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);
}
