer);
return(this);
}
