public void ConstructorTest1()
{
ConcatLayer layer = new ConcatLayer(
new Shape[] { ConcatLayerTest.inputShape1, ConcatLayerTest.inputShape2 });
CollectionAssert.AreEqual(ConcatLayerTest.outputShape.Axes, layer.OutputShape.Axes);
Assert.AreEqual("CONCAT", layer.Architecture);
}
public void CloneTest()
{
ConcatLayer layer1 = new ConcatLayer(
new Shape[] { ConcatLayerTest.inputShape1, ConcatLayerTest.inputShape2 });
ConcatLayer layer2 = layer1.Clone() as ConcatLayer;
Assert.AreEqual(JsonConvert.SerializeObject(layer1), JsonConvert.SerializeObject(layer2));
}
public void CopyConstructorTest1()
{
ConcatLayer layer1 = new ConcatLayer(
new Shape[] { ConcatLayerTest.inputShape1, ConcatLayerTest.inputShape2 });
ConcatLayer layer2 = new ConcatLayer(layer1);
Assert.AreEqual(JsonConvert.SerializeObject(layer1), JsonConvert.SerializeObject(layer2));
}
public void SerializeTest()
{
ConcatLayer layer1 = new ConcatLayer(
new Shape[] { ConcatLayerTest.inputShape1, ConcatLayerTest.inputShape2 });
string s1 = JsonConvert.SerializeObject(layer1);
ConcatLayer layer2 = JsonConvert.DeserializeObject <ConcatLayer>(s1);
string s2 = JsonConvert.SerializeObject(layer2);
Assert.AreEqual(s1, s2);
}
public void ArchitectureConstructorTest2()
{
string architecture = "CON";
try
{
ConcatLayer layer = new ConcatLayer(
new Shape[] { ConcatLayerTest.inputShape1, ConcatLayerTest.inputShape2 },
architecture,
null);
}
catch (ArgumentException e)
{
Assert.AreEqual(
new ArgumentException(string.Format(CultureInfo.InvariantCulture, Properties.Resources.E_InvalidLayerArchitecture, architecture), nameof(architecture)).Message,
e.Message);
throw;
}
}
public void ForwardBackwardTest()
{
ConcatLayer layer = new ConcatLayer(
new Shape[] { ConcatLayerTest.inputShape1, ConcatLayerTest.inputShape2 });
Tensor xTemp1 = new Tensor(null, ConcatLayerTest.inputShape1.Reshape(Axis.B, 1));
xTemp1.Set(ConcatLayerTest.weights1);
Tensor xTemp2 = new Tensor(null, ConcatLayerTest.inputShape2.Reshape(Axis.B, 1));
xTemp2.Set(ConcatLayerTest.weights2);
Tensor expectedTemp = new Tensor(null, new[] { 1, 2, 3, 5 });
expectedTemp.Set(new float[]
{
1, 11, 21, 31, 41, 2, 12, 22, 32, 42, 3, 13, 23, 33, 43,
4, 14, 24, 34, 44, 5, 15, 25, 35, 45, 6, 16, 26, 36, 46
});
for (int i = 1; i <= 3; i++)
{
Session session = new Session();
Tensor x1 = session.Tile(xTemp1, (int)Axis.B, i);
Tensor x2 = session.Tile(xTemp2, (int)Axis.B, i);
Tensor y = layer.Forward(session, new[] { x1, x2 })[0];
Tensor expected = session.Tile(expectedTemp, (int)Axis.B, i);
Helpers.AreTensorsEqual(expected, y);
// unroll the graph
Array.Copy(y.Weights, y.Gradient, y.Length);
session.Unroll();
Helpers.AreArraysEqual(x1.Length, x1.Weights, x1.Gradient);
Helpers.AreArraysEqual(x2.Length, x2.Weights, x2.Gradient);
}
}
