static bool SaveLoad()
{
BitmapCatEnumerator enums = new BitmapCatEnumerator("Sorted", new System.Drawing.Size(50, 25));
Network network = new Network();
network.AddLayer(new Conv2D(new Relu(), 7, 7, 32));
network.AddLayer(new MaxPool2D(new Relu(), 2, 2));
network.AddLayer(new Conv2D(new Relu(), 5, 5, 64));
network.AddLayer(new MaxPool2D(new Relu(), 2, 2));
network.AddLayer(new FullyConnLayar(new Relu(), new Size(1, 1, 256)));
network.AddLayer(new FullyConnLayar(new Sigmoid(), new Size(1, 1, 2)));
network.Compile(new Size(3, 25, 50), true);
network.Normalization();
network.Normalization();
string data = network.SaveJSON();
Network network2 = new Network();
network2.LoadJSON(data);
var pair = enums.GetRandom(ref network);
var out1 = network.GetOutput(pair.Key);
var out2 = network.GetOutput(pair.Key);
return(out1[0, 0, 0] == out2[0, 0, 0]);
}
static bool CatTrain()
{
BitmapCatEnumerator enums = new BitmapCatEnumerator("Sorted", new System.Drawing.Size(50, 25));
Network network = new Network();
network.AddLayer(new Conv2D(new Relu(), 7, 7, 32));
network.AddLayer(new MaxPool2D(new Relu(), 2, 2));
network.AddLayer(new Conv2D(new Relu(), 5, 5, 64));
network.AddLayer(new MaxPool2D(new Relu(), 2, 2));
network.AddLayer(new FullyConnLayar(new Relu(), new Size(1, 1, 256)));
network.AddLayer(new FullyConnLayar(new Sigmoid(), new Size(1, 1, 2)));
network.Compile(new Size(3, 25, 50), true);
network.Normalization();
var pair = enums.GetRandom(ref network);
OneEnumerator one = new OneEnumerator();
one.input = pair.Key;
one.output = pair.Value;
MomentumParallel sgd = new MomentumParallel(network, 0.9, 1e-6);
double[] errors = sgd.TrainBatch(enums, 32, 1000);
return(errors[0] > errors.Last());
}
