Java Code Examples for org.nd4j.linalg.dataset.DataSet#load()

The following examples show how to use org.nd4j.linalg.dataset.DataSet#load() . 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: SporadicTests.java    From nd4j with Apache License 2.0 6 votes vote down vote up 
@Test
public void testDataSetSaveLost() throws Exception {
    INDArray features = Nd4j.linspace(1, 16 * 784, 16 * 784).reshape(16, 784);
    INDArray labels = Nd4j.linspace(1, 160, 160).reshape(16, 10);

    for (int i = 0; i < 100; i++) {
        DataSet ds = new DataSet(features, labels);

        File tempFile = File.createTempFile("dataset", "temp");
        tempFile.deleteOnExit();

        ds.save(tempFile);

        DataSet restore = new DataSet();
        restore.load(tempFile);

        assertEquals(features, restore.getFeatureMatrix());
        assertEquals(labels, restore.getLabels());

    }
}
Example 2
Source File: EndlessWorkspaceTests.java    From nd4j with Apache License 2.0 5 votes vote down vote up 
@Test
public void endlessTestSerDe1() throws Exception {
    INDArray features = Nd4j.create(32, 3, 224, 224);
    INDArray labels = Nd4j.create(32, 200);
    File tmp = File.createTempFile("12dadsad", "dsdasds");
    float[] array = new float[33 * 3 * 224 * 224];
    DataSet ds = new DataSet(features, labels);
    ds.save(tmp);

    WorkspaceConfiguration wsConf = WorkspaceConfiguration.builder().initialSize(0)
                    .policyLearning(LearningPolicy.FIRST_LOOP).build();

    while (true) {

        try (MemoryWorkspace workspace = Nd4j.getWorkspaceManager().getAndActivateWorkspace(wsConf, "serde")) {
            /*
                        try (FileOutputStream fos = new FileOutputStream(tmp); BufferedOutputStream bos = new BufferedOutputStream(fos)) {
            SerializationUtils.serialize(array, fos);
                        }
            
                        try (FileInputStream fis = new FileInputStream(tmp); BufferedInputStream bis = new BufferedInputStream(fis)) {
            long time1 = System.currentTimeMillis();
            float[] arrayR = (float[]) SerializationUtils.deserialize(bis);
            long time2 = System.currentTimeMillis();
            
            log.info("Load time: {}", time2 - time1);
                        }
            */



            long time1 = System.currentTimeMillis();
            ds.load(tmp);
            long time2 = System.currentTimeMillis();

            log.info("Load time: {}", time2 - time1);
        }
    }
}
Example 3
Source File: InFileDataSetCache.java    From nd4j with Apache License 2.0 5 votes vote down vote up 
@Override
public DataSet get(String key) {
    File file = resolveKey(key);

    if (!file.exists()) {
        return null;
    } else if (!file.isFile()) {
        throw new IllegalStateException("ERROR: cannot read DataSet: cache path " + file + " is not a file");
    } else {
        DataSet ds = new DataSet();
        ds.load(file);
        return ds;
    }
}
Example 4
Source File: EndlessWorkspaceTests.java    From deeplearning4j with Apache License 2.0 5 votes vote down vote up 
@Test
public void endlessTestSerDe1() throws Exception {
    INDArray features = Nd4j.create(32, 3, 224, 224);
    INDArray labels = Nd4j.create(32, 200);
    File tmp = File.createTempFile("12dadsad", "dsdasds");
    float[] array = new float[33 * 3 * 224 * 224];
    DataSet ds = new DataSet(features, labels);
    ds.save(tmp);

    WorkspaceConfiguration wsConf = WorkspaceConfiguration.builder().initialSize(0)
                    .policyLearning(LearningPolicy.FIRST_LOOP).build();

    while (true) {

        try (MemoryWorkspace workspace = Nd4j.getWorkspaceManager().getAndActivateWorkspace(wsConf, "serde")) {
            /*
                        try (FileOutputStream fos = new FileOutputStream(tmp); BufferedOutputStream bos = new BufferedOutputStream(fos)) {
            SerializationUtils.serialize(array, fos);
                        }
            
                        try (FileInputStream fis = new FileInputStream(tmp); BufferedInputStream bis = new BufferedInputStream(fis)) {
            long time1 = System.currentTimeMillis();
            float[] arrayR = (float[]) SerializationUtils.deserialize(bis);
            long time2 = System.currentTimeMillis();
            
            log.info("Load time: {}", time2 - time1);
                        }
            */



            long time1 = System.currentTimeMillis();
            ds.load(tmp);
            long time2 = System.currentTimeMillis();

            log.info("Load time: {}", time2 - time1);
        }
    }
}
Example 5
Source File: InFileDataSetCache.java    From deeplearning4j with Apache License 2.0 5 votes vote down vote up 
@Override
public DataSet get(String key) {
    File file = resolveKey(key);

    if (!file.exists()) {
        return null;
    } else if (!file.isFile()) {
        throw new IllegalStateException("ERROR: cannot read DataSet: cache path " + file + " is not a file");
    } else {
        DataSet ds = new DataSet();
        ds.load(file);
        return ds;
    }
}
Example 6
Source File: SerializedDataSetLoader.java    From deeplearning4j with Apache License 2.0 5 votes vote down vote up 
@Override
public DataSet load(Source source) throws IOException {
    DataSet ds = new DataSet();
    try(InputStream is = source.getInputStream()){
        ds.load(is);
    }
    return ds;
}
Example 7
Source File: PortableDataStreamDataSetIterator.java    From deeplearning4j with Apache License 2.0 5 votes vote down vote up 
protected DataSet load(PortableDataStream pds) {
    DataSet ds = new DataSet();
    try (InputStream is = pds.open()) {
        ds.load(is);
    } catch (IOException e) {
        throw new RuntimeException("Error loading DataSet at path " + pds.getPath() + " - DataSet may be corrupt or invalid." +
                " Spark DataSets can be validated using org.deeplearning4j.spark.util.data.SparkDataValidation", e);
    }
    cursor++;
    return ds;
}
Example 8
Source File: InMemoryDataSetCache.java    From nd4j with Apache License 2.0 4 votes vote down vote up 
@Override
public DataSet get(String key) {

    if (!cache.containsKey(key)) {
        return null;
    }

    byte[] data = cache.get(key);

    ByteArrayInputStream is = new ByteArrayInputStream(data);

    DataSet ds = new DataSet();

    ds.load(is);

    return ds;
}
Example 9
Source File: InMemoryDataSetCache.java    From deeplearning4j with Apache License 2.0 4 votes vote down vote up 
@Override
public DataSet get(String key) {

    if (!cache.containsKey(key)) {
        return null;
    }

    byte[] data = cache.get(key);

    ByteArrayInputStream is = new ByteArrayInputStream(data);

    DataSet ds = new DataSet();

    ds.load(is);

    return ds;
}
Example 10
Source File: FileDataSetIterator.java    From deeplearning4j with Apache License 2.0 4 votes vote down vote up 
@Override
protected DataSet load(File f) {
    DataSet ds = new DataSet();
    ds.load(f);
    return ds;
}
Example 11
Source File: DataSetDeserializer.java    From deeplearning4j with Apache License 2.0 4 votes vote down vote up 
@Override
public <T> T call(File file) {
    DataSet dataSet = new DataSet();
    dataSet.load(file);
    return (T) dataSet;
}
Example 12
Source File: ValidateDataSetFn.java    From deeplearning4j with Apache License 2.0 4 votes vote down vote up 
@Override
public ValidationResult call(String path) throws Exception {
    if (fileSystem == null) {
        Configuration c = conf == null ? DefaultHadoopConfig.get() : conf.getValue().getConfiguration();
        try {
            fileSystem = FileSystem.get(new URI(path), c);
        } catch (Exception e) {
            throw new RuntimeException(e);
        }
    }

    ValidationResult ret = new ValidationResult();
    ret.setCountTotal(1);

    boolean shouldDelete = false;
    boolean loadSuccessful = false;
    DataSet ds = new DataSet();
    Path p = new Path(path);

    if(fileSystem.isDirectory(p)){
        ret.setCountTotal(0);
        return ret;
    }

    if (!fileSystem.exists(p)) {
        ret.setCountMissingFile(1);
        return ret;
    }

    try (FSDataInputStream inputStream = fileSystem.open(p, BUFFER_SIZE)) {
        ds.load(inputStream);
        loadSuccessful = true;
    } catch (RuntimeException t) {
        shouldDelete = deleteInvalid;
        ret.setCountLoadingFailure(1);
    }

    boolean isValid = loadSuccessful;
    if (loadSuccessful) {
        //Validate
        if (ds.getFeatures() == null) {
            ret.setCountMissingFeatures(1);
            isValid = false;
        } else {
            if(featuresShape != null && !validateArrayShape(featuresShape, ds.getFeatures())){
                ret.setCountInvalidFeatures(1);
                isValid = false;
            }
        }

        if(ds.getLabels() == null){
            ret.setCountMissingLabels(1);
            isValid = false;
        } else {
            if(labelsShape != null && !validateArrayShape(labelsShape, ds.getLabels())){
                ret.setCountInvalidLabels(1);
                isValid = false;
            }
        }

        if(!isValid && deleteInvalid){
            shouldDelete = true;
        }
    }

    if (isValid) {
        ret.setCountTotalValid(1);
    } else {
        ret.setCountTotalInvalid(1);
    }

    if (shouldDelete) {
        fileSystem.delete(p, false);
        ret.setCountInvalidDeleted(1);
    }

    return ret;
}
Example 13
Source File: TestExport.java    From deeplearning4j with Apache License 2.0 4 votes vote down vote up 
@Test
    public void testBatchAndExportDataSetsFunction() throws Exception {
        String baseDir = System.getProperty("java.io.tmpdir");
        baseDir = FilenameUtils.concat(baseDir, "dl4j_spark_testBatchAndExport/");
        baseDir = baseDir.replaceAll("\\\\", "/");
        File f = new File(baseDir);
        if (f.exists())
            FileUtils.deleteDirectory(f);
        f.mkdir();
        f.deleteOnExit();
        int minibatchSize = 5;
        int nIn = 4;
        int nOut = 3;

        List<DataSet> dataSets = new ArrayList<>();
        dataSets.add(new DataSet(Nd4j.create(10, nIn), Nd4j.create(10, nOut))); //Larger than minibatch size -> tests splitting
        for (int i = 0; i < 98; i++) {
            if (i % 2 == 0) {
                dataSets.add(new DataSet(Nd4j.create(5, nIn), Nd4j.create(5, nOut)));
            } else {
                dataSets.add(new DataSet(Nd4j.create(1, nIn), Nd4j.create(1, nOut)));
                dataSets.add(new DataSet(Nd4j.create(1, nIn), Nd4j.create(1, nOut)));
                dataSets.add(new DataSet(Nd4j.create(3, nIn), Nd4j.create(3, nOut)));
            }
        }

        Collections.shuffle(dataSets, new Random(12345));

        JavaRDD<DataSet> rdd = sc.parallelize(dataSets);
        rdd = rdd.repartition(1); //For testing purposes (should get exactly 100 out, but maybe more with more partitions)


        JavaRDD<String> pathsRdd = rdd.mapPartitionsWithIndex(
                        new BatchAndExportDataSetsFunction(minibatchSize, "file:///" + baseDir), true);

        List<String> paths = pathsRdd.collect();
        assertEquals(100, paths.size());

        File[] files = f.listFiles();
        assertNotNull(files);

        int count = 0;
        for (File file : files) {
            if (!file.getPath().endsWith(".bin"))
                continue;
//            System.out.println(file);
            DataSet ds = new DataSet();
            ds.load(file);
            assertEquals(minibatchSize, ds.numExamples());

            count++;
        }

        assertEquals(100, count);

        FileUtils.deleteDirectory(f);
    }