Examples with PipelineNetwork com.simiacryptus.mindseye.network.PipelineNetwork used on opensource projects

Example 6 with PipelineNetwork

use of com.simiacryptus.mindseye.network.PipelineNetwork in project MindsEye by SimiaCryptus.

the class EncodingUtil method downExplodeTensors.

/**
 * Down explode tensors stream.
 *
 * @param stream the stream
 * @param factor the factor
 * @return the stream
 */
@Nonnull
public static Stream<Tensor[]> downExplodeTensors(@Nonnull final Stream<Tensor[]> stream, final int factor) {
    if (0 >= factor)
        throw new IllegalArgumentException();
    if (-1 == factor)
        throw new IllegalArgumentException();
    return 1 == factor ? stream : stream.flatMap(tensor -> IntStream.range(0, factor * factor).mapToObj(subband -> {
        @Nonnull final int[] select = new int[tensor[1].getDimensions()[2]];
        final int offset = subband * select.length;
        for (int i = 0; i < select.length; i++) {
            select[i] = offset + i;
        }
        @Nonnull final PipelineNetwork network = new PipelineNetwork();
        network.add(new ImgReshapeLayer(factor, factor, false));
        network.add(new ImgBandSelectLayer(select));
        @Nullable final Tensor result = network.eval(tensor[1]).getData().get(0);
        return new Tensor[] { tensor[0], result };
    }));
}

Example 7 with PipelineNetwork

use of com.simiacryptus.mindseye.network.PipelineNetwork in project MindsEye by SimiaCryptus.

the class RecursiveSubspaceTest method buildModel.

@Override
public DAGNetwork buildModel(@Nonnull NotebookOutput log) {
    log.h3("Model");
    log.p("We use a multi-level convolution network");
    return log.code(() -> {
        @Nonnull final PipelineNetwork network = new PipelineNetwork();
        double weight = 1e-3;
        @Nonnull DoubleSupplier init = () -> weight * (Math.random() - 0.5);
        network.add(new ConvolutionLayer(3, 3, 1, 5).set(init));
        network.add(new ImgBandBiasLayer(5));
        network.add(new PoolingLayer().setMode(PoolingLayer.PoolingMode.Max));
        network.add(new ActivationLayer(ActivationLayer.Mode.RELU));
        network.add(newNormalizationLayer());
        network.add(new ConvolutionLayer(3, 3, 5, 5).set(init));
        network.add(new ImgBandBiasLayer(5));
        network.add(new PoolingLayer().setMode(PoolingLayer.PoolingMode.Max));
        network.add(new ActivationLayer(ActivationLayer.Mode.RELU));
        network.add(newNormalizationLayer());
        network.add(new BiasLayer(7, 7, 5));
        network.add(new FullyConnectedLayer(new int[] { 7, 7, 5 }, new int[] { 10 }).set(init));
        network.add(new SoftmaxActivationLayer());
        return network;
    });
}

Example 8 with PipelineNetwork

use of com.simiacryptus.mindseye.network.PipelineNetwork in project MindsEye by SimiaCryptus.

the class StochasticSamplingSubnetLayerTest method getLayer.

@Nonnull
@Override
public Layer getLayer(final int[][] inputSize, Random random) {
    PipelineNetwork subnetwork = new PipelineNetwork(1);
    subnetwork.wrap(new ProductLayer(), subnetwork.getInput(0), subnetwork.add(new StochasticBinaryNoiseLayer(0.5, 1.0, inputSize[0]), new DAGNode[] {}));
    StochasticSamplingSubnetLayer tileSubnetLayer = new StochasticSamplingSubnetLayer(subnetwork, 2);
    subnetwork.freeRef();
    return tileSubnetLayer;
}

Example 9 with PipelineNetwork

use of com.simiacryptus.mindseye.network.PipelineNetwork in project MindsEye by SimiaCryptus.

the class ArtistryUtil method withClamp.

/**
 * With clamp pipeline network.
 *
 * @param network1 the network 1
 * @return the pipeline network
 */
@Nonnull
public static PipelineNetwork withClamp(final PipelineNetwork network1) {
    PipelineNetwork network = new PipelineNetwork(1);
    network.wrap(getClamp(255));
    network.wrap(network1);
    return network;
}

Example 10 with PipelineNetwork

use of com.simiacryptus.mindseye.network.PipelineNetwork in project MindsEye by SimiaCryptus.

the class DeepDream method fitnessNetwork.

/**
 * Fitness function pipeline network.
 *
 * @param setup the setup
 * @return the pipeline network
 */
@Nonnull
public PipelineNetwork fitnessNetwork(NeuralSetup setup) {
    PipelineNetwork pipelineNetwork = getInstance().getNetwork();
    Map<T, DAGNode> nodes = new HashMap<>();
    Map<T, UUID> ids = getInstance().getNodes();
    ids.forEach((l, id) -> nodes.put(l, pipelineNetwork.getChildNode(id)));
    PipelineNetwork network = processStats(setup, nodes, pipelineNetwork);
    // network = withClamp(network);
    ArtistryUtil.setPrecision(network, setup.style.precision);
    return network;
}