public void TestConstructor()
{
LayerStub prevLayer = new LayerStub(4, 4, 2);
MaxPoolingLayer layer = new MaxPoolingLayer(2, 2, prevLayer);
Assert.AreEqual(2, layer.Width);
Assert.AreEqual(2, layer.Height);
Assert.AreEqual(prevLayer.Depth, layer.Depth);
}
public void TestCalculateErrorByOutputGradient()
{
LayerStub prevLayer = new LayerStub(4, 4, 2);
MaxPoolingLayer layer = new MaxPoolingLayer(2, 2, prevLayer);
//PrivateObject obj = new PrivateObject(layer);
//int[] maxIndices = new[] { 5, 7, 13, 15 };
//for (int fNIdx = 0; fNIdx < prevLayer.Neurons; fNIdx++) {
// for (int tNIdx = 0; tNIdx < layer.Neurons; tNIdx++) {
// float weight = (float)obj.Invoke("GetWeight", maxIndices, fNIdx, tNIdx);
// }
//}
}
public void TestFeedForward()
{
float[] data = new float[4 * 4 * 2];
for (int i = 0; i < data.Length; i++)
{
data[i] = i + 1;
}
LayerStub prevLayer = new LayerStub(4, 4, 2);
MaxPoolingLayer layer = new MaxPoolingLayer(2, 2, prevLayer);
NNFeedData feedData = new NNFeedData(4, 4, 2, data);
NNDetailedFeedData result = layer.FeedForward(feedData);
Assert.AreEqual(6, result.OutputData[result.OutputData.ToNeuronIndex(0, 0, 0)]);
Assert.AreEqual(8, result.OutputData[result.OutputData.ToNeuronIndex(1, 0, 0)]);
Assert.AreEqual(14, result.OutputData[result.OutputData.ToNeuronIndex(0, 1, 0)]);
Assert.AreEqual(16, result.OutputData[result.OutputData.ToNeuronIndex(1, 1, 0)]);
}
