public void ActivateAll()
{
layerToTest.ActivateNeurons();
foreach (Neuron inputNeuron in layerToTest.Neurons)
{
Assert.AreEqual(1, inputNeuron.Activation);
}
}
public void Scaffold_Testing_Layer()
{
activator = new ReLU();
layerToTest = new Layer(5);
learningRate = 0.01;
layerToTest.InputToNeurons(neuronInput);
testOutputLayer = new Layer(5, layerToTest, activator, 2); // generates a layer with all its neurons taking in the previous layer as inputs!
// Essentially, this layer becomes the output to the previous layer
// If this creation of the output layer worked, then by backpropping one of the neurons, all the previous neurons' errors should be 2
testOutputLayer.InputToNeurons(neuronInput);
testOutputLayer.ActivateNeurons();
testOutputLayer.SetErrorNeurons(expectedOutput);
}
