public void ForwardBackwardTest()
{
var input = new TensorOld(new double[]
{
4, 6, 1, 4,
8, 4, 5, 1,
5, 3, 5, 7,
1, 7, 2, 8,
}, 1, 1, 4, 4);
var conv = new ConvLayer(4, 2, 1, 1);
conv.SetFilters(new TensorOld(new double[]
{
1, 1, 0, 0,
0, 0, 1, 1,
1, 0, 1, 0,
0, 1, 0, 1,
}, 4, 1, 2, 2));
var expected = new TensorOld(new double[]
{
0, 0, 0, 0, 0,
4, 10, 7, 5, 4,
8, 12, 9, 6, 1,
5, 8, 8, 12, 7,
1, 8, 9, 10, 8,
4, 10, 7, 5, 4,
8, 12, 9, 6, 1,
5, 8, 8, 12, 7,
1, 8, 9, 10, 8,
0, 0, 0, 0, 0,
0, 4, 6, 1, 4,
0, 12, 10, 6, 5,
0, 13, 7, 10, 8,
0, 6, 10, 7, 15,
0, 1, 7, 2, 8,
4, 6, 1, 4, 0,
12, 10, 6, 5, 0,
13, 7, 10, 8, 0,
6, 10, 7, 15, 0,
1, 7, 2, 8, 0,
}, 1, 4, 5, 5);
conv.PrepareTrain(input);
var acutal = conv.Forward(input);
Assert.Equal(acutal, expected);
var error = expected / 10;
var back = conv.Backward(error);
}
public void ConvLayerStorageTest()
{
var doc = new XmlDocument();
var layer = new ConvLayer(3, 2, 1, 1);
layer.SetFilters(new TensorOld(
new double[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 }, 3, 1, 2, 2));
layer.SetBias(new TensorOld(new double[] { 1, 2, 3 }));
var el = XmlStorage.SaveToEl(doc, layer);
var test = XmlStorage.LoadFromNode <ConvLayer>(el);
Assert.True(test is ConvLayer);
Assert.Equal(layer.PaddingValue, test.PaddingValue);
Assert.Equal(layer.FilterRows, test.FilterRows);
Assert.Equal(layer.FilterColumns, test.FilterColumns);
Assert.Equal(layer.RowStride, test.RowStride);
Assert.Equal(layer.ColumnStride, test.ColumnStride);
Assert.Equal(layer.Filters, test.Filters);
Assert.Equal(layer.Bias, test.Bias);
}
