public void ModelGradients3()
{
Matrix <double> in_hid = Matrix <double> .Build.DenseOfArray(
new double[, ] {
{ 1 }, { 2 }
}
);
Matrix <double> hid_class = Matrix <double> .Build.DenseOfArray(
new double[, ] {
{ 1, 0 }, { 0, 1 }
}
);
Matrix <double> input = Matrix <double> .Build.DenseOfArray(
new double[, ] {
{ 1 }
}
);
Matrix <double> target = Matrix <double> .Build.DenseOfArray(
new double[, ] {
{ 1 }, { 0 }
}
);
MutableTypes.Model networkModel = new MutableTypes.Model(in_hid, hid_class);
MutableTypes.NetworkState networkState = NetRun.RunNetwork(networkModel, input);
MutableTypes.Model gradients = Training._getModelGradients(networkModel, networkState, target);
double l1 = NetworkFunctions.Logistic(1);
double l2 = NetworkFunctions.Logistic(2);
double el1 = Math.Exp(l1);
double el2 = Math.Exp(l2);
double N = el1 + el2;
double el1N = el1 / N;
double el2N = el2 / N;
double ld1 = NetworkFunctions.LogisticDerivative_f_output(l1);
double ld2 = NetworkFunctions.LogisticDerivative_f_output(l2);
Matrix <double> hid_class_gradient_check = Matrix <double> .Build.DenseOfArray(
new double[, ] {
{ l1 *(el1N - 1), l2 *(el1N - 1) }, { l1 *el2N, l2 *el2N }
}
);
Matrix <double> in_hid_gradient_check = Matrix <double> .Build.DenseOfArray(
new double[, ] {
{ ld1 *(el1N - 1) }, { ld2 *el2N }
}
);
Assert.AreEqual(hid_class_gradient_check, gradients.HiddenToClassifier);
Assert.AreEqual(in_hid_gradient_check, gradients.InputToHidden);
}
public void ModelGradients2()
{
Matrix <double> in_hid = Matrix <double> .Build.DenseOfArray(
new double[, ] {
{ 1 }
}
);
Matrix <double> hid_class = Matrix <double> .Build.DenseOfArray(
new double[, ] {
{ 1 }, { 1 }
}
);
Matrix <double> input = Matrix <double> .Build.DenseOfArray(
new double[, ] {
{ 1 }
}
);
Matrix <double> target = Matrix <double> .Build.DenseOfArray(
new double[, ] {
{ 1 }, { 0 }
}
);
MutableTypes.Model networkModel = new MutableTypes.Model(in_hid, hid_class);
MutableTypes.NetworkState networkState = NetRun.RunNetwork(networkModel, input);
MutableTypes.Model gradients = Training._getModelGradients(networkModel, networkState, target);
Matrix <double> hid_class_gradient_check = Matrix <double> .Build.DenseOfArray(
new double[, ] {
{ -NetworkFunctions.Logistic(1) / 2 }, { NetworkFunctions.Logistic(1) / 2 }
}
);
Matrix <double> in_hid_gradient_check = Matrix <double> .Build.DenseOfArray(
new double[, ] {
{ 0 }
}
);
Assert.AreEqual(hid_class_gradient_check, gradients.HiddenToClassifier);
Assert.AreEqual(in_hid_gradient_check, gradients.InputToHidden);
}
