Examples with IterativeTrainer com.simiacryptus.mindseye.opt.IterativeTrainer used on opensource projects

Example 16 with IterativeTrainer

use of com.simiacryptus.mindseye.opt.IterativeTrainer in project MindsEye by SimiaCryptus.

the class TrainingTester method trainLBFGS.

/**
 * Train lbfgs list.
 *
 * @param log       the log
 * @param trainable the trainable
 * @return the list
 */
@Nonnull
public List<StepRecord> trainLBFGS(@Nonnull final NotebookOutput log, final Trainable trainable) {
    log.p("Next, we apply the same optimization using L-BFGS, which is nearly ideal for purely second-order or quadratic functions.");
    @Nonnull final List<StepRecord> history = new ArrayList<>();
    @Nonnull final TrainingMonitor monitor = TrainingTester.getMonitor(history);
    try {
        log.code(() -> {
            return new IterativeTrainer(trainable).setLineSearchFactory(label -> new ArmijoWolfeSearch()).setOrientation(new LBFGS()).setMonitor(monitor).setTimeout(30, TimeUnit.SECONDS).setIterationsPerSample(100).setMaxIterations(250).setTerminateThreshold(0).runAndFree();
        });
    } catch (Throwable e) {
        if (isThrowExceptions())
            throw new RuntimeException(e);
    }
    return history;
}

Example 17 with IterativeTrainer

use of com.simiacryptus.mindseye.opt.IterativeTrainer in project MindsEye by SimiaCryptus.

the class TrustSphereTest method train.

@Override
public void train(@Nonnull final NotebookOutput log, @Nonnull final Layer network, @Nonnull final Tensor[][] trainingData, final TrainingMonitor monitor) {
    log.code(() -> {
        @Nonnull final SimpleLossNetwork supervisedNetwork = new SimpleLossNetwork(network, new EntropyLossLayer());
        @Nonnull final Trainable trainable = new SampledArrayTrainable(trainingData, supervisedNetwork, 10000);
        @Nonnull final TrustRegionStrategy trustRegionStrategy = new TrustRegionStrategy() {

            @Override
            public TrustRegion getRegionPolicy(final Layer layer) {
                return new AdaptiveTrustSphere();
            }
        };
        return new IterativeTrainer(trainable).setIterationsPerSample(100).setMonitor(monitor).setOrientation(trustRegionStrategy).setTimeout(3, TimeUnit.MINUTES).setMaxIterations(500).runAndFree();
    });
}

Example 18 with IterativeTrainer

use of com.simiacryptus.mindseye.opt.IterativeTrainer in project MindsEye by SimiaCryptus.

the class QuadraticLineSearchTest method train.

@Override
public void train(@Nonnull final NotebookOutput log, @Nonnull final Layer network, @Nonnull final Tensor[][] trainingData, final TrainingMonitor monitor) {
    log.code(() -> {
        @Nonnull final SimpleLossNetwork supervisedNetwork = new SimpleLossNetwork(network, new EntropyLossLayer());
        @Nonnull final Trainable trainable = new SampledArrayTrainable(trainingData, supervisedNetwork, 1000);
        return new IterativeTrainer(trainable).setMonitor(monitor).setOrientation(new GradientDescent()).setLineSearchFactory((@Nonnull final CharSequence name) -> new QuadraticSearch()).setTimeout(3, TimeUnit.MINUTES).setMaxIterations(500).runAndFree();
    });
}

Example 19 with IterativeTrainer

use of com.simiacryptus.mindseye.opt.IterativeTrainer in project MindsEye by SimiaCryptus.

the class RecursiveSubspace method train.

/**
 * Train.
 *
 * @param monitor    the monitor
 * @param macroLayer the macro layer
 */
public void train(@Nonnull TrainingMonitor monitor, Layer macroLayer) {
    @Nonnull BasicTrainable inner = new BasicTrainable(macroLayer);
    // @javax.annotation.Nonnull Tensor tensor = new Tensor();
    @Nonnull ArrayTrainable trainable = new ArrayTrainable(inner, new Tensor[][] { {} });
    inner.freeRef();
    // tensor.freeRef();
    new IterativeTrainer(trainable).setOrientation(new LBFGS()).setLineSearchFactory(n -> new ArmijoWolfeSearch()).setMonitor(new TrainingMonitor() {

        @Override
        public void log(String msg) {
            monitor.log("\t" + msg);
        }
    }).setMaxIterations(getIterations()).setIterationsPerSample(getIterations()).setTerminateThreshold(terminateThreshold).runAndFree();
    trainable.freeRef();
}

Example 20 with IterativeTrainer

use of com.simiacryptus.mindseye.opt.IterativeTrainer in project MindsEye by SimiaCryptus.

the class StaticRateTest method train.

@Override
public void train(@Nonnull final NotebookOutput log, @Nonnull final Layer network, @Nonnull final Tensor[][] trainingData, final TrainingMonitor monitor) {
    log.code(() -> {
        @Nonnull final SimpleLossNetwork supervisedNetwork = new SimpleLossNetwork(network, new EntropyLossLayer());
        @Nonnull final Trainable trainable = new SampledArrayTrainable(trainingData, supervisedNetwork, 1000);
        return new IterativeTrainer(trainable).setMonitor(monitor).setOrientation(new GradientDescent()).setLineSearchFactory((@Nonnull final CharSequence name) -> new StaticLearningRate(0.001)).setTimeout(3, TimeUnit.MINUTES).setMaxIterations(500).runAndFree();
    });
}