protected void SaveError(Layer lyr)
{
bool convtype = lyr.GetType().ToString() == "AI.ML.CNN.Layers.Convolution" ? true : false;
bool conctype = lyr.GetType().ToString() == "AI.ML.CNN.Layers.Connected" ? true : false;
switch (convtype)
{
case true:
Layers.Convolution convLyr = (Layers.Convolution)lyr;
Layers.Convolution.Kernel krn;
for (int j = 0; j < convLyr.Filters.Count; j++)
{
krn = (AI.ML.CNN.Layers.Convolution.Kernel)((AI.ML.CNN.Layers.Convolution.Filter)convLyr.Filters[j]).Kernels[0];
//bwc = (double?)krn.Element;
krn.Weights[0][0][2] += krn.WeightCorrection[0][0].Value;
// j: indexing filters
for (int k = 1; k < ((AI.ML.CNN.Layers.Convolution.Filter)convLyr.Filters[j]).Kernels.Length; k++)
{
//k: indexing kernels
krn = (AI.ML.CNN.Layers.Convolution.Kernel)((AI.ML.CNN.Layers.Convolution.Filter)convLyr.Filters[j]).Kernels[k];
for (int m = 0; m < krn.Weights.Length; m++)
{
for (int n = 0; n < krn.Weights.Length; n++)
{
krn.Weights[m][n][2] += krn.WeightCorrection[m][n].Value;
}
}
}
}
break;
case false:
switch (conctype)
{
case true:
Layers.Connected connLyr = (Layers.Connected)lyr;
Neuron n; Synapse syn;
for (int j = 0; j < connLyr.Neurons.Length; j++)
{
n = connLyr.Neurons[j];
n.Synapse[0].Weights[2] += n.Synapse[0].dW.Value;
for (int k = 1; k < n.Synapse.Count; k++)
{
syn = n.Synapse[k];
syn.Weights[2] += syn.dW.Value;
}
}
break;
case false:
break;
}
break;
default:
break;
}
}
protected void ClearError()
{
for (int i = 1; i < Model.Layers.Length; i++)
{
Model.Unit lyr;
lyr = Model.Layers[i];
bool convtype = lyr.GetType().ToString() == "AI.ML.CNN.Layers.Convolution" ? true : false;
bool conctype = lyr.GetType().ToString() == "AI.ML.CNN.Layers.Connected" ? true : false;
switch (convtype)
{
case true:
Layers.Convolution convLyr = (Layers.Convolution)lyr;
Layers.Convolution.Kernel krn;
for (int j = 0; j < convLyr.Filters.Count; j++)
{
krn = (AI.ML.CNN.Layers.Convolution.Kernel)((AI.ML.CNN.Layers.Convolution.Filter)convLyr.Filters[j]).Kernels[0];
krn.Weights[0][0][2] = 0;
// j: indexing filters
for (int k = 1; k < ((AI.ML.CNN.Layers.Convolution.Filter)convLyr.Filters[j]).Kernels.Length; k++)
{
//k: indexing kernels
krn = (AI.ML.CNN.Layers.Convolution.Kernel)((AI.ML.CNN.Layers.Convolution.Filter)convLyr.Filters[j]).Kernels[k];
for (int m = 0; m < krn.Weights.Length; m++)
{
for (int n = 0; n < krn.Weights.Length; n++)
{
krn.Weights[m][n][2] = 0;
}
}
}
}
break;
case false:
switch (conctype)
{
case true:
Layers.Connected connLyr = (Layers.Connected)lyr;
Neuron n; Synapse syn;
for (int j = 0; j < connLyr.Neurons.Length; j++)
{
n = connLyr.Neurons[j];
n.Synapse[0].Weights[2] = 0;
for (int k = 1; k < n.Synapse.Count; k++)
{
syn = n.Synapse[k];
syn.Weights[2] = 0;
}
}
break;
case false:
break;
}
break;
default:
break;
}
}
}
