public LayerNetManager(TrainDataManager trainDataManager, TrainParameters trainParameters)
{
LayerNet = new List <Layer>();
TrainParameters = trainParameters;
LabelMap = trainDataManager.LabelMap;
InputDataShape = trainDataManager.DataShapeIn;
OutputDataShape = trainDataManager.DataShapeOut;
LearningRate = trainParameters.LearningRate;
CreateLayNet(trainParameters);
}
public void CreateLayNet(TrainParameters layNetParameter)
{
LayerNet = new List <Layer>();
var inputLayer = new LayerInput(InputDataShape)
{
LayerIndex = 0
};
LayerNet.Add(inputLayer);
layNetParameter.InterLayerStructs.ToList().ForEach(a =>
{
var dataShape = LayerNet.Last().ShapeOut;
switch (a.LayerType)
{
case LayerType.FullConnectLayer:
var fullConnectedLayer = new LayerFullConnected(dataShape, a.NeureCount)
{
LayerIndex = LayerNet.Count
};
LayerNet.Add(fullConnectedLayer);
break;
case LayerType.PoolingLayer:
var poolingLayer = new LayerPooling(dataShape)
{
LayerIndex = LayerNet.Count
};
LayerNet.Add(poolingLayer);
break;
}
});
var outputLayer = new LayerOutput(LayerNet.Last().ShapeOut, OutputDataShape)
{
LayerIndex = LayerNet.Count
};
LayerNet.Add(outputLayer);
}