public void AllocateArrayOfArraysTest() { var result = ArrayAllocatorUtils.Allocate <double>(2, 3); Assert.AreEqual(2, result.Length); for (int i = 0; i < 2; i++) { Assert.AreEqual(3, result[i].Length); } }
public NeuralNet(NeuralNetParameters parameters) { wagesBetweenInputAndFirstHiddenLayer = ArrayAllocatorUtils.Allocate <double>(parameters.InputLayerSize, parameters.HiddenLayerSize); wagesBetweenHiddenLayers = ArrayAllocatorUtils.Allocate <double>(parameters.NumberOfHiddenLayers - 1, parameters.HiddenLayerSize, parameters.HiddenLayerSize); wagesBetweenLastHiddenAndOutputLayer = ArrayAllocatorUtils.Allocate <double>(parameters.HiddenLayerSize, parameters.OutputLayerSize); biasesInHiddenLayers = ArrayAllocatorUtils.Allocate <double>(parameters.NumberOfHiddenLayers, parameters.HiddenLayerSize); biasesInOutputLayer = ArrayAllocatorUtils.Allocate <double>(parameters.OutputLayerSize); this.activationFunctionType = parameters.ActivationFunctionType; activationFunction = ActivationFunctionFactory.Get(activationFunctionType); }
public void RandomizeArrayOfArraysTest() { var array = ArrayAllocatorUtils.Allocate <double>(2, 3); array.Randomize(-1.0, 1.0); foreach (var a in array) { foreach (var element in a) { Assert.AreNotEqual(element, 0.0); Assert.GreaterOrEqual(element, -1.0); Assert.LessOrEqual(element, 1.0); } } }
public void AllocateArrayTest() { var result = ArrayAllocatorUtils.Allocate <double>(2); Assert.AreEqual(2, result.Length); }