public override Volume <double> Random(Shape shape, double mu = 0, double std = 1.0)
{
var vol = new Volume(new NcwhVolumeStorage <double>(shape));
for (var n = 0; n < shape.Dimensions[3]; n++)
{
for (var c = 0; c < shape.Dimensions[2]; c++)
{
for (var y = 0; y < shape.Dimensions[1]; y++)
{
for (var x = 0; x < shape.Dimensions[0]; x++)
{
vol.Set(x, y, c, n, RandomUtilities.Randn(mu, std));
}
}
}
}
return(vol);
}
public override Volume <double> Random(Shape shape, double mu = 0, double std = 1.0)
{
//RandomUtilities.RandomDoubleArray(shape.TotalLength, mu, std), shape)
var vol = new Volume(new NcwhVolumeStorage <double>(shape));
for (int n = 0; n < shape.GetDimension(3); n++)
{
for (int c = 0; c < shape.GetDimension(2); c++)
{
for (int y = 0; y < shape.GetDimension(1); y++)
{
for (int x = 0; x < shape.GetDimension(0); x++)
{
vol.Set(x, y, c, n, RandomUtilities.Randn(mu, std));
}
}
}
}
return(vol);
}
/// <summary>
/// Volume will be filled with random numbers
/// </summary>
/// <param name="width">width</param>
/// <param name="height">height</param>
/// <param name="depth">depth</param>
public Volume(int width, int height, int depth)
{
// we were given dimensions of the vol
this.Width = width;
this.Height = height;
this.Depth = depth;
var n = width * height * depth;
this.Weights = new double[n];
this.WeightGradients = new double[n];
// weight normalization is done to equalize the output
// variance of every neuron, otherwise neurons with a lot
// of incoming connections have outputs of larger variance
var scale = Math.Sqrt(1.0 / (width * height * depth));
for (var i = 0; i < n; i++)
{
this.Weights[i] = RandomUtilities.Randn(0.0, scale);
}
}
