org.deeplearning4j.nn.graph.util.ComputationGraphUtil Maven / Gradle / Ivy

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 *  * This program and the accompanying materials are made available under the
 *  * terms of the Apache License, Version 2.0 which is available at
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 *  *  information regarding copyright ownership.
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package org.deeplearning4j.nn.graph.util;

import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.dataset.adapter.MultiDataSetIteratorAdapter;
import org.nd4j.linalg.dataset.api.DataSet;
import org.nd4j.linalg.dataset.api.MultiDataSet;
import org.nd4j.linalg.dataset.api.iterator.DataSetIterator;
import org.nd4j.linalg.dataset.api.iterator.MultiDataSetIterator;

import java.io.Serializable;
import java.util.List;

public class ComputationGraphUtil {

    private ComputationGraphUtil() {}

    /** Convert a DataSet to the equivalent MultiDataSet */
    public static MultiDataSet toMultiDataSet(DataSet dataSet) {
        INDArray f = dataSet.getFeatures();
        INDArray l = dataSet.getLabels();
        INDArray fMask = dataSet.getFeaturesMaskArray();
        INDArray lMask = dataSet.getLabelsMaskArray();
        List meta = dataSet.getExampleMetaData();

        INDArray[] fNew = f == null ? null : new INDArray[] {f};
        INDArray[] lNew = l == null ? null : new INDArray[] {l};
        INDArray[] fMaskNew = (fMask != null ? new INDArray[] {fMask} : null);
        INDArray[] lMaskNew = (lMask != null ? new INDArray[] {lMask} : null);

        org.nd4j.linalg.dataset.MultiDataSet mds = new org.nd4j.linalg.dataset.MultiDataSet(fNew, lNew, fMaskNew, lMaskNew);
        mds.setExampleMetaData(meta);
        return mds;
    }

    /** Convert a DataSetIterator to a MultiDataSetIterator, via an adaptor class */
    public static MultiDataSetIterator toMultiDataSetIterator(DataSetIterator iterator) {
        return new MultiDataSetIteratorAdapter(iterator);
    }

}