public void SoftmaxLayer_BackwardGradient()
{
var layer = new SoftmaxLayer();
var checker = new GradientChecker(1e-2f, 1e-3f);
checker.CheckExhaustive(layer, bottom, top);
}
public void BnllLayer_BackwardGradient()
{
var layer = new BnllLayer();
var checker = new GradientChecker(1e-2f, 1e-3f);
checker.CheckEltwise(layer, bottom, top);
}
public void ReluLayer_BackwardGradient()
{
var layer = new ReluLayer();
var checker = new GradientChecker(1e-2f, 1e-3f, 1701, 0.0d, 0.01f);
checker.CheckEltwise(layer, bottom, top);
}
public void PowerLayer_Backward(double power, double scale, double shift)
{
var config = new PowerLayerConfiguration(power, scale, shift);
var layer = new PowerLayer(config);
if (power != 0 && power != 1 && power != 2)
{
var minValue = -shift / scale;
using (var bottomCpu = bottom.OnCpu())
{
var bottomData = bottomCpu.Data;
for (int i = 0; i < bottom.Count; i++)
{
if (bottomData[i] < minValue)
{
bottomData[i] = minValue + (minValue - bottomData[i]);
}
}
}
}
var checker = new GradientChecker(1e-2f, 1e-2f, 1701, 0.0d, 0.01f);
checker.CheckEltwise(layer, bottom, top);
}
public void BnllLayer_BackwardGradient()
{
var layer = new BnllLayer();
var checker = new GradientChecker(1e-2f, 1e-3f);
checker.CheckEltwise(layer, bottom, top);
}
public void EuclideanLossLayer_BackwardGradient()
{
var layer = new EuclideanLossLayer();
layer.Setup(bottom, top);
var checker = new GradientChecker(1e-6f, 4e-1f);
checker.CheckSingle(layer, bottom, top, -1, -1, -1);
}
public void TanhLayer_BackwardGradient()
{
var layer = new TanhLayer();
var checker = new GradientChecker(1e-2f, 1e-3f, 1701, 0.0d, 0.01f);
checker.CheckEltwise(layer, bottom, top);
}
public void SoftmaxLayer_BackwardGradient()
{
var layer = new SoftmaxLayer();
var checker = new GradientChecker(1e-2f, 1e-3f);
checker.CheckExhaustive(layer, bottom, top);
}
public void SoftmaxLayer_BackwardGradient()
{
var layer = new SoftmaxLayer();
layer.Setup(bottom, labels);
var checker = new GradientChecker(1e-2f, 1e-2f);
checker.CheckSingle(layer, bottom, labels, 0, -1, -1);
}
public void ReluLayer_BackwardGradientWithLeakyUnits()
{
var config = new ReluLayerConfiguration(0.01f);
var layer = new ReluLayer(config);
var checker = new GradientChecker(1e-2f, 1e-2f, 1701, 0.0d, 0.01f);
checker.CheckEltwise(layer, bottom, top);
}
public void DropoutLayer_BackwardGradientTrainPhase()
{
Context.Instance.Phase = PhaseType.Train;
var layer = new DropoutLayer();
var checker = new GradientChecker(1e-2f, 1e-3f);
checker.CheckEltwise(layer, bottom, top);
}
public void ReluLayer_BackwardGradientWithLeakyUnits()
{
var config = new ReluLayerConfiguration(0.01f);
var layer = new ReluLayer(config);
var checker = new GradientChecker(1e-2f, 1e-2f, 1701, 0.0d, 0.01f);
checker.CheckEltwise(layer, bottom, top);
}
public void AveragePoolingLayer_BackwardGradient( Size kernel, Size stride, Size padding )
{
var filler = new ConstantFiller(2.0d);
filler.Fill(bottom);
var checker = new GradientChecker(1e-2f, 1e-2f);
var layer = new AveragePoolingLayer(kernel, stride, padding);
checker.CheckExhaustive(layer, bottom, top);
}
public void InnerProductLayer_BackwardGradient(int output, FillerConfiguration weightsFiller, FillerConfiguration biasFiller)
{
bool useBias = biasFiller != null;
var config = new InnerProductLayerConfiguration(output, useBias, weightsFiller, biasFiller);
var layer = new InnerProductLayer(config);
var checker = new GradientChecker(1e-4f, 1e-3f);
checker.CheckExhaustive(layer, bottom, top);
}
public void SoftmaxLayer_BackwardGradient()
{
var layer = new SoftmaxLayer();
layer.Setup(bottom, labels);
var checker = new GradientChecker(1e-2f, 1e-2f);
checker.CheckSingle(layer, bottom, labels, 0, -1, -1);
}
public void EuclideanLossLayer_BackwardGradient()
{
var layer = new EuclideanLossLayer();
layer.Setup(bottom, top);
var checker = new GradientChecker(1e-6f, 4e-1f);
checker.CheckSingle(layer, bottom, top, -1, -1, -1);
}
public void DropoutLayer_BackwardGradientTestPhase()
{
Context.Instance.Phase = PhaseType.Test;
var layer = new DropoutLayer();
var checker = new GradientChecker(1e-2f, 1e-3f);
checker.CheckEltwise(layer, bottom, top);
}
public void InnerProductLayer_BackwardGradient(int output, FillerConfiguration weightsFiller, FillerConfiguration biasFiller)
{
bool useBias = biasFiller != null;
var config = new InnerProductLayerConfiguration(output, useBias, weightsFiller, biasFiller);
var layer = new InnerProductLayer(config);
var checker = new GradientChecker(1e-4f, 1e-3f);
checker.CheckExhaustive(layer, bottom, top);
}
public void AveragePoolingLayer_BackwardGradient(Size kernel, Size stride, Size padding)
{
var filler = new ConstantFiller(2.0d);
filler.Fill(bottom);
var checker = new GradientChecker(1e-2f, 1e-2f);
var layer = new AveragePoolingLayer(kernel, stride, padding);
checker.CheckExhaustive(layer, bottom, top);
}
public void PowerLayer_Backward(double power, double scale, double shift)
{
var config = new PowerLayerConfiguration(power, scale, shift);
var layer = new PowerLayer(config);
if ( power != 0 && power != 1 && power != 2 )
{
var minValue = -shift / scale;
using (var bottomCpu = bottom.OnCpu())
{
var bottomData = bottomCpu.Data;
for (int i = 0; i < bottom.Count; i++)
{
if (bottomData[i] < minValue)
bottomData[i] = minValue + (minValue - bottomData[i]);
}
}
}
var checker = new GradientChecker(1e-2f, 1e-2f, 1701, 0.0d, 0.01f);
checker.CheckEltwise(layer, bottom, top);
}
