public void Initialise() { Console.WriteLine("Loading Training Data Set..."); trainingDataSet = DataSets.GetTrainingSet().Randomise(0); Console.WriteLine("Loading Generalisation Data Set..."); generalisationDataSet = DataSets.GetGeneralisationSet().Randomise(1); Console.WriteLine("Creating LeNet..."); LeNetConfiguration configuration = LeNetConfigurations.FromCharacters('0', '1', '2', '3', '4', '5', '6', '7', '8', '9'); Network = new LeNetNetwork(configuration); Snapshot = new LeNetSnapshot(Network); Network.LearningRate = 0.0005 / 16.0; Network.Mu = 0.02; bool isPreTraining = Network.IsPreTraining; }
public ObservationForm(LeNetSnapshot snapshot) { InitializeComponent(); this.Snapshot = snapshot; firstConvolutions = CreateHorizontalPictureBoxes(28 * 3, snapshot.FirstConvolutions.Count); firstConvolutionsContainer.Controls.AddRange(firstConvolutions); firstSubsampling = CreateHorizontalPictureBoxes(28 * 3, snapshot.FirstSubsampling.Count); firstSubsamplingContainer.Controls.AddRange(firstSubsampling); secondConvolutions = CreateHorizontalPictureBoxes(28 * 3, snapshot.SecondConvolutions.Count); secondConvolutionsContainer.Controls.AddRange(secondConvolutions); secondSubsampling = CreateHorizontalPictureBoxes(28 * 3, snapshot.SecondSubsampling.Count); secondSubsamplingContainer.Controls.AddRange(secondSubsampling); inputPicture.Paint += inputPicture_Paint; Snapshot.Updated += Snapshot_Updated; Snapshot.RequestUpdate(); }