public void Filler_GaussianDense(double meanParam, double stdParam)
{
var blob = new Tensor(2, 3, 4, 5);
var config = new GaussianFillerConfiguration(meanParam, stdParam);
var filler = new GaussianFiller(config);
filler.Fill(blob);
double mean = 0;
double var = 0;
int count = blob.Count;
using (var blobCpu = blob.OnCpu())
{
for (int i = 0; i < count; i++)
{
mean += blobCpu.DataAt(i);
var += (blobCpu.DataAt(i) - config.Mean) * (blobCpu.DataAt(i) - config.Mean);
}
mean /= count;
var /= count;
Assert.True(mean >= config.Mean - config.Std * 5);
Assert.True(mean <= config.Mean + config.Std * 5);
double targetVar = config.Std * config.Std;
Assert.True(var >= (targetVar / 5.0d));
Assert.True(var <= (targetVar * 5.0d));
}
}
public void Filler_GaussianDense(double meanParam, double stdParam)
{
var blob = new Tensor(2, 3, 4, 5);
var config = new GaussianFillerConfiguration(meanParam, stdParam);
var filler = new GaussianFiller(config);
filler.Fill(blob);
double mean = 0;
double var = 0;
int count = blob.Count;
using (var blobCpu = blob.OnCpu())
{
for (int i = 0; i < count; i++)
{
mean += blobCpu.DataAt(i);
var += (blobCpu.DataAt(i) - config.Mean) * (blobCpu.DataAt(i) - config.Mean);
}
mean /= count;
var /= count;
Assert.True(mean >= config.Mean - config.Std * 5);
Assert.True(mean <= config.Mean + config.Std * 5);
double targetVar = config.Std * config.Std;
Assert.True(var >= (targetVar / 5.0d));
Assert.True(var <= (targetVar * 5.0d));
}
}
public void Filler_GaussianSparse(double meanParam, double stdParam)
{
var blob = new Tensor(2, 3, 4, 5);
var config = new GaussianFillerConfiguration(meanParam, stdParam)
{
IsSparse = true
};
var filler = new GaussianFiller(config);
filler.Fill(blob);
double mean = 0;
double var = 0;
using (var blobCpu = blob.OnCpu())
{
int count = blob.Count;
int zeroes = 0;
for (int i = 0; i < count; i++)
{
if (blobCpu.DataAt(i) == 0.0d)
{
zeroes++;
}
else
{
mean += blobCpu.DataAt(i);
var += (blobCpu.DataAt(i) - config.Mean) * (blobCpu.DataAt(i) - config.Mean);
}
}
mean /= (count - zeroes);
var /= (count - zeroes);
Assert.True(mean >= config.Mean - config.Std * 5);
Assert.True(mean <= config.Mean + config.Std * 5);
double targetVar = config.Std * config.Std;
Assert.True(var >= (targetVar / 5.0d));
Assert.True(var <= (targetVar * 5.0d));
}
}
public void Filler_GaussianSparse(double meanParam, double stdParam)
{
var blob = new Tensor(2, 3, 4, 5);
var config = new GaussianFillerConfiguration(meanParam, stdParam) { IsSparse = true };
var filler = new GaussianFiller(config);
filler.Fill(blob);
double mean = 0;
double var = 0;
using (var blobCpu = blob.OnCpu())
{
int count = blob.Count;
int zeroes = 0;
for (int i = 0; i < count; i++)
{
if (blobCpu.DataAt(i) == 0.0d)
{
zeroes++;
}
else
{
mean += blobCpu.DataAt(i);
var += (blobCpu.DataAt(i) - config.Mean) * (blobCpu.DataAt(i) - config.Mean);
}
}
mean /= (count - zeroes);
var /= (count - zeroes);
Assert.True(mean >= config.Mean - config.Std * 5);
Assert.True(mean <= config.Mean + config.Std * 5);
double targetVar = config.Std * config.Std;
Assert.True(var >= (targetVar / 5.0d));
Assert.True(var <= (targetVar * 5.0d));
}
}
