Examples with CacheBasicFloatNetwork ml.shifu.shifu.core.dtrain.dataset.CacheBasicFloatNetwork used on opensource projects

Example 1 with CacheBasicFloatNetwork

use of ml.shifu.shifu.core.dtrain.dataset.CacheBasicFloatNetwork in project shifu by ShifuML.

the class VarSelectMapper method copy.

/**
 * Copy existing model to {@link CacheBasicFloatNetwork} model for fast scoring in sensitivity computing.
 *
 * @param network
 *            the raw network model
 * @return the cache network model instance.
 */
public static final CacheBasicFloatNetwork copy(final BasicFloatNetwork network) {
    final CacheBasicFloatNetwork result = new CacheBasicFloatNetwork(network);
    final CacheFlatNetwork flat = new CacheFlatNetwork();
    result.getProperties().putAll(network.getProperties());
    flat.setBeginTraining(network.getFlat().getBeginTraining());
    flat.setConnectionLimit(network.getFlat().getConnectionLimit());
    flat.setContextTargetOffset(network.getFlat().getContextTargetOffset());
    flat.setContextTargetSize(network.getFlat().getContextTargetSize());
    flat.setEndTraining(network.getFlat().getEndTraining());
    flat.setHasContext(network.getFlat().getHasContext());
    flat.setInputCount(network.getFlat().getInputCount());
    flat.setLayerCounts(network.getFlat().getLayerCounts());
    flat.setLayerFeedCounts(network.getFlat().getLayerFeedCounts());
    flat.setLayerContextCount(network.getFlat().getLayerContextCount());
    flat.setLayerIndex(network.getFlat().getLayerIndex());
    flat.setLayerOutput(network.getFlat().getLayerOutput());
    flat.setLayerSums(network.getFlat().getLayerSums());
    flat.setOutputCount(network.getFlat().getOutputCount());
    flat.setWeightIndex(network.getFlat().getWeightIndex());
    flat.setWeights(network.getFlat().getWeights());
    flat.setBiasActivation(network.getFlat().getBiasActivation());
    flat.setActivationFunctions(network.getFlat().getActivationFunctions());
    result.setFeatureSet(network.getFeatureSet());
    result.getStructure().setFlat(flat);
    return result;
}