public static ITrainer CreateTicTacToeTrainer(SigmaEnvironment sigma) { IDataset dataset = Defaults.Datasets.TicTacToe(); ITrainer trainer = sigma.CreateTrainer("tictactoe-trainer"); trainer.Network = new Network(); trainer.Network.Architecture = InputLayer.Construct(9) + FullyConnectedLayer.Construct(72, "tanh") + FullyConnectedLayer.Construct(99, "tanh") + FullyConnectedLayer.Construct(3, "tanh") + OutputLayer.Construct(3) + SoftMaxCrossEntropyCostLayer.Construct(); trainer.TrainingDataIterator = new MinibatchIterator(21, dataset); trainer.AddNamedDataIterator("validation", new UndividedIterator(dataset)); trainer.Optimiser = new MomentumGradientOptimiser(learningRate: 0.01, momentum: 0.9); trainer.Operator = new CpuSinglethreadedOperator(); trainer.AddInitialiser("*.*", new GaussianInitialiser(standardDeviation: 0.1)); trainer.AddLocalHook(new AccumulatedValueReporter("optimiser.cost_total", TimeStep.Every(1, TimeScale.Epoch))); trainer.AddHook(new MultiClassificationAccuracyReporter("validation", TimeStep.Every(1, TimeScale.Epoch), tops: new[] { 1, 2 })); trainer.AddGlobalHook(new DiskSaviorHook <INetwork>(TimeStep.Every(1, TimeScale.Epoch), "network.self", Namers.Static("tictactoe.sgnet"), verbose: true) .On(new ExtremaCriteria("shared.classification_accuracy_top1", ExtremaTarget.Max))); return(trainer); }
/// <summary> /// Create a savior hook that will automatically serialise a certain registry entry. /// </summary> /// <param name="timestep">The time step.</param> /// <param name="registryEntryToSave"></param> /// <param name="fileName">The file namer to store to disk as.</param> /// <param name="verbose">Indicate whether or not to report when the specified object was serialised.</param> public DiskSaviorHook(ITimeStep timestep, string registryEntryToSave, string fileName, bool verbose = true) : this(timestep, registryEntryToSave, Namers.Static(fileName), verbose) { }