public void Shape()
{
var cns = new ConvNetSharp <double>();
var x = cns.Const(1.0, "x");
var op = cns.Shape(x);
var xml = op.ToXml();
var deserialized = SerializationExtensions.FromXml <double>(xml) as Shape <double>;
Assert.IsNotNull(deserialized);
Assert.AreEqual(1, deserialized.Parents.Count);
Assert.AreEqual("x", (deserialized.Parents[0] as Const <double>).Name);
}
public void Dropout()
{
var cns = new ConvNetSharp <double>();
var x = cns.Const(1.0, "x");
var dropoutProbability = 0.5;
var op = cns.Dropout(x, dropoutProbability);
var xml = op.ToXml();
var deserialized = SerializationExtensions.FromXml <double>(xml) as Dropout <double>;
Assert.IsNotNull(deserialized);
Assert.AreEqual(dropoutProbability, ((Const <double>)deserialized.DropoutProbability).Value);
}
public void Sqrt()
{
var cns = new ConvNetSharp <double>();
var a = cns.Const(9.0, "input");
var op = cns.Sqrt(a);
var xml = op.ToXml();
var deserialized = SerializationExtensions.FromXml <double>(xml) as Sqrt <double>;
Assert.IsNotNull(deserialized);
Assert.AreEqual(1, deserialized.Parents.Count);
Assert.AreEqual("input", (deserialized.Parents[0] as Const <double>).Name);
}
public void LeakyRelu()
{
var cns = new ConvNetSharp <double>();
var a = cns.Const(1.0, "one");
var op = cns.LeakyRelu(a, 0.01);
var xml = op.ToXml();
var deserialized = SerializationExtensions.FromXml <double>(xml) as LeakyRelu <double>;
Assert.IsNotNull(deserialized);
Assert.AreEqual(1, deserialized.Parents.Count);
Assert.AreEqual("one", (deserialized.Parents[0] as Const <double>).Name);
}
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 = this.NewVolume(RandomUtilities.RandomDoubleArray(leftShape.TotalLength), new Shape(2, 2, 1, 1));
var x = cns.PlaceHolder("x");
var z = cns.Const(this.NewVolume(new double[rightShape.TotalLength].Populate(1.0), rightShape), "z");
var fun = cns.Concat(x, z);
this.GradientCheck(cns, fun, location, 1e-5);
}
public void Activation()
{
var cns = new ConvNetSharp <double>();
var x = cns.Const(1.0, "x");
var op = new Activation <double>(cns, x, ActivationType.Relu);
var xml = op.ToXml();
var deserialized = SerializationExtensions.FromXml <double>(xml) as Activation <double>;
Assert.IsNotNull(deserialized);
Assert.AreEqual(1, deserialized.Parents.Count);
Assert.AreEqual("x", (deserialized.Parents[0] as Const <double>).Name);
Assert.AreEqual(ActivationType.Relu, deserialized.Type);
}
public void AddOpBackward()
{
var cns = new ConvNetSharp <double>();
var volA = cns.Const(BuilderInstance <double> .Volume.SameAs(new Shape(1, 1, 3, 5)), "A");
var volB = cns.Const(BuilderInstance <double> .Volume.From(new[] { 1.0, 2.0, 3.0 }, new Shape(1, 1, 3, 1)), "bias");
var op = volA + volB;
using var session = new Session <double>();
var eval = op.Evaluate(session);
Assert.IsNotNull(eval);
op.Derivate = cns.Const(BuilderInstance <double> .Volume.From(new double[15].Populate(1.0), new Shape(1, 1, 3, 5)), "error");
op.Differentiate();
var volADiff = volA.Derivate.Evaluate(session);
Assert.AreEqual(volA.Result.Shape, volADiff.Shape);
var volBDiff = volB.Derivate.Evaluate(session);
Assert.AreEqual(volB.Result.Shape, volBDiff.Shape);
}
public void SumOpBatch()
{
var cns = new ConvNetSharp <T>();
var x = cns.Const(NewVolume(new[]
{
1.0, 2.0, 3.0,
4.0, 5.0, 6.0
}, new Shape(3, 1, 1, 2)), "x");
var op = cns.Sum(x, new Shape(1, 1, 1, 2));
using (var session = new Session <T>())
{
var result = op.Evaluate(session);
AssertNumber.AreEqual(6.0, result.Get(0));
AssertNumber.AreEqual(15.0, result.Get(1));
}
}
public void Dense()
{
var cns = new ConvNetSharp <double>();
var x = cns.Const(1.0, "x");
var op = new Dense <double>(cns, x, 16);
var xml = op.ToXml();
var deserialized = SerializationExtensions.FromXml <double>(xml) as Dense <double>;
Assert.IsNotNull(deserialized);
Assert.AreEqual(2, deserialized.Parents.Count); // input and filters
Assert.AreEqual("x", (deserialized.Parents[0] as Const <double>).Name);
Assert.AreEqual(1, deserialized.Width);
Assert.AreEqual(1, deserialized.Height);
Assert.AreEqual(16, deserialized.FilterCount);
Assert.AreEqual(1, deserialized.Stride);
Assert.AreEqual(0, deserialized.Pad);
}
public void Pool()
{
var cns = new ConvNetSharp <double>();
var x = cns.Const(1.0, "x");
var op = cns.Pool(x, 3, 4, 1, 2, 1, 2);
var xml = op.ToXml();
var deserialized = SerializationExtensions.FromXml <double>(xml) as Pool <double>;
Assert.IsNotNull(deserialized);
Assert.AreEqual(1, deserialized.Parents.Count);
Assert.AreEqual("x", (deserialized.Parents[0] as Const <double>).Name);
Assert.AreEqual(3, deserialized.Width);
Assert.AreEqual(4, deserialized.Height);
Assert.AreEqual(1, deserialized.HorizontalPad);
Assert.AreEqual(2, deserialized.VerticalPad);
Assert.AreEqual(1, deserialized.HorizontalStride);
Assert.AreEqual(2, deserialized.VerticalStride);
}