org.datavec.api.records.reader.SequenceRecordReader Java Examples

The following examples show how to use org.datavec.api.records.reader.SequenceRecordReader. 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: SameDiffRNNTestCases.java From deeplearning4j with Apache License 2.0

6 votes

protected MultiDataSetIterator getTrainingDataUnnormalized() throws Exception {
    int miniBatchSize = 10;
    int numLabelClasses = 6;

    File featuresDirTrain = Files.createTempDir();
    File labelsDirTrain = Files.createTempDir();
    Resources.copyDirectory("dl4j-integration-tests/data/uci_seq/train/features/", featuresDirTrain);
    Resources.copyDirectory("dl4j-integration-tests/data/uci_seq/train/labels/", labelsDirTrain);

    SequenceRecordReader trainFeatures = new CSVSequenceRecordReader();
    trainFeatures.initialize(new NumberedFileInputSplit(featuresDirTrain.getAbsolutePath() + "/%d.csv", 0, 449));
    SequenceRecordReader trainLabels = new CSVSequenceRecordReader();
    trainLabels.initialize(new NumberedFileInputSplit(labelsDirTrain.getAbsolutePath() + "/%d.csv", 0, 449));

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

    MultiDataSetIterator iter = new MultiDataSetIteratorAdapter(trainData);

    return iter;
}

Example #2

Source File: CSVSequenceRecordReaderTest.java From DataVec with Apache License 2.0

6 votes

@Test
public void testCsvSeqAndNumberedFileSplit() throws Exception {
    File baseDir = tempDir.newFolder();
    //Simple sanity check unit test
    for (int i = 0; i < 3; i++) {
        new org.nd4j.linalg.io.ClassPathResource(String.format("csvsequence_%d.txt", i)).getTempFileFromArchive(baseDir);
    }

    //Load time series from CSV sequence files; compare to SequenceRecordReaderDataSetIterator
    org.nd4j.linalg.io.ClassPathResource resource = new org.nd4j.linalg.io.ClassPathResource("csvsequence_0.txt");
    String featuresPath = new File(baseDir, "csvsequence_%d.txt").getAbsolutePath();

    SequenceRecordReader featureReader = new CSVSequenceRecordReader(1, ",");
    featureReader.initialize(new NumberedFileInputSplit(featuresPath, 0, 2));

    while(featureReader.hasNext()){
        featureReader.nextSequence();
    }

}

Example #3

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

6 votes

/**
 * Analyze the data quality of sequence data - provides a report on missing values, values that don't comply with schema, etc
 * @param schema Schema for data
 * @param data   Data to analyze
 * @return DataQualityAnalysis object
 */
public static DataQualityAnalysis analyzeQualitySequence(Schema schema, SequenceRecordReader data) {
    int nColumns = schema.numColumns();
    List<QualityAnalysisState> states = new ArrayList<>();
    QualityAnalysisAddFunction addFn = new QualityAnalysisAddFunction(schema);
    while(data.hasNext()){
        List<List<Writable>> seq = data.sequenceRecord();
        for(List<Writable> step : seq){
            states = addFn.apply(states, step);
        }
    }

    List<ColumnQuality> list = new ArrayList<>(nColumns);

    for (QualityAnalysisState qualityState : states) {
        list.add(qualityState.getColumnQuality());
    }
    return new DataQualityAnalysis(schema, list);
}

Example #4

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

6 votes

@Test
public void testSeqRRDSINoLabels(){
    List<List<Writable>> sequence1 = new ArrayList<>();
    sequence1.add(Arrays.asList((Writable) new DoubleWritable(1), new DoubleWritable(2)));
    sequence1.add(Arrays.asList((Writable) new DoubleWritable(3), new DoubleWritable(4)));
    sequence1.add(Arrays.asList((Writable) new DoubleWritable(5), new DoubleWritable(6)));
    List<List<Writable>> sequence2 = new ArrayList<>();
    sequence2.add(Arrays.asList((Writable) new DoubleWritable(10), new DoubleWritable(20)));
    sequence2.add(Arrays.asList((Writable) new DoubleWritable(30), new DoubleWritable(40)));
    SequenceRecordReader rrFeatures = new CollectionSequenceRecordReader(Arrays.asList(sequence1, sequence2));

    SequenceRecordReaderDataSetIterator iter = new SequenceRecordReaderDataSetIterator(rrFeatures, 2, -1, -1);

    DataSet ds = iter.next();
    assertNotNull(ds.getFeatures());
    assertNull(ds.getLabels());
}

Example #5

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

6 votes

@Ignore
@Test
public void testNativeCodecReader() throws Exception {
    File file = new ClassPathResource("datavec-data-codec/fire_lowres.mp4").getFile();
    SequenceRecordReader reader = new NativeCodecRecordReader();
    Configuration conf = new Configuration();
    conf.set(CodecRecordReader.RAVEL, "true");
    conf.set(CodecRecordReader.START_FRAME, "160");
    conf.set(CodecRecordReader.TOTAL_FRAMES, "500");
    conf.set(CodecRecordReader.ROWS, "80");
    conf.set(CodecRecordReader.COLUMNS, "46");
    reader.initialize(new FileSplit(file));
    reader.setConf(conf);
    assertTrue(reader.hasNext());
    List<List<Writable>> record = reader.sequenceRecord();
    //        System.out.println(record.size());

    Iterator<List<Writable>> it = record.iterator();
    List<Writable> first = it.next();
    //        System.out.println(first);

    //Expected size: 80x46x3
    assertEquals(1, first.size());
    assertEquals(80 * 46 * 3, ((ArrayWritable) first.iterator().next()).length());
}

Example #6

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

6 votes

@Test
public void testCodecReaderMeta() throws Exception {
    File file = new ClassPathResource("datavec-data-codec/fire_lowres.mp4").getFile();
    SequenceRecordReader reader = new CodecRecordReader();
    Configuration conf = new Configuration();
    conf.set(CodecRecordReader.RAVEL, "true");
    conf.set(CodecRecordReader.START_FRAME, "160");
    conf.set(CodecRecordReader.TOTAL_FRAMES, "500");
    conf.set(CodecRecordReader.ROWS, "80");
    conf.set(CodecRecordReader.COLUMNS, "46");
    reader.initialize(new FileSplit(file));
    reader.setConf(conf);
    assertTrue(reader.hasNext());
    List<List<Writable>> record = reader.sequenceRecord();
    assertEquals(500, record.size()); //500 frames

    reader.reset();
    SequenceRecord seqR = reader.nextSequence();
    assertEquals(record, seqR.getSequenceRecord());
    RecordMetaData meta = seqR.getMetaData();
    //        System.out.println(meta);
    assertTrue(meta.getURI().toString().endsWith(file.getName()));

    SequenceRecord fromMeta = reader.loadSequenceFromMetaData(meta);
    assertEquals(seqR, fromMeta);
}

Example #7

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

6 votes

@Test
public void testCodecReader() throws Exception {
    File file = new ClassPathResource("datavec-data-codec/fire_lowres.mp4").getFile();
    SequenceRecordReader reader = new CodecRecordReader();
    Configuration conf = new Configuration();
    conf.set(CodecRecordReader.RAVEL, "true");
    conf.set(CodecRecordReader.START_FRAME, "160");
    conf.set(CodecRecordReader.TOTAL_FRAMES, "500");
    conf.set(CodecRecordReader.ROWS, "80");
    conf.set(CodecRecordReader.COLUMNS, "46");
    reader.initialize(new FileSplit(file));
    reader.setConf(conf);
    assertTrue(reader.hasNext());
    List<List<Writable>> record = reader.sequenceRecord();
    //        System.out.println(record.size());

    Iterator<List<Writable>> it = record.iterator();
    List<Writable> first = it.next();
    //        System.out.println(first);

    //Expected size: 80x46x3
    assertEquals(1, first.size());
    assertEquals(80 * 46 * 3, ((ArrayWritable) first.iterator().next()).length());
}

Example #8

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

6 votes

protected MultiDataSetIterator getTrainingDataUnnormalized() throws Exception {
    int miniBatchSize = 10;
    int numLabelClasses = 6;

    File featuresDirTrain = Files.createTempDir();
    File labelsDirTrain = Files.createTempDir();
    new ClassPathResource("dl4j-integration-tests/data/uci_seq/train/features/").copyDirectory(featuresDirTrain);
    new ClassPathResource("dl4j-integration-tests/data/uci_seq/train/labels/").copyDirectory(labelsDirTrain);

    SequenceRecordReader trainFeatures = new CSVSequenceRecordReader();
    trainFeatures.initialize(new NumberedFileInputSplit(featuresDirTrain.getAbsolutePath() + "/%d.csv", 0, 449));
    SequenceRecordReader trainLabels = new CSVSequenceRecordReader();
    trainLabels.initialize(new NumberedFileInputSplit(labelsDirTrain.getAbsolutePath() + "/%d.csv", 0, 449));

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

    MultiDataSetIterator iter = new MultiDataSetIteratorAdapter(trainData);
    return iter;
}

Example #9

Source File: CodecReaderTest.java From DataVec with Apache License 2.0

6 votes

@Ignore
@Test
public void testNativeCodecReader() throws Exception {
    File file = new ClassPathResource("fire_lowres.mp4").getFile();
    SequenceRecordReader reader = new NativeCodecRecordReader();
    Configuration conf = new Configuration();
    conf.set(CodecRecordReader.RAVEL, "true");
    conf.set(CodecRecordReader.START_FRAME, "160");
    conf.set(CodecRecordReader.TOTAL_FRAMES, "500");
    conf.set(CodecRecordReader.ROWS, "80");
    conf.set(CodecRecordReader.COLUMNS, "46");
    reader.initialize(new FileSplit(file));
    reader.setConf(conf);
    assertTrue(reader.hasNext());
    List<List<Writable>> record = reader.sequenceRecord();
    //        System.out.println(record.size());

    Iterator<List<Writable>> it = record.iterator();
    List<Writable> first = it.next();
    //        System.out.println(first);

    //Expected size: 80x46x3
    assertEquals(1, first.size());
    assertEquals(80 * 46 * 3, ((ArrayWritable) first.iterator().next()).length());
}

Example #10

Source File: CodecReaderTest.java From DataVec with Apache License 2.0

6 votes

@Test
public void testCodecReaderMeta() throws Exception {
    File file = new ClassPathResource("fire_lowres.mp4").getFile();
    SequenceRecordReader reader = new CodecRecordReader();
    Configuration conf = new Configuration();
    conf.set(CodecRecordReader.RAVEL, "true");
    conf.set(CodecRecordReader.START_FRAME, "160");
    conf.set(CodecRecordReader.TOTAL_FRAMES, "500");
    conf.set(CodecRecordReader.ROWS, "80");
    conf.set(CodecRecordReader.COLUMNS, "46");
    reader.initialize(new FileSplit(file));
    reader.setConf(conf);
    assertTrue(reader.hasNext());
    List<List<Writable>> record = reader.sequenceRecord();
    assertEquals(500, record.size()); //500 frames

    reader.reset();
    SequenceRecord seqR = reader.nextSequence();
    assertEquals(record, seqR.getSequenceRecord());
    RecordMetaData meta = seqR.getMetaData();
    //        System.out.println(meta);
    assertTrue(meta.getURI().toString().endsWith("fire_lowres.mp4"));

    SequenceRecord fromMeta = reader.loadSequenceFromMetaData(meta);
    assertEquals(seqR, fromMeta);
}

Example #11

Source File: CodecReaderTest.java From DataVec with Apache License 2.0

6 votes

@Test
public void testCodecReader() throws Exception {
    File file = new ClassPathResource("fire_lowres.mp4").getFile();
    SequenceRecordReader reader = new CodecRecordReader();
    Configuration conf = new Configuration();
    conf.set(CodecRecordReader.RAVEL, "true");
    conf.set(CodecRecordReader.START_FRAME, "160");
    conf.set(CodecRecordReader.TOTAL_FRAMES, "500");
    conf.set(CodecRecordReader.ROWS, "80");
    conf.set(CodecRecordReader.COLUMNS, "46");
    reader.initialize(new FileSplit(file));
    reader.setConf(conf);
    assertTrue(reader.hasNext());
    List<List<Writable>> record = reader.sequenceRecord();
    //        System.out.println(record.size());

    Iterator<List<Writable>> it = record.iterator();
    List<Writable> first = it.next();
    //        System.out.println(first);

    //Expected size: 80x46x3
    assertEquals(1, first.size());
    assertEquals(80 * 46 * 3, ((ArrayWritable) first.iterator().next()).length());
}

Example #12

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

5 votes

@Test(expected = ZeroLengthSequenceException.class)
public void testSequenceRecordReaderSingleReaderWithEmptySequenceThrows() throws Exception {
    SequenceRecordReader reader = new CSVSequenceRecordReader(1, ",");
    reader.initialize(new FileSplit(Resources.asFile("empty.txt")));

    new SequenceRecordReaderDataSetIterator(reader, 1, -1, 1, true).next();
}

Example #13

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

5 votes

@Test
public void testViaDataInputStream() throws Exception {

    File file = new ClassPathResource("datavec-data-codec/fire_lowres.mp4").getFile();
    SequenceRecordReader reader = new CodecRecordReader();
    Configuration conf = new Configuration();
    conf.set(CodecRecordReader.RAVEL, "true");
    conf.set(CodecRecordReader.START_FRAME, "160");
    conf.set(CodecRecordReader.TOTAL_FRAMES, "500");
    conf.set(CodecRecordReader.ROWS, "80");
    conf.set(CodecRecordReader.COLUMNS, "46");

    Configuration conf2 = new Configuration(conf);

    reader.initialize(new FileSplit(file));
    reader.setConf(conf);
    assertTrue(reader.hasNext());
    List<List<Writable>> expected = reader.sequenceRecord();


    SequenceRecordReader reader2 = new CodecRecordReader();
    reader2.setConf(conf2);

    DataInputStream dataInputStream = new DataInputStream(new FileInputStream(file));
    List<List<Writable>> actual = reader2.sequenceRecord(null, dataInputStream);

    assertEquals(expected, actual);
}

Example #14

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

5 votes

/** Constructor where features and labels come from the SAME RecordReader (i.e., target/label is a column in the
 * same data as the features)
 * @param reader SequenceRecordReader with data
 * @param miniBatchSize size of each minibatch
 * @param numPossibleLabels number of labels/classes for classification
 * @param labelIndex index in input of the label index. If in regression mode and numPossibleLabels > 1, labelIndex denotes the
 *                   first index for labels. Everything before that index will be treated as input(s) and
 *                   everything from that index (inclusive) to the end will be treated as output(s)
 * @param regression Whether output is for regression or classification
 */
public SequenceRecordReaderDataSetIterator(SequenceRecordReader reader, int miniBatchSize, int numPossibleLabels,
                int labelIndex, boolean regression) {
    this.recordReader = reader;
    this.labelsReader = null;
    this.miniBatchSize = miniBatchSize;
    this.regression = regression;
    this.labelIndex = labelIndex;
    this.numPossibleLabels = numPossibleLabels;
    this.singleSequenceReaderMode = true;
}

Example #15

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

5 votes

@Ignore
@Test
public void testNativeCodecReaderMeta() throws Exception {
    File file = new ClassPathResource("datavec-data-codec/fire_lowres.mp4").getFile();
    SequenceRecordReader reader = new NativeCodecRecordReader();
    Configuration conf = new Configuration();
    conf.set(CodecRecordReader.RAVEL, "true");
    conf.set(CodecRecordReader.START_FRAME, "160");
    conf.set(CodecRecordReader.TOTAL_FRAMES, "500");
    conf.set(CodecRecordReader.ROWS, "80");
    conf.set(CodecRecordReader.COLUMNS, "46");
    reader.initialize(new FileSplit(file));
    reader.setConf(conf);
    assertTrue(reader.hasNext());
    List<List<Writable>> record = reader.sequenceRecord();
    assertEquals(500, record.size()); //500 frames

    reader.reset();
    SequenceRecord seqR = reader.nextSequence();
    assertEquals(record, seqR.getSequenceRecord());
    RecordMetaData meta = seqR.getMetaData();
    //        System.out.println(meta);
    assertTrue(meta.getURI().toString().endsWith("fire_lowres.mp4"));

    SequenceRecord fromMeta = reader.loadSequenceFromMetaData(meta);
    assertEquals(seqR, fromMeta);
}

Example #16

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

5 votes

@Ignore
@Test
public void testNativeViaDataInputStream() throws Exception {

    File file = new ClassPathResource("datavec-data-codec/fire_lowres.mp4").getFile();
    SequenceRecordReader reader = new NativeCodecRecordReader();
    Configuration conf = new Configuration();
    conf.set(CodecRecordReader.RAVEL, "true");
    conf.set(CodecRecordReader.START_FRAME, "160");
    conf.set(CodecRecordReader.TOTAL_FRAMES, "500");
    conf.set(CodecRecordReader.ROWS, "80");
    conf.set(CodecRecordReader.COLUMNS, "46");

    Configuration conf2 = new Configuration(conf);

    reader.initialize(new FileSplit(file));
    reader.setConf(conf);
    assertTrue(reader.hasNext());
    List<List<Writable>> expected = reader.sequenceRecord();


    SequenceRecordReader reader2 = new NativeCodecRecordReader();
    reader2.setConf(conf2);

    DataInputStream dataInputStream = new DataInputStream(new FileInputStream(file));
    List<List<Writable>> actual = reader2.sequenceRecord(null, dataInputStream);

    assertEquals(expected, actual);
}

Example #17

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

5 votes

@Test
public void testSeqRRDSIArrayWritableOneReader() {

    List<List<Writable>> sequence1 = new ArrayList<>();
    sequence1.add(Arrays.asList((Writable) new NDArrayWritable(Nd4j.create(new double[] {1, 2, 3}, new long[]{1,3})),
                    new IntWritable(0)));
    sequence1.add(Arrays.asList((Writable) new NDArrayWritable(Nd4j.create(new double[] {4, 5, 6}, new long[]{1,3})),
                    new IntWritable(1)));
    List<List<Writable>> sequence2 = new ArrayList<>();
    sequence2.add(Arrays.asList((Writable) new NDArrayWritable(Nd4j.create(new double[] {7, 8, 9}, new long[]{1,3})),
                    new IntWritable(2)));
    sequence2.add(Arrays.asList((Writable) new NDArrayWritable(Nd4j.create(new double[] {10, 11, 12}, new long[]{1,3})),
                    new IntWritable(3)));


    SequenceRecordReader rr = new CollectionSequenceRecordReader(Arrays.asList(sequence1, sequence2));

    SequenceRecordReaderDataSetIterator iter = new SequenceRecordReaderDataSetIterator(rr, 2, 4, 1, false);

    DataSet ds = iter.next();

    INDArray expFeatures = Nd4j.create(2, 3, 2); //2 examples, 3 values per time step, 2 time steps
    expFeatures.tensorAlongDimension(0, 1, 2).assign(Nd4j.create(new double[][] {{1, 4}, {2, 5}, {3, 6}}));
    expFeatures.tensorAlongDimension(1, 1, 2).assign(Nd4j.create(new double[][] {{7, 10}, {8, 11}, {9, 12}}));

    INDArray expLabels = Nd4j.create(2, 4, 2);
    expLabels.tensorAlongDimension(0, 1, 2).assign(Nd4j.create(new double[][] {{1, 0}, {0, 1}, {0, 0}, {0, 0}}));
    expLabels.tensorAlongDimension(1, 1, 2).assign(Nd4j.create(new double[][] {{0, 0}, {0, 0}, {1, 0}, {0, 1}}));

    assertEquals(expFeatures, ds.getFeatures());
    assertEquals(expLabels, ds.getLabels());
}

Example #18

Source File: CSVVariableSlidingWindowRecordReaderTest.java From DataVec with Apache License 2.0

5 votes

@Test
public void testCSVVariableSlidingWindowRecordReader() throws Exception {
    int maxLinesPerSequence = 3;

    SequenceRecordReader seqRR = new CSVVariableSlidingWindowRecordReader(maxLinesPerSequence);
    seqRR.initialize(new FileSplit(new ClassPathResource("iris.dat").getFile()));

    CSVRecordReader rr = new CSVRecordReader();
    rr.initialize(new FileSplit(new ClassPathResource("iris.dat").getFile()));

    int count = 0;
    while (seqRR.hasNext()) {
        List<List<Writable>> next = seqRR.sequenceRecord();

        if(count==maxLinesPerSequence-1) {
            LinkedList<List<Writable>> expected = new LinkedList<>();
            for (int i = 0; i < maxLinesPerSequence; i++) {
                expected.addFirst(rr.next());
            }
            assertEquals(expected, next);

        }
        if(count==maxLinesPerSequence) {
            assertEquals(maxLinesPerSequence, next.size());
        }
        if(count==0) { // first seq should be length 1
            assertEquals(1, next.size());
        }
        if(count>151) { // last seq should be length 1
            assertEquals(1, next.size());
        }

        count++;
    }

    assertEquals(152, count);
}

Example #19

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

5 votes

@Test(expected = ZeroLengthSequenceException.class)
public void testSequenceRecordReaderTwoReadersWithEmptyLabelSequenceThrows() throws Exception {
    SequenceRecordReader featureReader = new CSVSequenceRecordReader(1, ",");
    SequenceRecordReader labelReader = new CSVSequenceRecordReader(1, ",");

    File f = Resources.asFile("csvsequence_0.txt");
    featureReader.initialize(new FileSplit(f));
    labelReader.initialize(new FileSplit(Resources.asFile("empty.txt")));

    new SequenceRecordReaderDataSetIterator(featureReader, labelReader, 1, -1, true).next();
}

Example #20

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

5 votes

@Test(expected = ZeroLengthSequenceException.class)
public void testSequenceRecordReaderTwoReadersWithEmptyFeatureSequenceThrows() throws Exception {
    SequenceRecordReader featureReader = new CSVSequenceRecordReader(1, ",");
    SequenceRecordReader labelReader = new CSVSequenceRecordReader(1, ",");

    featureReader.initialize(new FileSplit(Resources.asFile("empty.txt")));
    labelReader.initialize(
                    new FileSplit(Resources.asFile("csvsequencelabels_0.txt")));

    new SequenceRecordReaderDataSetIterator(featureReader, labelReader, 1, -1, true).next();
}

Example #21

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

5 votes

/**
 * Constructor where features and labels come from different RecordReaders (for example, different files)
 */
public SequenceRecordReaderDataSetIterator(SequenceRecordReader featuresReader, SequenceRecordReader labels,
                int miniBatchSize, int numPossibleLabels, boolean regression, AlignmentMode alignmentMode) {
    this.recordReader = featuresReader;
    this.labelsReader = labels;
    this.miniBatchSize = miniBatchSize;
    this.numPossibleLabels = numPossibleLabels;
    this.regression = regression;
    this.alignmentMode = alignmentMode;
    this.singleSequenceReaderMode = false;
}

Example #22

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

5 votes

@Test
public void testSequenceRecordReaderReset() throws Exception {
    File rootDir = temporaryFolder.newFolder();
    //need to manually extract
    for (int i = 0; i < 3; i++) {
        FileUtils.copyFile(Resources.asFile(String.format("csvsequence_%d.txt", i)), new File(rootDir, String.format("csvsequence_%d.txt", i)));
        FileUtils.copyFile(Resources.asFile(String.format("csvsequencelabels_%d.txt", i)), new File(rootDir, String.format("csvsequencelabels_%d.txt", i)));
    }
    String featuresPath = FilenameUtils.concat(rootDir.getAbsolutePath(), "csvsequence_%d.txt");
    String labelsPath = FilenameUtils.concat(rootDir.getAbsolutePath(), "csvsequencelabels_%d.txt");

    SequenceRecordReader featureReader = new CSVSequenceRecordReader(1, ",");
    SequenceRecordReader labelReader = new CSVSequenceRecordReader(1, ",");
    featureReader.initialize(new NumberedFileInputSplit(featuresPath, 0, 2));
    labelReader.initialize(new NumberedFileInputSplit(labelsPath, 0, 2));

    SequenceRecordReaderDataSetIterator iter =
                    new SequenceRecordReaderDataSetIterator(featureReader, labelReader, 1, 4, false);

    assertEquals(3, iter.inputColumns());
    assertEquals(4, iter.totalOutcomes());

    int nResets = 5;
    for (int i = 0; i < nResets; i++) {
        iter.reset();
        int count = 0;
        while (iter.hasNext()) {
            DataSet ds = iter.next();
            INDArray features = ds.getFeatures();
            INDArray labels = ds.getLabels();
            assertArrayEquals(new long[] {1, 3, 4}, features.shape());
            assertArrayEquals(new long[] {1, 4, 4}, labels.shape());
            count++;
        }
        assertEquals(3, count);
    }
}

Example #23

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

5 votes

/**
 * Write all sequences from the specified sequence record reader to the specified sequence record writer.
 * Closes the sequence record writer on completion.
 *
 * @param reader Sequence record reader (source of data)
 * @param writer Sequence record writer (location to write data)
 * @param closeOnCompletion if true: close the record writer once complete, via {@link SequenceRecordWriter#close()}
 * @throws IOException If underlying reader/writer throws an exception
 */
public static void convert(SequenceRecordReader reader, SequenceRecordWriter writer, boolean closeOnCompletion) throws IOException {

    if(!reader.hasNext()){
        throw new UnsupportedOperationException("Cannot convert SequenceRecordReader: reader has no next element");
    }

    while(reader.hasNext()){
        writer.write(reader.sequenceRecord());
    }

    if(closeOnCompletion){
        writer.close();
    }
}

Example #24

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

5 votes

@Test
public void testSequenceRecordReaderMeta() throws Exception {
    File rootDir = temporaryFolder.newFolder();
    //need to manually extract
    for (int i = 0; i < 3; i++) {
        FileUtils.copyFile(Resources.asFile(String.format("csvsequence_%d.txt", i)), new File(rootDir, String.format("csvsequence_%d.txt", i)));
        FileUtils.copyFile(Resources.asFile(String.format("csvsequencelabels_%d.txt", i)), new File(rootDir, String.format("csvsequencelabels_%d.txt", i)));
    }
    String featuresPath = FilenameUtils.concat(rootDir.getAbsolutePath(), "csvsequence_%d.txt");
    String labelsPath = FilenameUtils.concat(rootDir.getAbsolutePath(), "csvsequencelabels_%d.txt");

    SequenceRecordReader featureReader = new CSVSequenceRecordReader(1, ",");
    SequenceRecordReader labelReader = new CSVSequenceRecordReader(1, ",");
    featureReader.initialize(new NumberedFileInputSplit(featuresPath, 0, 2));
    labelReader.initialize(new NumberedFileInputSplit(labelsPath, 0, 2));

    SequenceRecordReaderDataSetIterator iter =
                    new SequenceRecordReaderDataSetIterator(featureReader, labelReader, 1, 4, false);

    iter.setCollectMetaData(true);

    assertEquals(3, iter.inputColumns());
    assertEquals(4, iter.totalOutcomes());

    while (iter.hasNext()) {
        DataSet ds = iter.next();
        List<RecordMetaData> meta = ds.getExampleMetaData(RecordMetaData.class);
        DataSet fromMeta = iter.loadFromMetaData(meta);

        assertEquals(ds, fromMeta);
    }
}

Example #25

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

5 votes

@Test
public void testCSVVariableSlidingWindowRecordReader() throws Exception {
    int maxLinesPerSequence = 3;

    SequenceRecordReader seqRR = new CSVVariableSlidingWindowRecordReader(maxLinesPerSequence);
    seqRR.initialize(new FileSplit(new ClassPathResource("datavec-api/iris.dat").getFile()));

    CSVRecordReader rr = new CSVRecordReader();
    rr.initialize(new FileSplit(new ClassPathResource("datavec-api/iris.dat").getFile()));

    int count = 0;
    while (seqRR.hasNext()) {
        List<List<Writable>> next = seqRR.sequenceRecord();

        if(count==maxLinesPerSequence-1) {
            LinkedList<List<Writable>> expected = new LinkedList<>();
            for (int i = 0; i < maxLinesPerSequence; i++) {
                expected.addFirst(rr.next());
            }
            assertEquals(expected, next);

        }
        if(count==maxLinesPerSequence) {
            assertEquals(maxLinesPerSequence, next.size());
        }
        if(count==0) { // first seq should be length 1
            assertEquals(1, next.size());
        }
        if(count>151) { // last seq should be length 1
            assertEquals(1, next.size());
        }

        count++;
    }

    assertEquals(152, count);
}

Example #26

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

5 votes

@Test
public void testCSVNLinesSequenceRecordReader() throws Exception {
    int nLinesPerSequence = 10;

    SequenceRecordReader seqRR = new CSVNLinesSequenceRecordReader(nLinesPerSequence);
    seqRR.initialize(new FileSplit(new ClassPathResource("datavec-api/iris.dat").getFile()));

    CSVRecordReader rr = new CSVRecordReader();
    rr.initialize(new FileSplit(new ClassPathResource("datavec-api/iris.dat").getFile()));

    int count = 0;
    while (seqRR.hasNext()) {
        List<List<Writable>> next = seqRR.sequenceRecord();

        List<List<Writable>> expected = new ArrayList<>();
        for (int i = 0; i < nLinesPerSequence; i++) {
            expected.add(rr.next());
        }

        assertEquals(10, next.size());
        assertEquals(expected, next);

        count++;
    }

    assertEquals(150 / nLinesPerSequence, count);
}

Example #27

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

5 votes

@Test
public void testEvalSplitting2(){
    List<List<Writable>> seqFeatures = new ArrayList<>();
    List<Writable> step = Arrays.<Writable>asList(new FloatWritable(0), new FloatWritable(0), new FloatWritable(0));
    for( int i=0; i<30; i++ ){
        seqFeatures.add(step);
    }
    List<List<Writable>> seqLabels = Collections.singletonList(Collections.<Writable>singletonList(new FloatWritable(0)));

    SequenceRecordReader fsr = new CollectionSequenceRecordReader(Collections.singletonList(seqFeatures));
    SequenceRecordReader lsr = new CollectionSequenceRecordReader(Collections.singletonList(seqLabels));


    DataSetIterator testData = new SequenceRecordReaderDataSetIterator(fsr, lsr, 1, -1, true,
            SequenceRecordReaderDataSetIterator.AlignmentMode.ALIGN_END);

    MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder().seed(123)
            .list()
            .layer(0, new LSTM.Builder().activation(Activation.TANH).nIn(3).nOut(3).build())
            .layer(1, new RnnOutputLayer.Builder().activation(Activation.SIGMOID).lossFunction(LossFunctions.LossFunction.XENT)
                    .nIn(3).nOut(1).build())
            .backpropType(BackpropType.TruncatedBPTT).tBPTTForwardLength(10).tBPTTBackwardLength(10)
            .build();
    MultiLayerNetwork net = new MultiLayerNetwork(conf);
    net.init();

    net.evaluate(testData);
}

Example #28

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

5 votes

private static SequenceRecordReader getReader() {
    SequenceRecordReader seqRR = new CodecRecordReader();
    Configuration conf = new Configuration();
    conf.set(CodecRecordReader.RAVEL, "true");
    conf.set(CodecRecordReader.START_FRAME, "0");
    conf.set(CodecRecordReader.TOTAL_FRAMES, "25");
    conf.set(CodecRecordReader.ROWS, "64");
    conf.set(CodecRecordReader.COLUMNS, "64");
    seqRR.setConf(conf);
    return seqRR;
}

Example #29

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

5 votes

@Test
public void test() throws Exception {

    File f = testDir.newFolder();
    File source = new File(f, "temp.csv");
    String str = "a,b,c\n1,2,3,4";
    FileUtils.writeStringToFile(source, str, StandardCharsets.UTF_8);

    SequenceRecordReader rr = new CSVLineSequenceRecordReader();
    rr.initialize(new FileSplit(source));

    List<List<Writable>> exp0 = Arrays.asList(
            Collections.<Writable>singletonList(new Text("a")),
            Collections.<Writable>singletonList(new Text("b")),
            Collections.<Writable>singletonList(new Text("c")));

    List<List<Writable>> exp1 = Arrays.asList(
            Collections.<Writable>singletonList(new Text("1")),
            Collections.<Writable>singletonList(new Text("2")),
            Collections.<Writable>singletonList(new Text("3")),
            Collections.<Writable>singletonList(new Text("4")));

    for( int i=0; i<3; i++ ) {
        int count = 0;
        while (rr.hasNext()) {
            List<List<Writable>> next = rr.sequenceRecord();
            if (count++ == 0) {
                assertEquals(exp0, next);
            } else {
                assertEquals(exp1, next);
            }
        }

        assertEquals(2, count);

        rr.reset();
    }
}

Example #30

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;
        }