public void LogGradientCheck()
{
var x = new PlaceHolder <T>("x");
var fun = ConvNetSharp <T> .Instance.Log(x);
var shape = new Shape(2, 2, 3, 4);
var location = NewVolume(RandomUtilities.RandomDoubleArray(shape.TotalLength, 20.0, 1.0, true), shape);
GradientCheck(fun, location, 1e-2);
}
public void TanhGradientCheck()
{
var x = new PlaceHolder <T>("x");
var fun = ConvNetSharp <T> .Instance.Tanh(x);
var shape = new Shape(2, 2, 3, 4);
var location = NewVolume(RandomUtilities.RandomDoubleArray(shape.TotalLength), shape);
GradientCheck(fun, location);
}
public void DivideGradientCheck()
{
var shape = new Shape(2, 2, 3, 4);
var location = NewVolume(RandomUtilities.RandomDoubleArray(shape.TotalLength), shape);
var x = new PlaceHolder <T>("x");
var z = new Const <T>(NewVolume(new double[shape.TotalLength].Populate(1.0), shape), "z");
GradientCheck(x / z, location, 1e-5);
GradientCheck(z / x, location, 1e-5);
}
public void SqrtGradientCheck()
{
var cns = new ConvNetSharp <T>();
var x = cns.PlaceHolder("x");
var fun = cns.Sqrt(x);
var shape = new Shape(2, 2, 3, 4);
var location = this.NewVolume(RandomUtilities.RandomDoubleArray(shape.TotalLength, posisitveOnly: true), shape);
this.GradientCheck(cns, fun, location);
}
public void TanhGradientCheck()
{
var cns = new ConvNetSharp <T>();
var x = cns.PlaceHolder("x");
var fun = cns.Tanh(x);
var shape = new Shape(2, 2, 3, 4);
var location = NewVolume(RandomUtilities.RandomDoubleArray(shape.TotalLength), shape);
GradientCheck(cns, fun, location);
}
public void LeakyReluGradientCheck()
{
var cns = new ConvNetSharp <T>();
var x = cns.PlaceHolder("x");
var fun = cns.LeakyRelu(x, (T)Convert.ChangeType(0.01, typeof(T)));
var shape = new Shape(2, 2, 3, 4);
var location = NewVolume(RandomUtilities.RandomDoubleArray(shape.TotalLength), shape);
GradientCheck(cns, fun, location, 1e-5);
}
public void SigmoidGradientCheck()
{
var cns = new ConvNetSharp <T>();
var x = cns.PlaceHolder("x");
var fun = cns.Sigmoid(x);
var shape = new Shape(2, 2, 3, 4);
var location = this.NewVolume(RandomUtilities.RandomDoubleArray(shape.TotalLength), shape);
this.GradientCheck(cns, fun, location, 1e-3);
}
public void SumGradientCheck()
{
var x = new PlaceHolder <T>("x");
var fun = ConvNetSharp <T> .Instance.Sum(x, new Shape(1, 1, 1, 4));
var shape = new Shape(2, 2, 3, 4);
var location = NewVolume(RandomUtilities.RandomDoubleArray(shape.TotalLength), shape);
var grad = NewVolume(new[] { 1.0, 1.0, 1.0, 1.0 }, new Shape(1, 1, 1, 4));
GradientCheck(fun, location, 1e-4, grad);
}
public void SubstractGradientCheck()
{
var shape = new Shape(2, 2, 3, 4);
var location = NewVolume(RandomUtilities.RandomDoubleArray(shape.TotalLength), shape);
var cns = new ConvNetSharp <T>();
var x = cns.PlaceHolder("x");
var z = cns.Const(NewVolume(new double[shape.TotalLength].Populate(1.0), shape), "z");
GradientCheck(cns, x - z, location);
GradientCheck(cns, z - x, location);
}
public void MatMultiplyGradientCheck()
{
var shape = new Shape(2, 2, 1, 4);
var location = NewVolume(RandomUtilities.RandomDoubleArray(shape.TotalLength), shape);
var cns = new ConvNetSharp <T>();
var x = cns.PlaceHolder("x");
var z = cns.Const(NewVolume(new double[shape.TotalLength].Populate(1.0), shape), "z");
GradientCheck(cns, cns.MatMult(x, z), location);
GradientCheck(cns, cns.MatMult(z, x), location);
}
public void PowerGradientCheck()
{
var cns = new ConvNetSharp <T>();
var shape = new Shape(2, 2, 3, 4);
var location = this.NewVolume(RandomUtilities.RandomDoubleArray(shape.TotalLength), shape);
var x = cns.PlaceHolder("x");
var z = cns.Const(this.NewVolume(new double[shape.TotalLength].Populate(2.0), shape), "z");
this.GradientCheck(cns, x ^ z, location);
this.GradientCheck(cns, z ^ x, location);
}
public void ConcatGradientCheck()
{
var leftShape = new Shape(2, 2, 1, 1);
var rightShape = new Shape(3, 1, 1, 1);
var cns = new ConvNetSharp <T>();
var location = NewVolume(RandomUtilities.RandomDoubleArray(leftShape.TotalLength), new Shape(2, 2, 1, 1));
var x = cns.PlaceHolder("x");
var z = cns.Const(NewVolume(new double[rightShape.TotalLength].Populate(1.0), rightShape), "z");
var fun = cns.Concat(x, z);
GradientCheck(cns, fun, location, 1e-5);
}
public void SumGradientCheck()
{
var cns = new ConvNetSharp <T>();
var x = cns.PlaceHolder("x");
var fun = cns.Sum(x, new Shape(1, 1, 1, 4));
var shape = new Shape(2, 2, 3, 4);
var location = this.NewVolume(RandomUtilities.RandomDoubleArray(shape.TotalLength), shape);
var grad = this.NewVolume(new[] { 1.0, 1.0, 1.0, 1.0 }, new Shape(1, 1, 1, 4));
this.GradientCheck(cns, fun, location, 1e-4, grad);
}
public void DropoutWith0Dropprob()
{
var volume = NewVolume(RandomUtilities.RandomDoubleArray(100), new Shape(100));
var result = NewVolume(new double[100], new Shape(100));
var dropprob = (T)Convert.ChangeType(0.0, typeof(T));
// Forward
volume.DoDropout(result, dropprob);
Assert.IsTrue(volume.ToArray().SequenceEqual(result.ToArray()));
// Backward
var inputGradient = BuilderInstance <T> .Volume.SameAs(volume.Storage, volume.Shape);
var outputActivationGradient = NewVolume(new double[100].Populate(1.0), new Shape(100));
result.DoDropoutGradient(volume, outputActivationGradient, inputGradient, dropprob);
Assert.IsTrue(inputGradient.ToArray().SequenceEqual(outputActivationGradient.ToArray()));
}
public override Volume <double> Random(Shape shape, double mu = 0, double std = 1.0)
{
return(new Volume(new VolumeStorage(RandomUtilities.RandomDoubleArray(shape.TotalLength, mu, std), shape, this.Context)));
}
