コード例 #1
0
 public void CanCalculateBackProp__Given__LayersOfVariousSizes(double[] inputs, double[] inputToHiddenWeights, double[] hiddenToOutputWeights, double target)
 {
     var net              = NNSigmoid.FromFlatWeightArrays(inputs.Length, inputToHiddenWeights, hiddenToOutputWeights);
     var input            = new MatrixD(inputs.Length, 1, inputs);
     var outSize          = hiddenToOutputWeights.Length * inputs.Length / inputToHiddenWeights.Length;
     var targets          = new MatrixD(outSize, 1, target);
     var calculatedDeltas = net.backprop(input, targets);
 }
コード例 #2
0
        public void Given__223_SigmoidNetwork(double[] inputs, double[] inputToHiddenWeights, double[] hiddenToOutputWeights, double target)
        {
            var net              = NNSigmoid.FromFlatWeightArrays(inputs.Length, inputToHiddenWeights, hiddenToOutputWeights);
            var input            = new MatrixD(inputs.Length, 1, inputs);
            var targets          = new MatrixD(3, 1, target);
            var calculatedDeltas = net.backprop(input, targets);

            var exOutputDelta1 = -0.040681125112339026d;
            var exOutputDelta2 = hiddenToOutputWeights[1].Equals(0) ? 0 : exOutputDelta1;
            var exOutputDelta3 = hiddenToOutputWeights[2].Equals(0) ? 0 : exOutputDelta1;

            var exHiddenDelta00 = -0.0023685025015371172d;
            var exHiddenDelta01 = -0.0075927347073177845d;

            //calculatedDeltas.Item1.First().ShouldEqualByValue(expectedDeltas.HiddenWeights);
            //calculatedDeltas.Item1.Last().ShouldEqualByValue(expectedDeltas.OutputWeights);
            calculatedDeltas.Item2.First().ShouldEqualByValue(new MatrixD(2, 1, 0));
            calculatedDeltas.Item2.Last().ShouldEqualByValue(new MatrixD(3, 1, 0));
        }
コード例 #3
0
        public void Given__221_SigmoidNetwork(double[] inputs, double[] inputToHiddenWeights, double[] hiddenToOutputWeights, double target)
        {
            var net              = NNSigmoid.FromFlatWeightArrays(inputs.Length, inputToHiddenWeights, hiddenToOutputWeights);
            var input            = new MatrixD(inputs.Length, 1, inputs);
            var targets          = new MatrixD(1, 1, target);
            var calculatedDeltas = net.backprop(input, targets);

            /*
             * 0.680267196698649d, 0.663738697404353d, 0.690283492907644d
             */
            var output         = net.feedforward(input);
            var exOutputDelta  = -0.040681125112339026d;
            var exHiddenDelta0 = -0.0023685025015371172d;
            var exHiddenDelta1 = -0.0075927347073177845d;

            var expectedDeltaValues = new
            {
                OutputBiases = new MatrixD(1, 1, exOutputDelta),
                HiddenBiases = new MatrixD(2, 1, new [] { -0.00260919207722715d, -0.00782757623168145d }),

                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
                }),

                HiddenWeights = new MatrixD(
                    new[, ] {
                    { -0.000913217227029503d, -0.0026574571475612243d },
                    { -0.0021316522513834054d, -0.0068334612365860059d }
                }),
            };

            //
            calculatedDeltas.Item2.Last().ShouldEqualByValue(expectedDeltaValues.OutputBiases, "OutputBiases");
            calculatedDeltas.Item1.Last().ShouldEqualByValue(expectedDeltaValues.OutputWeights, "OutputWeights");
            calculatedDeltas.Item2.First().ShouldEqualByValue(expectedDeltaValues.HiddenBiases, "HiddenBiases");
            calculatedDeltas.Item1.First().ShouldEqualByValue(expectedDeltaValues.HiddenWeights, "HiddenWeights");
        }