/*- * * * Copyright 2016 Skymind,Inc. * * * * Licensed under the Apache License, Version 2.0 (the "License"); * * you may not use this file except in compliance with the License. * * You may obtain a copy of the License at * * * * http://www.apache.org/licenses/LICENSE-2.0 * * * * Unless required by applicable law or agreed to in writing, software * * distributed under the License is distributed on an "AS IS" BASIS, * * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * * See the License for the specific language governing permissions and * * limitations under the License. * */ package org.deeplearning4j.nn.graph.util; import org.deeplearning4j.datasets.iterator.impl.MultiDataSetIteratorAdapter; import org.nd4j.linalg.api.ndarray.INDArray; import org.nd4j.linalg.dataset.api.DataSet; import org.nd4j.linalg.dataset.api.MultiDataSet; import org.nd4j.linalg.dataset.api.MultiDataSetPreProcessor; import org.nd4j.linalg.dataset.api.iterator.DataSetIterator; import org.nd4j.linalg.dataset.api.iterator.MultiDataSetIterator; 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(); 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); return new org.nd4j.linalg.dataset.MultiDataSet(fNew, lNew, fMaskNew, lMaskNew); } /** Convert a DataSetIterator to a MultiDataSetIterator, via an adaptor class */ public static MultiDataSetIterator toMultiDataSetIterator(DataSetIterator iterator) { return new MultiDataSetIteratorAdapter(iterator); } }