Java Code Examples for org.nd4j.linalg.dataset.api.iterator.MultiDataSetIterator#setPreProcessor()

The following examples show how to use org.nd4j.linalg.dataset.api.iterator.MultiDataSetIterator#setPreProcessor() . You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.

Example 1

Source File: RNNTestCases.java From deeplearning4j with Apache License 2.0

6 votes

@Override
public MultiDataSetIterator getTrainingData() throws Exception {
    MultiDataSetIterator iter = getTrainingDataUnnormalized();

    MultiDataSetPreProcessor pp = multiDataSet -> {
        INDArray l = multiDataSet.getLabels(0);
        l = l.get(NDArrayIndex.all(), NDArrayIndex.all(), NDArrayIndex.point(l.size(2)-1));
        multiDataSet.setLabels(0, l);
        multiDataSet.setLabelsMaskArray(0, null);
    };


    iter.setPreProcessor(new CompositeMultiDataSetPreProcessor(getNormalizer(),pp));

    return iter;
}

Example 2

Source File: RNNTestCases.java From deeplearning4j with Apache License 2.0

5 votes

@Override
        public MultiDataSetIterator getEvaluationTestData() throws Exception {
            int miniBatchSize = 10;
            int numLabelClasses = 6;

//            File featuresDirTest = new ClassPathResource("/RnnCsvSequenceClassification/uci_seq/test/features/").getFile();
//            File labelsDirTest = new ClassPathResource("/RnnCsvSequenceClassification/uci_seq/test/labels/").getFile();
            File featuresDirTest = Files.createTempDir();
            File labelsDirTest = Files.createTempDir();
            new ClassPathResource("dl4j-integration-tests/data/uci_seq/test/features/").copyDirectory(featuresDirTest);
            new ClassPathResource("dl4j-integration-tests/data/uci_seq/test/labels/").copyDirectory(labelsDirTest);

            SequenceRecordReader trainFeatures = new CSVSequenceRecordReader();
            trainFeatures.initialize(new NumberedFileInputSplit(featuresDirTest.getAbsolutePath() + "/%d.csv", 0, 149));
            SequenceRecordReader trainLabels = new CSVSequenceRecordReader();
            trainLabels.initialize(new NumberedFileInputSplit(labelsDirTest.getAbsolutePath() + "/%d.csv", 0, 149));

            DataSetIterator testData = new SequenceRecordReaderDataSetIterator(trainFeatures, trainLabels, miniBatchSize, numLabelClasses,
                    false, SequenceRecordReaderDataSetIterator.AlignmentMode.ALIGN_END);

            MultiDataSetIterator iter = new MultiDataSetIteratorAdapter(testData);

            MultiDataSetPreProcessor pp = multiDataSet -> {
                INDArray l = multiDataSet.getLabels(0);
                l = l.get(NDArrayIndex.all(), NDArrayIndex.all(), NDArrayIndex.point(l.size(2)-1));
                multiDataSet.setLabels(0, l);
                multiDataSet.setLabelsMaskArray(0, null);
            };


            iter.setPreProcessor(new CompositeMultiDataSetPreProcessor(getNormalizer(),pp));

            return iter;
        }

Example 3

Source File: SameDiffRNNTestCases.java From deeplearning4j with Apache License 2.0

5 votes

@Override
public MultiDataSetIterator getTrainingData() throws Exception {
    MultiDataSetIterator iter = getTrainingDataUnnormalized();
    MultiDataSetPreProcessor pp = multiDataSet -> {
        INDArray l = multiDataSet.getLabels(0);
        l = l.get(NDArrayIndex.all(), NDArrayIndex.all(), NDArrayIndex.point(l.size(2) - 1));
        multiDataSet.setLabels(0, l);
        multiDataSet.setLabelsMaskArray(0, null);
    };


    iter.setPreProcessor(new CompositeMultiDataSetPreProcessor(getNormalizer(), pp));

    return iter;
}

Example 4

Source File: SameDiffRNNTestCases.java From deeplearning4j with Apache License 2.0

5 votes

@Override
        public MultiDataSetIterator getEvaluationTestData() throws Exception {
            int miniBatchSize = 10;
            int numLabelClasses = 6;

//            File featuresDirTest = new ClassPathResource("/RnnCsvSequenceClassification/uci_seq/test/features/").getFile();
//            File labelsDirTest = new ClassPathResource("/RnnCsvSequenceClassification/uci_seq/test/labels/").getFile();
            File featuresDirTest = Files.createTempDir();
            File labelsDirTest = Files.createTempDir();
            Resources.copyDirectory("dl4j-integration-tests/data/uci_seq/test/features/", featuresDirTest);
            Resources.copyDirectory("dl4j-integration-tests/data/uci_seq/test/labels/", labelsDirTest);

            SequenceRecordReader trainFeatures = new CSVSequenceRecordReader();
            trainFeatures.initialize(new NumberedFileInputSplit(featuresDirTest.getAbsolutePath() + "/%d.csv", 0, 149));
            SequenceRecordReader trainLabels = new CSVSequenceRecordReader();
            trainLabels.initialize(new NumberedFileInputSplit(labelsDirTest.getAbsolutePath() + "/%d.csv", 0, 149));

            DataSetIterator testData = new SequenceRecordReaderDataSetIterator(trainFeatures, trainLabels, miniBatchSize, numLabelClasses,
                    false, SequenceRecordReaderDataSetIterator.AlignmentMode.ALIGN_END);

            MultiDataSetIterator iter = new MultiDataSetIteratorAdapter(testData);

            MultiDataSetPreProcessor pp = multiDataSet -> {
                INDArray l = multiDataSet.getLabels(0);
                l = l.get(NDArrayIndex.all(), NDArrayIndex.all(), NDArrayIndex.point(l.size(2) - 1));
                multiDataSet.setLabels(0, l);
                multiDataSet.setLabelsMaskArray(0, null);
            };


            iter.setPreProcessor(new CompositeMultiDataSetPreProcessor(getNormalizer(), pp));

            return iter;
        }