public void BackPropagateIsCorrect()
{
int numberOfBanks = 3;
Layer layer = new Layer(new WeightsMatrix(new double[, ] {
{ 1 }
}));
LayerBank bank = new LayerBank(layer, numberOfBanks);
NetworkVector inputVector = new NetworkVector(new double[] { 1, 2, 3 });
NetworkVector bpVector = new NetworkVector(new double[] { 5, 7, 11 });
bank.Run(inputVector);
NetworkVector inputGradientCheck = new NetworkVector(new double[] { 5, 7, 11 });
Assert.AreEqual(inputGradientCheck, bank.InputGradient(bpVector));
bank.BackPropagate(bpVector, inputVector);
bank.Update(new GradientDescent());
WeightsMatrix weightsCheck = new WeightsMatrix(new double[, ] {
{ -51 }
});
NetworkVector biasCheck = new NetworkVector(new double[] { -23 });
Assert.AreEqual(biasCheck, bank.Biases);
Assert.AreEqual(weightsCheck, bank.Weights);
}
public void CannotBackPropagateLayerBankWithBadOutputGradientSize()
{
int numberOfBanks = 3;
Layer layer = new Layer(new WeightsMatrix(new double[, ] {
{ 1 }
}));
LayerBank bank = new LayerBank(layer, numberOfBanks);
NetworkVector badGradient = new NetworkVector(2);
try
{
bank.BackPropagate(badGradient, new NetworkVector(3));
Assert.Fail("LayerBank.BackPropagate failed to throw an ArgumentException for outputgradient of the wrong size.");
}
catch (ArgumentException) { }
}
