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

Example 1 with ImgBandBiasLayer

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

the class VGG16_HDF5 method phase3a.

/**
 * Phase 3 a.
 */
protected void phase3a() {
    add(new ConvolutionLayer(1, 1, 4096, 4096).setPaddingXY(0, 0).setAndFree(hdf5.readDataSet("param_0", "layer_34").permuteDimensionsAndFree(fullyconnectedOrder)));
    add(new ImgBandBiasLayer(4096).setAndFree((hdf5.readDataSet("param_1", "layer_34"))));
    add(new ActivationLayer(ActivationLayer.Mode.RELU));
    add(new ConvolutionLayer(1, 1, 4096, 1000).setPaddingXY(0, 0).setAndFree(hdf5.readDataSet("param_0", "layer_36").permuteDimensionsAndFree(fullyconnectedOrder)));
    add(new ImgBandBiasLayer(1000).setAndFree((hdf5.readDataSet("param_1", "layer_36"))));
}

Example 2 with ImgBandBiasLayer

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

the class VGG16_HDF5 method phase0.

/**
 * Phase 0.
 */
protected void phase0() {
    add(new ImgMinSizeLayer(226, 226));
    add(new ImgBandBiasLayer(3).set(new Tensor(-103.939, -116.779, -123.68)));
}

Example 3 with ImgBandBiasLayer

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

the class VGG19_HDF5 method phase0.

/**
 * Phase 0.
 */
protected void phase0() {
    add(new ImgMinSizeLayer(226, 226));
    add(new ImgBandBiasLayer(3).set(new Tensor(-103.939, -116.779, -123.68)));
}

Example 4 with ImgBandBiasLayer

use of com.simiacryptus.mindseye.layers.cudnn.ImgBandBiasLayer 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 5 with ImgBandBiasLayer

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

the class ArtistryUtil method gram.

/**
 * Gram pipeline network.
 *
 * @param network      the network
 * @param mean         the mean
 * @param pcaTransform the pca transform
 * @return the pipeline network
 */
@Nonnull
public static PipelineNetwork gram(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 GramianLayer());
    return network;
}