org.deeplearning4j.spark.data.BatchDataSetsFunction Maven / Gradle / Ivy
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/*
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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
* * https://www.apache.org/licenses/LICENSE-2.0.
* *
* * See the NOTICE file distributed with this work for additional
* * information regarding copyright ownership.
* * 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
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* * SPDX-License-Identifier: Apache-2.0
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*/
package org.deeplearning4j.spark.data;
import lombok.AllArgsConstructor;
import org.apache.spark.api.java.function.FlatMapFunction;
import org.nd4j.linalg.dataset.DataSet;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.List;
@AllArgsConstructor
public class BatchDataSetsFunction implements FlatMapFunction, DataSet> {
private final int minibatchSize;
@Override
public Iterator call(Iterator iter) throws Exception {
List out = new ArrayList<>();
while (iter.hasNext()) {
List list = new ArrayList<>();
int count = 0;
while (count < minibatchSize && iter.hasNext()) {
DataSet ds = iter.next();
count += ds.getFeatures().size(0);
list.add(ds);
}
DataSet next;
if (list.isEmpty())
next = list.get(0);
else
next = DataSet.merge(list);
out.add(next);
}
return out.iterator();
}
}