public void Given__ExampleWeightsFor221Net__HasExpectedFiringRatesAndOutput(double[] inputs, double[] inputToHidden, double[] hiddenToOutput, double expectedH0, double expectedH1, double expectedOutput)
{
var net = NeuralNet3LayerSigmoid.FromFlatWeightArrays(2, inputToHidden, hiddenToOutput);
//
net.ActivateInputs(inputs);
net.HiddenLayer[0].FiringRate.ShouldBe(expectedH0, "Hidden 0 Firing Rate");
net.HiddenLayer[1].FiringRate.ShouldBe(expectedH1, "Hidden 1 Firing Rate");
net.OutputLayer[0].FiringRate.ShouldBe(expectedOutput, "Output 0 Firing Rate");
net.OutputFor(inputs).ShouldBe(new ZeroToOne[] { expectedOutput });
}
public void Given__a221Network(double[] inputs, double[] inputToHidden, double[] hiddenToOutput)
{
var net = NeuralNet3LayerSigmoid.FromFlatWeightArrays(inputs.Length, inputToHidden, hiddenToOutput);
net.InputToHidden[0, 0].ShouldBe(inputToHidden[0], "inputToHidden[0,0]");
net.InputToHidden[0, 1].ShouldBe(inputToHidden[1], "inputToHidden[0,1]");
net.InputToHidden[1, 0].ShouldBe(inputToHidden[2 + 0], "inputToHidden[1,0]");
net.InputToHidden[1, 1].ShouldBe(inputToHidden[2 + 1], "inputToHidden[1,1]");
net.HiddenToOutput.ShouldEqualByValue(new MatrixD(new[, ] {
{ hiddenToOutput[0] }, { hiddenToOutput[1] }
}), "HiddenToOutput");
}
public void Given__a323Network(double[] inputs, double[] inputToHidden, double[] hiddenToOutput)
{
var net = NeuralNet3LayerSigmoid.FromFlatWeightArrays(inputs.Length, inputToHidden, hiddenToOutput);
net.InputToHidden[0, 0].ShouldBe(inputToHidden[0]);
net.InputToHidden[0, 1].ShouldBe(inputToHidden[1]);
net.InputToHidden[1, 0].ShouldBe(inputToHidden[2 + 0]);
net.InputToHidden[1, 1].ShouldBe(inputToHidden[2 + 1]);
net.InputToHidden[2, 0].ShouldBe(inputToHidden[4 + 0]);
net.InputToHidden[2, 1].ShouldBe(inputToHidden[4 + 1]);
net.HiddenToOutput[0, 0].ShouldBe(hiddenToOutput[0]);
net.HiddenToOutput[0, 1].ShouldBe(hiddenToOutput[1]);
net.HiddenToOutput[0, 2].ShouldBe(hiddenToOutput[2]);
net.HiddenToOutput[1, 0].ShouldBe(hiddenToOutput[3 + 0]);
net.HiddenToOutput[1, 1].ShouldBe(hiddenToOutput[3 + 1]);
net.HiddenToOutput[1, 2].ShouldBe(hiddenToOutput[3 + 2]);
net.HiddenLayer.ShouldAll(n => n.Bias.ShouldBe(0));
net.OutputLayer.ShouldAll(n => n.Bias.ShouldBe(0));
}
public void Given__223_SigmoidNetwork(double[] inputs, double[] inputToHiddenWeights, double[] hiddenToOutputWeights, double target)
{
var net = NeuralNet3LayerSigmoid.FromFlatWeightArrays(inputs.Length, inputToHiddenWeights, hiddenToOutputWeights);
var targets = Enumerable.Range(0, net.OutputLayer.Length).Select(i => (ZeroToOne)target);
var calculatedDeltas = BackPropagationWithGradientDescent.DeltasFor(net, inputs, targets);
var exOutputDelta1 = -0.040681125112339026d;
var exOutputDelta2 = hiddenToOutputWeights[1].Equals(0) ? 0 : exOutputDelta1;
var exOutputDelta3 = hiddenToOutputWeights[2].Equals(0) ? 0 : exOutputDelta1;
var expected = new DeltasFor2LayersOfNet
{
OutputBiases = new[] { 0d, 0d, 0d },
OutputWeights = new MatrixD(
new[, ]
{
{ exOutputDelta1 *net.HiddenLayer[0].FiringRate, exOutputDelta2 *net.HiddenLayer[0].FiringRate, exOutputDelta3 *net.HiddenLayer[0].FiringRate },
{ exOutputDelta1 *net.HiddenLayer[1].FiringRate, exOutputDelta2 *net.HiddenLayer[1].FiringRate, exOutputDelta3 *net.HiddenLayer[1].FiringRate }
}),
};
calculatedDeltas.OutputWeights.ShouldEqualByValue(expected.OutputWeights);
calculatedDeltas.OutputBiases.ShouldEqualByValue(expected.OutputBiases);
}
public void Given__221_SigmoidNetwork(double[] inputs, double[] inputToHiddenWeights, double[] hiddenToOutputWeights, double target)
{
var net = NeuralNet3LayerSigmoid.FromFlatWeightArrays(inputs.Length, inputToHiddenWeights, hiddenToOutputWeights);
var targets = Enumerable.Range(0, net.OutputLayer.Length).Select(i => (ZeroToOne)target);
var calculatedDeltas = BackPropagationWithGradientDescent.DeltasFor(net, inputs, targets);
/*
* 0.680267196698649d, 0.663738697404353d, 0.690283492907644d
*/
var exOutputDelta = -0.040681125112339026d;
var expected = new DeltasFor2LayersOfNet
{
OutputBiases = new[] { 0d },
OutputWeights = new MatrixD(
new[, ]
{
{ exOutputDelta *net.HiddenLayer[0].FiringRate },
{ exOutputDelta *net.HiddenLayer[1].FiringRate }
}),
};
calculatedDeltas.OutputWeights.ShouldEqualByValue(expected.OutputWeights);
calculatedDeltas.OutputBiases.ShouldEqualByValue(expected.OutputBiases);
}
public void Given__221_SigmoidNetwork(double[] inputs, double[] inputToHiddenWeights, double[] hiddenToOutputWeights, double target)
{
var net = NeuralNet3LayerSigmoid.FromFlatWeightArrays(inputs.Length, inputToHiddenWeights, hiddenToOutputWeights);
var targets = Enumerable.Range(0, net.OutputLayer.Length).Select(i => (ZeroToOne)target);
var calculatedDeltas = BackPropagationWithGradientDescent.DeltasFor(net, inputs, targets);
/*
* 0.680267196698649d, 0.663738697404353d, 0.690283492907644d
*/
var outputs = net.LastOutputs.ToArray();
var exOutputDelta = -0.040681125112339026d;
var exHiddenDelta0 = -0.0023685025015371172d;
var exHiddenDelta1 = -0.0075927347073177845d;
var expectedOutputDeltas = new DeltasFor2LayersOfNet
{
OutputBiases = new[] { 0d },
OutputWeights = new MatrixD(
new[, ]
{
{ exOutputDelta *net.HiddenLayer[0].FiringRate },
{ exOutputDelta *net.HiddenLayer[1].FiringRate }
}),
HiddenBiases = new [] { 0d, 0d },
HiddenWeights = new MatrixD(
new[, ]
{
{
exHiddenDelta0 *net.HiddenLayer[0].Inputs[0].Source.FiringRate,
exHiddenDelta1 *net.HiddenLayer[1].Inputs[0].Source.FiringRate
},
{
exHiddenDelta0 *net.HiddenLayer[0].Inputs[1].Source.FiringRate,
exHiddenDelta1 *net.HiddenLayer[1].Inputs[1].Source.FiringRate
}
}),
};
var expectedDeltaValues = new DeltasFor2LayersOfNet
{
OutputBiases = new[] { 0d },
OutputWeights = new MatrixD(
new[, ]
{
{ -0.027674034938717864 }, // -0.040681125112339026d * 0.680267196698649d +/- last two d.p.s
{ -0.027001636991007407 } // -0.040681125112339026d * 0.663738697404353d +/- last two d.p.s
}),
HiddenBiases = new[] { 0d, 0d },
HiddenWeights = new MatrixD(
new[, ]
{
{
-0.000828975875537991d,
-0.0026574571475612243d
},
{
-0.0021316522513834054d,
-0.0068334612365860059d
}
}),
};
calculatedDeltas.OutputWeights.ShouldEqualByValue(expectedOutputDeltas.OutputWeights, "OutputWeights");
calculatedDeltas.OutputBiases.ShouldEqualByValue(expectedOutputDeltas.OutputBiases, "OutputBiases");
calculatedDeltas.HiddenWeights.ShouldEqualByValue(expectedOutputDeltas.HiddenWeights, "HiddenWeights");
calculatedDeltas.HiddenBiases.ShouldEqualByValue(expectedOutputDeltas.HiddenBiases, "HiddenBiases");
//
expectedOutputDeltas.HiddenBiases.ShouldEqualByValue(expectedDeltaValues.HiddenBiases, "HiddenBiases");
expectedOutputDeltas.OutputBiases.ShouldEqualByValue(expectedDeltaValues.OutputBiases, "OutputBiases");
expectedOutputDeltas.HiddenWeights.ShouldEqualByValue(expectedDeltaValues.HiddenWeights, "HiddenWeights");
expectedOutputDeltas.OutputWeights.ShouldEqualByValue(expectedDeltaValues.OutputWeights, "OutputWeights");
}