public void JsonMetadataSerialization()
{
INeuralNetwork network = NetworkManager.NewSequential(TensorInfo.Image <Rgb24>(120, 120),
NetworkLayers.Convolutional((10, 10), 20, ActivationType.AbsoluteReLU),
NetworkLayers.Convolutional((5, 5), 20, ActivationType.ELU),
NetworkLayers.Convolutional((10, 10), 20, ActivationType.Identity),
NetworkLayers.Pooling(ActivationType.ReLU),
NetworkLayers.Convolutional((10, 10), 20, ActivationType.Identity),
NetworkLayers.Pooling(ActivationType.Identity),
NetworkLayers.BatchNormalization(NormalizationMode.Spatial, ActivationType.ReLU),
NetworkLayers.FullyConnected(125, ActivationType.Tanh),
NetworkLayers.Softmax(133));
string metadata1 = network.SerializeMetadataAsJson();
Assert.IsTrue(metadata1.Length > 0);
Assert.IsTrue(metadata1.Equals(network.Clone().SerializeMetadataAsJson()));
network.Layers.First().To <INetworkLayer, ConvolutionalLayer>().Weights[0] += 0.1f;
Assert.IsFalse(metadata1.Equals(network.SerializeMetadataAsJson()));
}
public void NetworkSerialization()
{
INeuralNetwork network = NetworkManager.NewSequential(TensorInfo.Image <Rgb24>(120, 120),
NetworkLayers.Convolutional((10, 10), 20, ActivationType.AbsoluteReLU),
NetworkLayers.Convolutional((5, 5), 20, ActivationType.ELU),
NetworkLayers.Convolutional((10, 10), 20, ActivationType.Identity),
NetworkLayers.Pooling(ActivationType.ReLU),
NetworkLayers.Convolutional((10, 10), 20, ActivationType.Identity),
NetworkLayers.Pooling(ActivationType.Identity),
NetworkLayers.BatchNormalization(NormalizationMode.Spatial, ActivationType.ReLU),
NetworkLayers.FullyConnected(125, ActivationType.Tanh),
NetworkLayers.Softmax(133));
using (MemoryStream stream = new MemoryStream())
{
network.Save(stream);
stream.Seek(0, SeekOrigin.Begin);
INeuralNetwork copy = NetworkLoader.TryLoad(stream, ExecutionModePreference.Cpu);
Assert.IsTrue(network.Equals(copy));
}
}