public void CopyTo(RNdMatrix dist)
{
if (IsSimilarity(this, dist))
{
Array.Copy(Data, 0, dist.Data, 0, Data.Length);
}
}
protected override void ConfirmField(object shared)
{
double sd = Math.Sqrt(1.0 / (InArea));
if (shared != null)
{
var obj = shared as Utility.Shared.ModelParameter;
var w = new Utility.Shared.ModelParameter.WeightData(1);
w.Data[0] = new Components.RNdMatrix(InArea + 1, OutArea, 1, 1);
Utility.Randomizer.Noize(ref w.Data[0].Data, Utility.Randomizer.Sign.Both, 0, sd);
obj.Weignt.Add(w);
Weight = new Components.RNdMatrix(w.Data[0].Shape);
Weight.Data = (w.Data[0].Data.Clone()) as Components.Real[];
WeightDifference = w.Difference.Clone() as Components.Real[];
}
else
{
if (!ObjectDecoded)
{
Weight = (new Components.RNdMatrix(InArea + 1, OutArea, 1, 1)) as Components.RNdMatrix;
Utility.Randomizer.Noize(ref Weight.Data, Utility.Randomizer.Sign.Both, 0, sd);
}
WeightDifference = new Components.Real[1];
}
}
public override RNdObject Clone()
{
var matrix = new RNdMatrix()
{
Data = (Real[])Data.Clone(), Shape = (int[])Shape.Clone()
};
return(matrix);
}
public override RNdObject Abs()
{
var matrix = new RNdMatrix()
{
Data = ((Real[])Data.Clone()).Select(x => (Real)Math.Abs(x)).ToArray(), Shape = (int[])Shape.Clone()
};
return(matrix);
}
public override RNdObject Clone()
{
var cl = new Real[Data.Length];
Array.Copy(Data, 0, cl, 0, Data.Length);
var matrix = new RNdMatrix()
{
Hash = this.Hash, Data = cl, Shape = (int[])Shape.Clone()
};
return(matrix);
}
protected override void ConfirmField(object shared)
{
CompressSize = CompressSize <= 0 ? 1 : CompressSize;
ExpandSize = ExpandSize <= 0 ? 1 : ExpandSize;
OutputChannels = InputChannels;
OutWidth = (int)(((double)ExpandSize / (double)CompressSize) * InWidth);
OutHeight = (int)(((double)ExpandSize / (double)CompressSize) * InHeight);
Map = new Components.RNdMatrix(BatchCount, OutputChannels, InWidth, InHeight);
if (shared != null)
{
var obj = shared as Utility.Shared.ModelParameter;
var w = new Utility.Shared.ModelParameter.WeightData(0);
obj.Weignt.Add(w);
}
}
public static void TestStart_ImageConvolusion()
{
Components.Imaging.Core.Instance.Initialize(State.CaptureMode.Device_Camera);
(new System.Threading.Tasks.Task(() =>
{
Random rand = new Random();
RNdMatrix inmat = new RNdMatrix(1, 3, 340, 240);
RNdMatrix outmat = new RNdMatrix(1, 3, 340, 240);
var unit = new GPGPU.Layer.Unit.Convolution.Convolution()
{
Activation = true,
KernelSize = 5,
OutputChannels = 3,
Rho = 0.001,
};
unit.Initialize(inmat.Clone());
unit.Confirm();
int counter = 0;
double time = 0;
while (true)
{
time = 0;
var input = Imaging.Core.Instance.GetFrame(inmat.Shape);
unit.Input = input.Clone();
time += unit.Action(State.ActionMode.Forward);
var sigma = unit.Output - input;
unit.Sigma = sigma;
//time += unit.Action(ActionMode.Back);
unit.Output.Show("output", 0);
sigma.Show("sigma", 0);
Terminal.WriteLine(State.EventState.State, "Step:{0}, TimeSpan[ms]:{1}, FPS:{2}", counter++, (int)time, (int)(1000.0 / time));
}
})).Start();
}
protected override void ConfirmField(object shared)
{
OutWidth = (int)(OutScale * InWidth);
OutHeight = (int)(OutScale * InHeight);
double sd_b = Math.Sqrt(1.0 / (InputChannels * KernelLength));
double sd_k = Math.Sqrt(1.0 / (InputChannels * KernelLength));
if (shared != null)
{
var obj = shared as Utility.Shared.ModelParameter;
var w = new Utility.Shared.ModelParameter.WeightData(2);
w.Data[0] = new Components.RNdMatrix(OutputChannels, 1, 1, 1);
w.Data[1] = new Components.RNdMatrix(InputChannels, OutputChannels, 2 * KernelSize + 1, 2 * KernelSize + 1);
Utility.Randomizer.Noize(ref w.Data[0].Data, Utility.Randomizer.Sign.Both, 0, sd_b);
Utility.Randomizer.Noize(ref w.Data[1].Data, Utility.Randomizer.Sign.Both, 0, sd_k);
obj.Weignt.Add(w);
WeightBias = new Components.RNdMatrix(w.Data[0].Shape);
WeightBias.Data = (w.Data[0].Data.Clone()) as Components.Real[];
WeightKernel = new Components.RNdMatrix(w.Data[1].Shape);
WeightKernel.Data = (w.Data[1].Data.Clone()) as Components.Real[];
WeightDifference = w.Difference.Clone() as Components.Real[];
}
else
{
if (!ObjectDecoded)
{
WeightBias = (new Components.RNdMatrix(OutputChannels, 1, 1, 1)) as Components.RNdMatrix;
WeightKernel = (new Components.RNdMatrix(InputChannels, OutputChannels, 2 * KernelSize + 1, 2 * KernelSize + 1)) as Components.RNdMatrix;
Utility.Randomizer.Noize(ref WeightBias.Data, Utility.Randomizer.Sign.Both, 0, sd_b);
Utility.Randomizer.Noize(ref WeightKernel.Data, Utility.Randomizer.Sign.Both, 0, sd_k);
}
WeightDifference = new Components.Real[2];
}
}
protected override void DecodeOption(List <object> values)
{
Weight = values[0] as RNdMatrix;
}
protected override void DecodeOption(List <object> values)
{
WeightBias = values[0] as RNdMatrix;
WeightKernel = values[1] as RNdMatrix;
}
