public void DerivativeNxorNoRegularizationTest()
{
var net = NetBuilder.CreateNxorNet();
var inputs = DenseMatrix.OfArray(new double[, ] {
{ 0, 0 }, { 1, 1 }
});
var outputIndices = new int[] { 0, 0 };
net.CostFunction.SetInputsOutputs(inputs, outputIndices, 0);
int dims = net.CostFunction.DimensionsCount;
var rand = new Random(0);
FunctionDerivativeTester.PerformDerivativeTest(net.CostFunction,
Enumerable.Range(0, 100).Select(x =>
Enumerable.Range(0, dims).Select(y => rand.NextDouble() * 10 - 5).ToArray()
).ToArray()
);
}
public void EvaluateAndNandNoRegularizationTest()
{
var net = NetBuilder.CreateAndNandNet();
var func = net.CostFunction;
var inputs = DenseMatrix.OfArray(new double[, ] {
{ 0, 0 }, { 0, 1 }, { 1, 0 }, { 1, 1 }
});
{
var outputIndices = new int[] { 1, 1, 1, 0 };
func.SetInputsOutputs(inputs, outputIndices, 0);
double value = func.Evaluate(net.Coefficients.Pack());
Assert.IsTrue(value < 0.001);
}
{
var outputIndices = new int[] { 0, 0, 0, 1 };
func.SetInputsOutputs(inputs, outputIndices, 0);
double value = func.Evaluate(net.Coefficients.Pack());
Assert.IsTrue(value > 10);
}
}