Beispiel #1
0
        public void TestForward()
        {
            var parameterGenerator = new ActionParameterGenerator(() => 0.1, () => 1.0);
            var neuronFactor       = new NeuronFactory(parameterGenerator);
            var synapseFactory     = new SynapseFactory(parameterGenerator);
            var n = NetworkFactory.CreateMultilayerPerceptron(new[] { 2, 2, 1 }, ActivationFunction.Sigmoid,
                                                              ActivationFunction.Identity, null, neuronFactor, synapseFactory);
            var x = new Vector(3, 5);

            Assert.IsTrue(Math.Abs(n.Compute(x)[0] - 2.0993931) < 0.001);
        }
Beispiel #2
0
        public void TestBack()
        {
            var parameterGenerator = new ActionParameterGenerator(() => 0.1, () => 1.0);
            var neuronFactor       = new NeuronFactory(parameterGenerator);
            var synapseFactory     = new SynapseFactory(parameterGenerator);
            var network            = NetworkFactory.CreateMultilayerPerceptron(new[] { 2, 2, 1, 1 }, ActivationFunction.Sigmoid,
                                                                               ActivationFunction.Identity, null, neuronFactor, synapseFactory);
            var networkTrainer = new NetworkTrainer(network);
            var x = new Vector(3, 5);

            network.Compute(x);
            networkTrainer.Back(42.0);

            var n = network.OutputLayer[0].Inputs[0].Source;

            Console.WriteLine(n.InputDerivative);
            Console.WriteLine(n.OutputDerivative);
            Console.WriteLine(n.InputDerivativeCount);

            Assert.IsTrue(Math.Abs(-3.987764 - n.InputDerivative) < 0.01);
            Assert.IsTrue(Math.Abs(-41.009155 - n.OutputDerivative) < 0.01);
            Assert.AreEqual(1, n.InputDerivativeCount);
        }