Examples with SquareActivationLayer com.simiacryptus.mindseye.layers.cudnn.SquareActivationLayer used on opensource projects

Example 1 with SquareActivationLayer

use of com.simiacryptus.mindseye.layers.cudnn.SquareActivationLayer in project MindsEye by SimiaCryptus.

the class DeepDream method getContentComponents.

/**
 * Gets content components.
 *
 * @param setup   the setup
 * @param nodeMap the node map
 * @return the content components
 */
@Nonnull
public ArrayList<Tuple2<Double, DAGNode>> getContentComponents(NeuralSetup<T> setup, final Map<T, DAGNode> nodeMap) {
    ArrayList<Tuple2<Double, DAGNode>> contentComponents = new ArrayList<>();
    for (final T layerType : getLayerTypes()) {
        final DAGNode node = nodeMap.get(layerType);
        if (setup.style.coefficients.containsKey(layerType)) {
            final double coeff_content = setup.style.coefficients.get(layerType).rms;
            DAGNetwork network = node.getNetwork();
            contentComponents.add(new Tuple2<>(coeff_content, network.wrap(new MeanSqLossLayer(), node, network.wrap(new ValueLayer(setup.contentTarget.content.get(layerType))))));
            final double coeff_gain = setup.style.coefficients.get(layerType).gain;
            contentComponents.add(new Tuple2<>(-coeff_gain, network.wrap(new AvgReducerLayer(), network.wrap(new SquareActivationLayer(), node))));
        }
    }
    return contentComponents;
}

Example 2 with SquareActivationLayer

use of com.simiacryptus.mindseye.layers.cudnn.SquareActivationLayer in project MindsEye by SimiaCryptus.

the class ArtistryUtil method squareAvg.

/**
 * Square avg pipeline network.
 *
 * @param network      the network
 * @param mean         the mean
 * @param pcaTransform the pca transform
 * @return the pipeline network
 */
@Nonnull
public static PipelineNetwork squareAvg(final PipelineNetwork network, Tensor mean, Tensor pcaTransform) {
    int[] dimensions = pcaTransform.getDimensions();
    int inputBands = mean.getDimensions()[2];
    int pcaBands = dimensions[2];
    int outputBands = pcaBands / inputBands;
    int width = dimensions[0];
    int height = dimensions[1];
    network.wrap(new ImgBandBiasLayer(mean.scale(-1)));
    network.wrap(new ConvolutionLayer(width, height, inputBands, outputBands).set(pcaTransform));
    network.wrap(new SquareActivationLayer());
    network.wrap(new BandAvgReducerLayer());
    return network;
}