//Setup Engine. If using TensorSharp then pass SiaNet.Backend.TensorSharp.SiaNetBackend.Instance. 
//Once other backend is ready you will be able to use CNTK, TensorFlow and MxNet as well.
Global.UseEngine(SiaNet.Backend.ArrayFire.SiaNetBackend.Instance, DeviceType.CPU);

var dataset = LoadTrain(); //Load train data
var test = LoadTest(); //Load test data

var (train, val) = dataset.Split(0.25);

//Build model
var model = new Sequential();
model.EpochEnd += Model_EpochEnd;
model.Add(new Dense(128, ActivationType.ReLU));
model.Add(new Dense(64, ActivationType.ReLU));
model.Add(new Dense(1, ActivationType.Sigmoid));

//Compile with Optimizer, Loss and Metric
model.Compile(OptimizerType.Adam, LossType.BinaryCrossEntropy, MetricType.BinaryAccurary);

// Train for 100 epoch with batch size of 32
model.Train(train, 100, 32, val);

var predictions = model.Predict(test);
predictions.Print();