public PoolingLayer(int kernelSize, int layerIndex, FilterMeta filterMeta)
: base(layerIndex, filterMeta)
{
_maxValues = new bool[filterMeta.Channels, filterMeta.Size, filterMeta.Size];
_inputMaps = new double[filterMeta.Channels, filterMeta.Size, filterMeta.Size];
_kernelSize = kernelSize;
}
public ConvolutionalLayer(int nk, int ks, int li, FilterMeta ifm, IWeightInitializer wi, LearningRateAnnealerType lrat)
: base(li, ifm)
{
_numberOfKernels = nk;
_kernelSize = ks;
List <Kernel> temp = new List <Kernel>();
for (int i = 0; i < _numberOfKernels; i++)
{
var k = new Kernel(ks, ifm.Channels, lrat);
k.RandomizeWeights(wi);
temp.Add(k);
}
_kernels = new List <Kernel>(temp);
_inputeFm = ifm;
_outputFm = GetOutputFilterMeta();
_featureMaps = new double[_outputFm.Channels, _outputFm.Size, _outputFm.Size];
}
public DetectorLayer(int layerIndex, IActivator activator, FilterMeta filterMeta)
: base(layerIndex, filterMeta)
{
_featureMaps = new double[filterMeta.Channels, filterMeta.Size, filterMeta.Size];
_activator = activator;
}
protected FilterLayer(int layerIndex, FilterMeta filterMeta)
: base(layerIndex)
{
InputFilterMeta = filterMeta;
}
