Examples with MemoryWorkspace org.nd4j.linalg.api.memory.MemoryWorkspace used on opensource projects

Example 16 with MemoryWorkspace

use of org.nd4j.linalg.api.memory.MemoryWorkspace in project nd4j by deeplearning4j.

the class EndlessWorkspaceTests method endlessTestSerDe1.

@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 17 with MemoryWorkspace

use of org.nd4j.linalg.api.memory.MemoryWorkspace in project nd4j by deeplearning4j.

the class EndlessWorkspaceTests method endlessTest4.

@Test
public void endlessTest4() throws Exception {
    Nd4j.getWorkspaceManager().setDefaultWorkspaceConfiguration(WorkspaceConfiguration.builder().initialSize(100 * 1024L * 1024L).build());
    while (true) {
        try (MemoryWorkspace workspace1 = Nd4j.getWorkspaceManager().getAndActivateWorkspace("WS_1")) {
            for (int i = 0; i < 1000; i++) {
                INDArray array = Nd4j.createUninitialized(RandomUtils.nextInt(1, 50), RandomUtils.nextInt(1, 50));
                INDArray mean = array.max(1);
            }
            for (int i = 0; i < 1000; i++) {
                INDArray array = Nd4j.createUninitialized(RandomUtils.nextInt(1, 100));
                array.maxNumber().doubleValue();
            }
        }
    }
}

Example 18 with MemoryWorkspace

use of org.nd4j.linalg.api.memory.MemoryWorkspace in project nd4j by deeplearning4j.

the class EndlessWorkspaceTests method endlessTest2.

/**
 * This test checks for allocation from workspace AND spills
 * @throws Exception
 */
@Test
public void endlessTest2() throws Exception {
    Nd4j.getWorkspaceManager().setDefaultWorkspaceConfiguration(WorkspaceConfiguration.builder().initialSize(10 * 1024L * 1024L).build());
    Nd4j.getMemoryManager().togglePeriodicGc(false);
    AtomicLong counter = new AtomicLong(0);
    while (true) {
        try (MemoryWorkspace workspace = Nd4j.getWorkspaceManager().getAndActivateWorkspace()) {
            long time1 = System.nanoTime();
            INDArray array = Nd4j.create(2 * 1024 * 1024);
            long time2 = System.nanoTime();
            array.addi(1.0f);
            assertEquals(1.0f, array.meanNumber().floatValue(), 0.1f);
            long time3 = System.nanoTime();
            INDArray array2 = Nd4j.create(3 * 1024 * 1024);
            long time4 = System.nanoTime();
            if (counter.incrementAndGet() % 1000 == 0) {
                log.info("{} iterations passed... Allocation time: {} vs {} (ns)", counter.get(), time2 - time1, time4 - time3);
                System.gc();
            }
        }
    }
}

Example 19 with MemoryWorkspace

use of org.nd4j.linalg.api.memory.MemoryWorkspace in project nd4j by deeplearning4j.

the class SpecialWorkspaceTests method testVariableTimeSeries1.

@Test
public void testVariableTimeSeries1() throws Exception {
    WorkspaceConfiguration configuration = WorkspaceConfiguration.builder().initialSize(0).overallocationLimit(3.0).policyAllocation(AllocationPolicy.OVERALLOCATE).policySpill(SpillPolicy.EXTERNAL).policyLearning(LearningPolicy.FIRST_LOOP).policyReset(ResetPolicy.ENDOFBUFFER_REACHED).build();
    try (MemoryWorkspace ws = Nd4j.getWorkspaceManager().getAndActivateWorkspace(configuration, "WS1")) {
        Nd4j.create(500);
        Nd4j.create(500);
    }
    Nd4jWorkspace workspace = (Nd4jWorkspace) Nd4j.getWorkspaceManager().getWorkspaceForCurrentThread("WS1");
    workspace.enableDebug(true);
    assertEquals(0, workspace.getStepNumber());
    long requiredMemory = 1000 * Nd4j.sizeOfDataType();
    long shiftedSize = ((long) (requiredMemory * 1.3)) + (8 - (((long) (requiredMemory * 1.3)) % 8));
    assertEquals(requiredMemory, workspace.getSpilledSize());
    assertEquals(shiftedSize, workspace.getInitialBlockSize());
    assertEquals(workspace.getInitialBlockSize() * 4, workspace.getCurrentSize());
    try (MemoryWorkspace ws = Nd4j.getWorkspaceManager().getAndActivateWorkspace("WS1")) {
        Nd4j.create(2000);
    }
    assertEquals(0, workspace.getStepNumber());
    assertEquals(1000 * Nd4j.sizeOfDataType(), workspace.getSpilledSize());
    assertEquals(2000 * Nd4j.sizeOfDataType(), workspace.getPinnedSize());
    assertEquals(0, workspace.getDeviceOffset());
    // FIXME: fix this!
    // assertEquals(0, workspace.getHostOffset());
    assertEquals(0, workspace.getThisCycleAllocations());
    log.info("------------------");
    assertEquals(1, workspace.getNumberOfPinnedAllocations());
    for (int e = 0; e < 4; e++) {
        for (int i = 0; i < 4; i++) {
            try (MemoryWorkspace ws = Nd4j.getWorkspaceManager().getAndActivateWorkspace(configuration, "WS1")) {
                Nd4j.create(500);
                Nd4j.create(500);
            }
            assertEquals("Failed on iteration " + i, (i + 1) * workspace.getInitialBlockSize(), workspace.getDeviceOffset());
        }
        if (e >= 2) {
            assertEquals("Failed on iteration " + e, 0, workspace.getNumberOfPinnedAllocations());
        } else {
            assertEquals("Failed on iteration " + e, 1, workspace.getNumberOfPinnedAllocations());
        }
    }
    assertEquals(0, workspace.getSpilledSize());
    assertEquals(0, workspace.getPinnedSize());
    assertEquals(0, workspace.getNumberOfPinnedAllocations());
    assertEquals(0, workspace.getNumberOfExternalAllocations());
    log.info("Workspace state after first block: ---------------------------------------------------------");
    Nd4j.getWorkspaceManager().printAllocationStatisticsForCurrentThread();
    log.info("--------------------------------------------------------------------------------------------");
    // we just do huge loop now, with pinned stuff in it
    for (int i = 0; i < 100; i++) {
        try (MemoryWorkspace ws = Nd4j.getWorkspaceManager().getAndActivateWorkspace(configuration, "WS1")) {
            Nd4j.create(500);
            Nd4j.create(500);
            Nd4j.create(500);
            assertEquals(1500 * Nd4j.sizeOfDataType(), workspace.getThisCycleAllocations());
        }
    }
    assertEquals(0, workspace.getSpilledSize());
    assertNotEquals(0, workspace.getPinnedSize());
    assertNotEquals(0, workspace.getNumberOfPinnedAllocations());
    assertEquals(0, workspace.getNumberOfExternalAllocations());
    // and we do another clean loo, without pinned stuff in it, to ensure all pinned allocates are gone
    for (int i = 0; i < 100; i++) {
        try (MemoryWorkspace ws = Nd4j.getWorkspaceManager().getAndActivateWorkspace(configuration, "WS1")) {
            Nd4j.create(500);
            Nd4j.create(500);
        }
    }
    assertEquals(0, workspace.getSpilledSize());
    assertEquals(0, workspace.getPinnedSize());
    assertEquals(0, workspace.getNumberOfPinnedAllocations());
    assertEquals(0, workspace.getNumberOfExternalAllocations());
    log.info("Workspace state after second block: ---------------------------------------------------------");
    Nd4j.getWorkspaceManager().printAllocationStatisticsForCurrentThread();
}

Example 20 with MemoryWorkspace

use of org.nd4j.linalg.api.memory.MemoryWorkspace in project nd4j by deeplearning4j.

the class CpuWorkspaceManager method createNewWorkspace.

@Override
public MemoryWorkspace createNewWorkspace(@NonNull WorkspaceConfiguration configuration, @NonNull String id) {
    ensureThreadExistense();
    MemoryWorkspace workspace = new CpuWorkspace(configuration, id);
    backingMap.get().put(id, workspace);
    pickReference(workspace);
    return workspace;
}