protected override void ConvertVariable(ComputeVariable _variable)
{
var variable = _variable as Variable.AffineVariable;
BatchCount = variable.BatchCount;
InWidth = variable.InWidth;
InHeight = variable.InHeight;
InputChannels = variable.InputChannels;
OutWidth = variable.OutWidth;
OutHeight = variable.OutHeight;
OutputChannels = variable.OutputChannels;
InSize = variable.InSize;
InArea = variable.InArea;
InTotal = variable.InTotal;
OutSize = variable.OutSize;
OutArea = variable.OutArea;
OutTotal = variable.OutTotal;
OptimizerType = variable.OptimizerType;
Rho = variable.Rho;
Weight = variable.Weight.Data;
Input = variable.Input.Data;
Output = variable.Output.Data;
Sigma = variable.Sigma.Data;
Propagator = variable.Propagator.Data;
Error = variable.Error;
Difference = variable.WeightDifference;
}
public void AddConvolution(int outch, int kernelsize, int expand,
Utility.Types.Optimizer type = Utility.Types.Optimizer.Adam, double scale = 1, double rho = 0.0005)
{
int inw, inh, inch;
GetLayerInputInfomation(out inw, out inh, out inch);
AddLayer(new Layer.Convolution(true)
{
Variable = new DedicatedFunction.Variable.ConvolutionVariable()
{
BatchCount = BatchCount,
InputChannels = inch,
InWidth = inw,
InHeight = inh,
OutputChannels = outch,
OutScale = scale,
KernelSize = kernelsize,
KernelExpand = expand,
OptimizerType = type,
Rho = rho,
}.Confirm(Instance),
}.Confirm());
}
public static OptimizerBase CreateInstance(Utility.Types.Optimizer type, List <Components.RNdMatrix> sender, Components.Real[] weight)
{
OptimizerBase instance = null;
switch (type)
{
case Utility.Types.Optimizer.Adam:
instance = new Adam(sender, weight);
break;
case Utility.Types.Optimizer.AdaSelf:
instance = new AdaSelf(sender, weight);
break;
default:
break;
}
return(instance);
}
protected override void ConvertVariable(ComputeVariable _variable)
{
var variable = _variable as Variable.ConvolutionVariable;
BatchCount = variable.BatchCount;
InWidth = variable.InWidth;
InHeight = variable.InHeight;
InputChannels = variable.InputChannels;
OutScale = (float)variable.OutScale;
OutWidth = variable.OutWidth;
OutHeight = variable.OutHeight;
OutputChannels = variable.OutputChannels;
InSize = variable.InSize;
InArea = variable.InArea;
InTotal = variable.InTotal;
OutSize = variable.OutSize;
OutArea = variable.OutArea;
OutTotal = variable.OutTotal;
KernelSize = variable.KernelSize;
KernelArea = variable.KernelArea;
KernelLength = variable.KernelLength;
KernelExpand = variable.KernelExpand;
OptimizerType = variable.OptimizerType;
rho = variable.Rho;
Input = variable.Input.Data;
Output = variable.Output.Data;
Sigma = variable.Sigma.Data;
Propagator = variable.Propagator.Data;
WeightKernel = variable.WeightKernel.Data;
WeightBias = variable.WeightBias.Data;
Error = variable.Error;
Difference = variable.WeightDifference;
}
public void AddAffine(int outcount, Utility.Types.Optimizer type = Utility.Types.Optimizer.Adam, double rho = 0.0005)
{
int inw, inh, inch;
GetLayerInputInfomation(out inw, out inh, out inch);
AddLayer(new Layer.Affine(true)
{
Variable = new DedicatedFunction.Variable.AffineVariable()
{
BatchCount = BatchCount,
InputChannels = inch,
InWidth = inw,
InHeight = inh,
OutputChannels = 1,
OutWidth = 1,
OutHeight = outcount,
OptimizerType = type,
Rho = rho,
}.Confirm(Instance),
}.Confirm());
}
