public void EnumGradientsTest()
{
Shape shape = new Shape(new int[] { 1, 20, 20, 10 });
GRULayer layer = new GRULayer(shape, RNNDirection.ForwardOnly, new[] { 20, 30 }, MatrixLayout.ColumnMajor, null);
Assert.AreEqual(5, layer.EnumGradients().Count());
}
public void Test_GRU_WrongSizeinWidth_Weights()
{
Data2D weights = new Data2D(1, 3, 5, 4);
GRULayer rnn = new GRULayer(5, 3, TanHLayer.TanHLambda, p => { });
rnn.SetWeights(weights);
}
public void Test_GRU_Null_Weights()
{
Data2D weights = null;
GRULayer rnn = new GRULayer(5, 3, TanHLayer.TanHLambda, TanHLayer.TanHLambda);
rnn.SetWeights(weights);
}
public void CloneTest()
{
Shape shape = new Shape(new int[] { -1, 20, 20, 10 });
GRULayer layer1 = new GRULayer(shape, RNNDirection.ForwardOnly, new[] { 2, 3 }, MatrixLayout.ColumnMajor, null);
GRULayer layer2 = layer1.Clone() as GRULayer;
Assert.AreEqual(JsonConvert.SerializeObject(layer1), JsonConvert.SerializeObject(layer2));
}
public void CopyConstructorTest1()
{
Shape shape = new Shape(new int[] { -1, 20, 20, 10 });
GRULayer layer1 = new GRULayer(shape, RNNDirection.ForwardOnly, new[] { 20, 20 }, MatrixLayout.ColumnMajor, null);
GRULayer layer2 = new GRULayer(layer1);
Assert.AreEqual(JsonConvert.SerializeObject(layer1), JsonConvert.SerializeObject(layer2));
}
public void Test_GRU_DifferentData_Input()
{
DataArray data = new DataArray(5);
Data2D weights = new Data2D(1, 5, 5, 3);
GRULayer rnn = new GRULayer(5, 3, TanHLayer.TanHLambda, p => { });
rnn.SetWeights(weights);
rnn.SetInput(data);
}
public void Test_GRU_Null_Input()
{
Data2D data = null;
Data2D weights = new Data2D(1, 5, 5, 3);
GRULayer rnn = new GRULayer(5, 3, TanHLayer.TanHLambda, TanHLayer.TanHLambda);
rnn.SetWeights(weights);
rnn.SetInput(data);
}
public void SerializeTest()
{
Shape shape = new Shape(new int[] { -1, 20, 20, 10 });
GRULayer layer1 = new GRULayer(shape, RNNDirection.ForwardOnly, new[] { 2, 3 }, MatrixLayout.ColumnMajor, null);
string s1 = JsonConvert.SerializeObject(layer1);
GRULayer layer2 = JsonConvert.DeserializeObject <GRULayer>(s1);
string s2 = JsonConvert.SerializeObject(layer2);
Assert.AreEqual(s1, s2);
}
public void ConstructorTest1()
{
Shape shape = new Shape(new int[] { 1, 10, 12, 3 });
GRULayer layer = new GRULayer(shape, RNNDirection.ForwardOnly, new[] { 20, 30 }, MatrixLayout.ColumnMajor, null);
Assert.AreEqual(20, ((StochasticLayer)layer.Graph.Vertices.ElementAt(0)).NumberOfNeurons);
Assert.AreEqual(30, ((StochasticLayer)layer.Graph.Vertices.ElementAt(1)).NumberOfNeurons);
Assert.AreEqual("20-30GRU", layer.Architecture);
Assert.AreEqual(1, layer.NumberOfOutputs);
CollectionAssert.AreEqual(new[] { 1, 30 }, layer.OutputShape.Axes);
}
public void ArchitectureConstructorTest2()
{
const string Architecture = "20-30-40GRU(Bi=1)";
Shape shape = new Shape(new int[] { -1, 20, 20, 10 });
GRULayer layer = new GRULayer(shape, Architecture, null);
Assert.AreEqual(20, ((StochasticLayer)layer.Graph.Vertices.ElementAt(0)).NumberOfNeurons);
Assert.AreEqual(30, ((StochasticLayer)layer.Graph.Vertices.ElementAt(1)).NumberOfNeurons);
Assert.AreEqual(40, ((StochasticLayer)layer.Graph.Vertices.ElementAt(2)).NumberOfNeurons);
Assert.AreEqual(Architecture, layer.Architecture);
Assert.IsTrue(layer.Graph.Vertices.Take(2).Cast <GRUCell>().All(x => x.Direction == RNNDirection.BiDirectional));
Assert.AreEqual(1, layer.NumberOfOutputs);
CollectionAssert.AreEqual(new[] { -1, 40 }, layer.OutputShape.Axes);
}
public void ArchitectureConstructorTest3()
{
string architecture = "100GRU";
try
{
GRULayer layer = new GRULayer(new Shape(new int[] { 1, 20, 20, 10 }), 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 Test_GRU_Execute_Linear()
{
// Initialize data.
Data2D data = new Data2D(1, 3, 3, 5);
int l = 0;
for (int b = 0; b < 5; ++b)
{
for (int w = 0; w < 3; ++w)
{
for (int c = 0; c < 3; ++c)
{
l += 1;
data[0, w, c, b] = (l % 5 + 1) / 10.0;
}
}
}
// Initialize parameters.
Data2D pms = new Data2D(2, 3, 2, 9);
int k = 0;
int bc = 0;
for (int i = 0; i < 3; ++i)
{
for (int u = 0; u < 6; ++u)
{
k += 1;
pms[u % 2, i, 0, bc] = (k % 5 - 2) / 10.0;
if (k % 2 == 0)
{
bc += 1;
bc = bc % 3;
}
}
}
k = 0;
bc = 0;
for (int i = 0; i < 2; ++i)
{
for (int u = 0; u < 6; ++u)
{
k += 1;
pms[u % 2, i, 0, 3 + bc] = (k % 5 - 2) / 10.0;
if (k % 2 == 0)
{
bc += 1;
bc = bc % 3;
}
}
}
pms[0, 0, 0, 6] = 1.0 / 10.0;
pms[0, 0, 1, 6] = 2.0 / 10.0;
pms[0, 0, 0, 7] = -1.0 / 10.0;
pms[0, 0, 1, 7] = 0.0 / 10;
pms[0, 0, 0, 8] = 3.0 / 10;
pms[0, 0, 1, 8] = 4.0 / 10;
GRULayer rnn = new GRULayer(2, 3, p => { }, p => { });
rnn.SetWeights(pms);
rnn.SetInput(data);
rnn.Execute();
Data2D output = rnn.GetOutput() as Data2D;
// Checking sizes
Dimension dim = output.GetDimension();
Assert.AreEqual(dim.b, 5);
Assert.AreEqual(dim.c, 2);
Assert.AreEqual(dim.h, 1);
Assert.AreEqual(dim.w, 1);
// Checking calculation
Assert.AreEqual(output[0, 0, 0, 0], 0.20213, 0.00001);
Assert.AreEqual(output[0, 0, 1, 0], 0.39285, 0.00001);
Assert.AreEqual(output[0, 0, 0, 1], 0.22716, 0.00001);
Assert.AreEqual(output[0, 0, 1, 1], 0.39534, 0.00001);
Assert.AreEqual(output[0, 0, 0, 2], 0.25739, 0.00001);
Assert.AreEqual(output[0, 0, 1, 2], 0.40368, 0.00001);
Assert.AreEqual(output[0, 0, 0, 3], 0.18944, 0.00001);
Assert.AreEqual(output[0, 0, 1, 3], 0.36951, 0.00001);
Assert.AreEqual(output[0, 0, 0, 4], 0.16984, 0.00001);
Assert.AreEqual(output[0, 0, 1, 4], 0.36987, 0.00001);
}
public void Test_GRU_Execute_ReLu()
{
// Initialize data.
Data2D data = new Data2D(1, 3, 3, 5);
int l = 0;
for (int b = 0; b < 5; ++b)
{
for (int w = 0; w < 3; ++w)
{
for (int c = 0; c < 3; ++c)
{
l += 1;
data[0, w, c, b] = (l % 5 + 1) / 10.0;
}
}
}
// Initialize parameters.
Data2D pms = new Data2D(2, 3, 2, 9);
int k = 0;
int bc = 0;
for (int i = 0; i < 3; ++i)
{
for (int u = 0; u < 6; ++u)
{
k += 1;
pms[u % 2, i, 0, bc] = (k % 5 - 2) / 10.0;
if (k % 2 == 0)
{
bc += 1;
bc = bc % 3;
}
}
}
k = 0;
bc = 0;
for (int i = 0; i < 2; ++i)
{
for (int u = 0; u < 6; ++u)
{
k += 1;
pms[u % 2, i, 0, 3 + bc] = (k % 5 - 2) / 10.0;
if (k % 2 == 0)
{
bc += 1;
bc = bc % 3;
}
}
}
pms[0, 0, 0, 6] = 1.0 / 10.0;
pms[0, 0, 1, 6] = 2.0 / 10.0;
pms[0, 0, 0, 7] = -1.0 / 10.0;
pms[0, 0, 1, 7] = 0.0 / 10;
pms[0, 0, 0, 8] = 3.0 / 10;
pms[0, 0, 1, 8] = 4.0 / 10;
GRULayer rnn = new GRULayer(2, 3, TanHKernel.TanHLambda, ReLuKernel.ReLuLambda);
rnn.SetWeights(pms);
rnn.SetInput(data);
rnn.Execute();
Data2D output = rnn.GetOutput() as Data2D;
// Checking sizes
Dimension dim = output.GetDimension();
Assert.AreEqual(dim.b, 5);
Assert.AreEqual(dim.c, 2);
Assert.AreEqual(dim.h, 1);
Assert.AreEqual(dim.w, 1);
// Checking calculation
Assert.AreEqual(output[0, 0, 0, 0], 0.19632, 0.00001);
Assert.AreEqual(output[0, 0, 1, 0], 0.37259, 0.00001);
Assert.AreEqual(output[0, 0, 0, 1], 0.21991, 0.00001);
Assert.AreEqual(output[0, 0, 1, 1], 0.37473, 0.00001);
Assert.AreEqual(output[0, 0, 0, 2], 0.24834, 0.00001);
Assert.AreEqual(output[0, 0, 1, 2], 0.38176, 0.00001);
Assert.AreEqual(output[0, 0, 0, 3], 0.18727, 0.00001);
Assert.AreEqual(output[0, 0, 1, 3], 0.35267, 0.00001);
Assert.AreEqual(output[0, 0, 0, 4], 0.166619, 0.00001);
Assert.AreEqual(output[0, 0, 1, 4], 0.35275, 0.00001);
}
