org.nd4j.linalg.api.memory.enums.LearningPolicy Java Examples

@Test
public void testReallocationWorkspace() {
    WorkspaceConfiguration initialConfig = WorkspaceConfiguration.builder().initialSize(10 * 1024L * 1024L)
                    .policyAllocation(AllocationPolicy.STRICT).policyLearning(LearningPolicy.NONE).build();
    MemoryWorkspace workspace = Nd4j.getWorkspaceManager().getAndActivateWorkspace(initialConfig, "SOME_ID");

    DataBuffer buffer = Nd4j.createBuffer(new int[] {1, 2, 3, 4});
    val old = buffer.asInt();
    assertTrue(buffer.isAttached());
    assertEquals(4, buffer.capacity());
    buffer.reallocate(6);
    assertEquals(6, buffer.capacity());
    val newContent = buffer.asInt();
    assertEquals(6, newContent.length);
    assertArrayEquals(old, Arrays.copyOf(newContent, old.length));
    workspace.close();
}
 

protected void initializeWorkspaces(long size) {
    WorkspaceConfiguration configuration = WorkspaceConfiguration.builder().initialSize(size)
                    .overallocationLimit(bufferSize).policyReset(ResetPolicy.ENDOFBUFFER_REACHED)
                    .policyAllocation(AllocationPolicy.OVERALLOCATE).policySpill(SpillPolicy.EXTERNAL)
                    .policyLearning(LearningPolicy.NONE).build();

    int numDevices = Nd4j.getAffinityManager().getNumberOfDevices();
    int cDevice = Nd4j.getAffinityManager().getDeviceForCurrentThread();
    for (int i = 0; i < numDevices; i++) {
        Nd4j.getAffinityManager().unsafeSetDevice(i);
        workspaces.add(Nd4j.getWorkspaceManager().createNewWorkspace(configuration, "IDSC-" + i, i));
    }

    Nd4j.getAffinityManager().unsafeSetDevice(cDevice);
    numWorkspaces = numDevices;
    isInitialized = true;
}
 

@Test
    public void testWorkspaceBool(){
        val conf = WorkspaceConfiguration.builder().minSize(10 * 1024 * 1024)
                .overallocationLimit(1.0).policyAllocation(AllocationPolicy.OVERALLOCATE)
                .policyLearning(LearningPolicy.FIRST_LOOP).policyMirroring(MirroringPolicy.FULL)
                .policySpill(SpillPolicy.EXTERNAL).build();

        val ws = Nd4j.getWorkspaceManager().getWorkspaceForCurrentThread(conf, "WS");

        for( int i=0; i<10; i++ ) {
            try (val workspace = (Nd4jWorkspace)ws.notifyScopeEntered() ) {
                val bool = Nd4j.create(DataType.BOOL, 1, 10);
                val dbl = Nd4j.create(DataType.DOUBLE, 1, 10);

                val boolAttached = bool.isAttached();
                val doubleAttached = dbl.isAttached();

//                System.out.println(i + "\tboolAttached=" + boolAttached + ", doubleAttached=" + doubleAttached );
                //System.out.println("bool: " + bool);        //java.lang.IllegalStateException: Indexer must never be null
                //System.out.println("double: " + dbl);
            }
        }
    }
 

@Test
    public void testBasicMechanics_1() {
        val fShape = new long[]{128, 784};
        val lShape = new long[] {128, 10};
        val prefetchSize = 24;
        val configuration = WorkspaceConfiguration.builder().minSize(10 * 1024L * 1024L)
                .overallocationLimit(prefetchSize + 1).policyReset(ResetPolicy.ENDOFBUFFER_REACHED)
                .policyLearning(LearningPolicy.FIRST_LOOP).policyAllocation(AllocationPolicy.OVERALLOCATE)
                .policySpill(SpillPolicy.REALLOCATE).build();

        for (int e = 0; e < 100; e++) {
            try (val ws = Nd4j.getWorkspaceManager().getAndActivateWorkspace(configuration, "randomNameHere" + 119)) {
                val fArray = Nd4j.create(fShape).assign(e);
                val lArray = Nd4j.create(lShape).assign(e);

//                log.info("Current offset: {}; Current size: {};", ws.getCurrentOffset(), ws.getCurrentSize());
            }
        }
    }
 

@Test
public void endlessTest6() {
    Nd4j.getMemoryManager().togglePeriodicGc(false);
    WorkspaceConfiguration wsConf = WorkspaceConfiguration.builder().initialSize(10 * 1024L * 1024L)
                    .policyLearning(LearningPolicy.NONE).build();
    final AtomicLong cnt = new AtomicLong(0);
    while (true) {

        try (MemoryWorkspace ws = Nd4j.getWorkspaceManager().getAndActivateWorkspace(wsConf, "PEW-PEW")) {
            INDArray array = Nd4j.create(new float[] {1f, 2f, 3f, 4f, 5f});
        }

        if (cnt.incrementAndGet() % 1000000 == 0)
            log.info("TotalBytes: {}", Pointer.totalBytes());
    }
}
 

@Test
public void endlessTest5() throws Exception {
    while (true) {
        Thread thread = new Thread(new Runnable() {
            @Override
            public void run() {
                WorkspaceConfiguration wsConf = WorkspaceConfiguration.builder().initialSize(10 * 1024L * 1024L)
                                .policyLearning(LearningPolicy.NONE).build();

                try (MemoryWorkspace ws = Nd4j.getWorkspaceManager().getAndActivateWorkspace(wsConf, "PEW-PEW")) {
                    INDArray array = Nd4j.create(10);
                }
            }
        });

        thread.start();
        thread.join();

        System.gc();
    }
}
 

@Test
public void testReallocationWorkspace() {
    WorkspaceConfiguration initialConfig = WorkspaceConfiguration.builder().initialSize(10 * 1024L * 1024L)
                    .policyAllocation(AllocationPolicy.STRICT).policyLearning(LearningPolicy.NONE).build();
    MemoryWorkspace workspace = Nd4j.getWorkspaceManager().getAndActivateWorkspace(initialConfig, "SOME_ID");

    DataBuffer buffer = Nd4j.createBuffer(new float[] {1, 2, 3, 4});
    assertTrue(buffer.isAttached());
    float[] old = buffer.asFloat();
    assertEquals(4, buffer.capacity());
    buffer.reallocate(6);
    assertEquals(6, buffer.capacity());
    float[] newBuf = buffer.asFloat();
    assertArrayEquals(old, newBuf, 1e-4F);
    workspace.close();
}
 

@Test
public void testReallocationWorkspace() {
    WorkspaceConfiguration initialConfig = WorkspaceConfiguration.builder().initialSize(10 * 1024L * 1024L)
                    .policyAllocation(AllocationPolicy.STRICT).policyLearning(LearningPolicy.NONE).build();
    MemoryWorkspace workspace = Nd4j.getWorkspaceManager().getAndActivateWorkspace(initialConfig, "SOME_ID");

    DataBuffer buffer = Nd4j.createBuffer(new double[] {1, 2, 3, 4});
    double[] old = buffer.asDouble();
    assertTrue(buffer.isAttached());
    assertEquals(4, buffer.capacity());
    buffer.reallocate(6);
    assertEquals(6, buffer.capacity());
    assertArrayEquals(old, Arrays.copyOf(buffer.asDouble(), 4), 1e-1);
    workspace.close();

}
 

@Test
public void testWorkspaceAccounting_1() {
    val deviceId = Nd4j.getAffinityManager().getDeviceForCurrentThread();
    val wsConf = WorkspaceConfiguration.builder()
            .initialSize(10 * 1024 * 1024)
            .policyAllocation(AllocationPolicy.STRICT)
            .policyLearning(LearningPolicy.FIRST_LOOP)
            .build();

    val before = Nd4j.getMemoryManager().allocatedMemory(deviceId);

    val workspace = Nd4j.getWorkspaceManager().createNewWorkspace(wsConf, "random_name_here");

    val middle = Nd4j.getMemoryManager().allocatedMemory(deviceId);

    workspace.destroyWorkspace(true);

    val after = Nd4j.getMemoryManager().allocatedMemory(deviceId);

    log.info("Before: {}; Middle: {}; After: {}", before, middle, after);
    assertTrue(middle > before);
    assertTrue(after < middle);
}
 

@Test
public void testCircularWorkspaceAsymmetry_3() {
    // circular workspace mode
    val configuration = WorkspaceConfiguration.builder().initialSize(10 * 1024 * 1024)
            .policyReset(ResetPolicy.ENDOFBUFFER_REACHED).policyAllocation(AllocationPolicy.STRICT)
            .policySpill(SpillPolicy.FAIL).policyLearning(LearningPolicy.NONE).build();

    val root = Nd4j.create(DataType.FLOAT, 1000000).assign(119);

    for (int e = 0; e < 100; e++) {
        try (val ws = (CudaWorkspace) Nd4j.getWorkspaceManager().getAndActivateWorkspace(configuration, "circular_ws")) {
            val array = Nd4j.create(DataType.FLOAT, root.shape());
            array.assign(root);

            val second = Nd4j.create(DataType.FLOAT, root.shape());

            array.data().getInt(3);
        }
    }
}
 

@Test
public void testCircularWorkspaceAsymmetry_2() {
    // circular workspace mode
    val configuration = WorkspaceConfiguration.builder().initialSize(10 * 1024 * 1024)
            .policyReset(ResetPolicy.ENDOFBUFFER_REACHED).policyAllocation(AllocationPolicy.STRICT)
            .policySpill(SpillPolicy.FAIL).policyLearning(LearningPolicy.NONE).build();

    val root = Nd4j.create(DataType.FLOAT, 1000000).assign(119);

    for (int e = 0; e < 100; e++) {
        try (val ws = (CudaWorkspace) Nd4j.getWorkspaceManager().getAndActivateWorkspace(configuration, "circular_ws")) {
            val array = Nd4j.create(DataType.FLOAT, root.shape());
            array.assign(root);

            array.data().getInt(3);

            assertEquals(ws.getHostOffset(), ws.getDeviceOffset());
        }
    }
}
 

@Test
public void endlessTest6() throws Exception {
    Nd4j.getMemoryManager().togglePeriodicGc(false);
    WorkspaceConfiguration wsConf = WorkspaceConfiguration.builder().initialSize(10 * 1024L * 1024L)
                    .policyLearning(LearningPolicy.NONE).build();
    final AtomicLong cnt = new AtomicLong(0);
    while (true) {

        try (MemoryWorkspace ws = Nd4j.getWorkspaceManager().getAndActivateWorkspace(wsConf, "PEW-PEW")) {
            INDArray array = Nd4j.create(new float[] {1f, 2f, 3f, 4f, 5f});
        }

        if (cnt.incrementAndGet() % 1000000 == 0)
            log.info("TotalBytes: {}", Pointer.totalBytes());
    }
}
 

@Test
public void endlessTest5() throws Exception {
    while (true) {
        Thread thread = new Thread(new Runnable() {
            @Override
            public void run() {
                WorkspaceConfiguration wsConf = WorkspaceConfiguration.builder().initialSize(10 * 1024L * 1024L)
                                .policyLearning(LearningPolicy.NONE).build();

                try (MemoryWorkspace ws = Nd4j.getWorkspaceManager().getAndActivateWorkspace(wsConf, "PEW-PEW")) {
                    INDArray array = Nd4j.create(10);
                }
            }
        });

        thread.start();
        thread.join();

        System.gc();
    }
}
 

@Test
public void testReallocationWorkspace() {
    WorkspaceConfiguration initialConfig = WorkspaceConfiguration.builder().initialSize(10 * 1024L * 1024L)
                    .policyAllocation(AllocationPolicy.STRICT).policyLearning(LearningPolicy.NONE).build();
    MemoryWorkspace workspace = Nd4j.getWorkspaceManager().getAndActivateWorkspace(initialConfig, "SOME_ID");

    DataBuffer buffer = Nd4j.createBuffer(new double[] {1, 2, 3, 4});
    double[] old = buffer.asDouble();
    assertTrue(buffer.isAttached());
    assertEquals(4, buffer.capacity());
    buffer.reallocate(6);
    assertEquals(6, buffer.capacity());
    assertArrayEquals(old, buffer.asDouble(), 1e-1);
    workspace.close();

}
 

@Test
public void testReallocationWorkspace() {
    WorkspaceConfiguration initialConfig = WorkspaceConfiguration.builder().initialSize(10 * 1024L * 1024L)
                    .policyAllocation(AllocationPolicy.STRICT).policyLearning(LearningPolicy.NONE).build();
    MemoryWorkspace workspace = Nd4j.getWorkspaceManager().getAndActivateWorkspace(initialConfig, "SOME_ID");

    DataBuffer buffer = Nd4j.createBuffer(new float[] {1, 2, 3, 4});
    assertTrue(buffer.isAttached());
    float[] old = buffer.asFloat();
    assertEquals(4, buffer.capacity());
    buffer.reallocate(6);
    assertEquals(6, buffer.capacity());
    float[] newBuf = buffer.asFloat();
    assertArrayEquals(old, newBuf, 1e-4F);
    workspace.close();
}
 

@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);
        }
    }
}
 

/**
 * Detect faces and related points.
 * @param image3HW input image with dimensions [C x H x W] (e.g. channels first)
 * @return Two INDArray elements representing the Total Boxes found and the related points.
 * @throws IOException
 */
public INDArray[] rawFaceDetection(INDArray image3HW) throws IOException {

	WorkspaceConfiguration initialConfig = WorkspaceConfiguration.builder()
			.initialSize(10 * 1024L * 1024L)
			.policyAllocation(AllocationPolicy.STRICT)
			.policyLearning(LearningPolicy.NONE)
			.build();

	try (MemoryWorkspace ws = Nd4j.getWorkspaceManager().getAndActivateWorkspace(initialConfig, "SOME_ID")) {

		Assert.isTrue(image3HW.rank() == 3, "The input image is expected to have [0, Channels, Width, Height] dimensions");
		Assert.isTrue(image3HW.shape()[0] == 3, "The input image is expected to have channel count at dimension 0");

		// Compute the scale pyramid
		int height = (int) image3HW.size(1);
		int width = (int) image3HW.size(2);

		List<Double> scales = MtcnnUtil.computeScalePyramid(height, width, this.minFaceSize, this.scaleFactor);

		// Stage One
		Object[] stageOneResult = this.preparationStage(image3HW, scales);

		// Reorder image dimensions from [3,H,W] to [H,W,3]
		image3HW = image3HW.permute(1, 2, 0);

		// Stage Two
		INDArray totalBoxes = this.refinementStage(image3HW, (INDArray) stageOneResult[0], (MtcnnUtil.PadResult) stageOneResult[1]);

		// Stage Three
		INDArray[] stageThreeResult = this.outputStage(image3HW, totalBoxes);

		return stageThreeResult;
	}
}
 

protected static WorkspaceConfiguration getLayerActivationWSConfig(int numLayers){
    //Activations memory: opened once per layer - for every second layer (preprocessors are within the loop).
    //Technically we could set learning to numLayers / 2, but will set to numLayers for simplicity, and also to
    // account for a backward pass
    return WorkspaceConfiguration.builder()
            .initialSize(0)
            .overallocationLimit(0.02)
            .policyLearning(LearningPolicy.OVER_TIME)
            .cyclesBeforeInitialization(numLayers)
            .policyReset(ResetPolicy.BLOCK_LEFT)
            .policySpill(SpillPolicy.REALLOCATE)
            .policyAllocation(AllocationPolicy.OVERALLOCATE)
            .build();
}
 

protected static WorkspaceConfiguration getLayerWorkingMemWSConfig(int numWorkingMemCycles){
    return WorkspaceConfiguration.builder()
            .initialSize(0)
            .overallocationLimit(0.02)
            .policyLearning(LearningPolicy.OVER_TIME)
            .cyclesBeforeInitialization(numWorkingMemCycles)
            .policyReset(ResetPolicy.BLOCK_LEFT)
            .policySpill(SpillPolicy.REALLOCATE)
            .policyAllocation(AllocationPolicy.OVERALLOCATE)
            .build();
}
 

@Test
    public void testYoloStyle(){
        WorkspaceConfiguration WS_ALL_LAYERS_ACT_CONFIG = WorkspaceConfiguration.builder()
                .initialSize(0)
                .overallocationLimit(0.05)
                .policyLearning(LearningPolicy.FIRST_LOOP)
                .policyReset(ResetPolicy.BLOCK_LEFT)
                .policySpill(SpillPolicy.REALLOCATE)
                .policyAllocation(AllocationPolicy.OVERALLOCATE)
                .build();



        for( int i=0; i<10; i++ ){
            try(val ws = Nd4j.getWorkspaceManager().getAndActivateWorkspace(WS_ALL_LAYERS_ACT_CONFIG, "ws")){
//                System.out.println("STARTING: " + i);

                INDArray objectPresentMask = Nd4j.create(DataType.BOOL, 1,4,4);

                long[] shape = {1,3,2,4,4};
                INDArray noIntMask1 = Nd4j.createUninitialized(DataType.BOOL, shape, 'c');
                INDArray noIntMask2 = Nd4j.createUninitialized(DataType.BOOL, shape, 'c');

                noIntMask1 = Transforms.or(noIntMask1.get(all(), all(), point(0), all(), all()), noIntMask1.get(all(), all(), point(1), all(), all()) );    //Shape: [mb, b, H, W]. Values 1 if no intersection
                noIntMask2 = Transforms.or(noIntMask2.get(all(), all(), point(0), all(), all()), noIntMask2.get(all(), all(), point(1), all(), all()) );
                INDArray noIntMask = Transforms.or(noIntMask1, noIntMask2 );

                Nd4j.getExecutioner().commit();

                INDArray intMask = Transforms.not(noIntMask); //Values 0 if no intersection
                Nd4j.getExecutioner().commit();

                Broadcast.mul(intMask, objectPresentMask, intMask, 0, 2, 3);
                Nd4j.getExecutioner().commit();
//                System.out.println("DONE: " + i);
            }
        }
    }
 

@Test
public void testReallocationWorkspace() {
    WorkspaceConfiguration initialConfig = WorkspaceConfiguration.builder().initialSize(10 * 1024L * 1024L)
                    .policyAllocation(AllocationPolicy.STRICT).policyLearning(LearningPolicy.NONE).build();
    MemoryWorkspace workspace = Nd4j.getWorkspaceManager().getAndActivateWorkspace(initialConfig, "SOME_ID");

    DataBuffer buffer = Nd4j.createBuffer(new int[] {1, 2, 3, 4});
    int[] old = buffer.asInt();
    assertTrue(buffer.isAttached());
    assertEquals(4, buffer.capacity());
    buffer.reallocate(6);
    assertEquals(6, buffer.capacity());
    assertArrayEquals(old, buffer.asInt());
    workspace.close();
}
 

@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);
        }
    }
}
 

@Test
public void testViewDetach_1() throws Exception {
    WorkspaceConfiguration configuration = WorkspaceConfiguration.builder().initialSize(10000000).overallocationLimit(3.0)
            .policyAllocation(AllocationPolicy.OVERALLOCATE).policySpill(SpillPolicy.REALLOCATE)
            .policyLearning(LearningPolicy.FIRST_LOOP).policyReset(ResetPolicy.BLOCK_LEFT).build();

    Nd4jWorkspace workspace =
            (Nd4jWorkspace) Nd4j.getWorkspaceManager().getWorkspaceForCurrentThread(configuration, "WS109");

    INDArray row = Nd4j.linspace(1, 10, 10);
    INDArray exp = Nd4j.create(1, 10).assign(2.0);
    INDArray result = null;
    try (MemoryWorkspace ws = Nd4j.getWorkspaceManager().getAndActivateWorkspace(configuration, "WS109")) {
        INDArray matrix = Nd4j.create(10, 10);
        for (int e = 0; e < matrix.rows(); e++)
            matrix.getRow(e).assign(row);


        INDArray column = matrix.getColumn(1);
        assertTrue(column.isView());
        assertTrue(column.isAttached());
        result = column.detach();
    }

    assertFalse(result.isView());
    assertFalse(result.isAttached());
    assertEquals(exp, result);
}
 

@Test
public void testWorkspaceAccounting_2() {
    val deviceId = Nd4j.getAffinityManager().getDeviceForCurrentThread();
    val wsConf = WorkspaceConfiguration.builder()
            .initialSize(0)
            .policyAllocation(AllocationPolicy.STRICT)
            .policyLearning(LearningPolicy.OVER_TIME)
            .cyclesBeforeInitialization(3)
            .build();

    val before = Nd4j.getMemoryManager().allocatedMemory(deviceId);

    long middle1 = 0;
    try (val workspace = Nd4j.getWorkspaceManager().getAndActivateWorkspace(wsConf, "random_name_here")) {
        val array = Nd4j.create(DataType.DOUBLE, 5, 5);
        middle1 = Nd4j.getMemoryManager().allocatedMemory(deviceId);
    }

    val middle2 = Nd4j.getMemoryManager().allocatedMemory(deviceId);

    Nd4j.getWorkspaceManager().destroyAllWorkspacesForCurrentThread();

    val after = Nd4j.getMemoryManager().allocatedMemory(deviceId);

    log.info("Before: {}; Middle1: {}; Middle2: {}; After: {}", before, middle1, middle2, after);
    assertTrue(middle1 > before);
    assertTrue(after < middle1);
}
 

@Test
public void testCircularWorkspaceAsymmetry_1() {
    // circular workspace mode
    val configuration = WorkspaceConfiguration.builder().initialSize(10 * 1024 * 1024)
            .policyReset(ResetPolicy.ENDOFBUFFER_REACHED).policyAllocation(AllocationPolicy.STRICT)
            .policySpill(SpillPolicy.FAIL).policyLearning(LearningPolicy.NONE).build();


    try (val ws = (CudaWorkspace) Nd4j.getWorkspaceManager().getAndActivateWorkspace(configuration, "circular_ws")) {
        val array = Nd4j.create(DataType.FLOAT, 10, 10);

        assertEquals(0, ws.getHostOffset());
        assertNotEquals(0, ws.getDeviceOffset());

        // we expect that this array has no data/buffer on HOST side
        assertEquals(AffinityManager.Location.DEVICE, Nd4j.getAffinityManager().getActiveLocation(array));

        // since this array doesn't have HOST buffer - it will allocate one now
        array.getDouble(3L);

        assertEquals(ws.getHostOffset(), ws.getDeviceOffset());
    }

    try (val ws = (CudaWorkspace) Nd4j.getWorkspaceManager().getAndActivateWorkspace(configuration, "circular_ws")) {
        assertEquals(ws.getHostOffset(), ws.getDeviceOffset());
    }

    Nd4j.getWorkspaceManager().destroyAllWorkspacesForCurrentThread();
}
 

@Test
public void testVariableTimeSeries2() throws Exception {
    WorkspaceConfiguration configuration = WorkspaceConfiguration.builder().initialSize(0).overallocationLimit(3.0)
                    .policyAllocation(AllocationPolicy.OVERALLOCATE).policySpill(SpillPolicy.REALLOCATE)
                    .policyLearning(LearningPolicy.FIRST_LOOP).policyReset(ResetPolicy.ENDOFBUFFER_REACHED).build();

    Nd4jWorkspace workspace =
                    (Nd4jWorkspace) Nd4j.getWorkspaceManager().getWorkspaceForCurrentThread(configuration, "WS1");
    workspace.enableDebug(true);

    try (MemoryWorkspace ws = Nd4j.getWorkspaceManager().getAndActivateWorkspace(configuration, "WS1")) {
        Nd4j.create(500);
        Nd4j.create(500);
    }



    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());


    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(workspace.getInitialBlockSize() * 4, workspace.getCurrentSize());

    assertEquals(0, workspace.getNumberOfPinnedAllocations());
    assertEquals(0, workspace.getNumberOfExternalAllocations());

    assertEquals(0, workspace.getSpilledSize());
    assertEquals(0, workspace.getPinnedSize());

}
 

@Test
    public void testCreateTypedBuffer() {

        WorkspaceConfiguration initialConfig = WorkspaceConfiguration.builder().initialSize(10 * 1024L * 1024L)
                .policyAllocation(AllocationPolicy.STRICT).policyLearning(LearningPolicy.NONE).build();
        MemoryWorkspace workspace = Nd4j.getWorkspaceManager().createNewWorkspace(initialConfig, "WorkspaceId");

        for (String sourceType : new String[]{"int", "long", "float", "double", "short", "byte", "boolean"}) {
            for (DataType dt : DataType.values()) {
                if (dt == DataType.UTF8 || dt == DataType.COMPRESSED || dt == DataType.UNKNOWN) {
                    continue;
                }

//                log.info("Testing source [{}]; target: [{}]", sourceType, dt);

                for (boolean useWs : new boolean[]{false, true}) {

                    try (MemoryWorkspace ws = (useWs ? workspace.notifyScopeEntered() : null)) {

                        DataBuffer db1;
                        DataBuffer db2;
                        switch (sourceType) {
                            case "int":
                                db1 = Nd4j.createTypedBuffer(new int[]{1, 2, 3}, dt);
                                db2 = Nd4j.createTypedBufferDetached(new int[]{1, 2, 3}, dt);
                                break;
                            case "long":
                                db1 = Nd4j.createTypedBuffer(new long[]{1, 2, 3}, dt);
                                db2 = Nd4j.createTypedBufferDetached(new long[]{1, 2, 3}, dt);
                                break;
                            case "float":
                                db1 = Nd4j.createTypedBuffer(new float[]{1, 2, 3}, dt);
                                db2 = Nd4j.createTypedBufferDetached(new float[]{1, 2, 3}, dt);
                                break;
                            case "double":
                                db1 = Nd4j.createTypedBuffer(new double[]{1, 2, 3}, dt);
                                db2 = Nd4j.createTypedBufferDetached(new double[]{1, 2, 3}, dt);
                                break;
                            case "short":
                                db1 = Nd4j.createTypedBuffer(new short[]{1, 2, 3}, dt);
                                db2 = Nd4j.createTypedBufferDetached(new short[]{1, 2, 3}, dt);
                                break;
                            case "byte":
                                db1 = Nd4j.createTypedBuffer(new byte[]{1, 2, 3}, dt);
                                db2 = Nd4j.createTypedBufferDetached(new byte[]{1, 2, 3}, dt);
                                break;
                            case "boolean":
                                db1 = Nd4j.createTypedBuffer(new boolean[]{true, false, true}, dt);
                                db2 = Nd4j.createTypedBufferDetached(new boolean[]{true, false, true}, dt);
                                break;
                            default:
                                throw new RuntimeException();
                        }

                        checkTypes(dt, db1, 3);
                        checkTypes(dt, db2, 3);

                        assertEquals(useWs, db1.isAttached());
                        assertFalse(db2.isAttached());

                        if(!sourceType.equals("boolean")){
                            testDBOps(db1);
                            testDBOps(db2);
                        }
                    }
                }
            }
        }
    }
 

@Test
    @Ignore("AB 2019/06/03 - CI issue: \"CUDA stream synchronization failed\" - see issue 7657")
    public void testNoArgCreateBufferFromArray() {

        //Tests here:
        //1. Create from JVM array
        //2. Create from JVM array with offset -> does this even make sense?
        //3. Create detached buffer

        WorkspaceConfiguration initialConfig = WorkspaceConfiguration.builder().initialSize(10 * 1024L * 1024L)
                .policyAllocation(AllocationPolicy.STRICT).policyLearning(LearningPolicy.NONE).build();
        MemoryWorkspace workspace = Nd4j.getWorkspaceManager().createNewWorkspace(initialConfig, "WorkspaceId");

        for (boolean useWs : new boolean[]{false, true}) {

            try (MemoryWorkspace ws = (useWs ? workspace.notifyScopeEntered() : null)) {

                //Float
                DataBuffer f = Nd4j.createBuffer(new float[]{1, 2, 3});
                checkTypes(DataType.FLOAT, f, 3);
                assertEquals(useWs, f.isAttached());
                testDBOps(f);

                f = Nd4j.createBuffer(new float[]{1, 2, 3}, 0);
                checkTypes(DataType.FLOAT, f, 3);
                assertEquals(useWs, f.isAttached());
                testDBOps(f);

                f = Nd4j.createBufferDetached(new float[]{1, 2, 3});
                checkTypes(DataType.FLOAT, f, 3);
                assertFalse(f.isAttached());
                testDBOps(f);

                //Double
                DataBuffer d = Nd4j.createBuffer(new double[]{1, 2, 3});
                checkTypes(DataType.DOUBLE, d, 3);
                assertEquals(useWs, d.isAttached());
                testDBOps(d);

                d = Nd4j.createBuffer(new double[]{1, 2, 3}, 0);
                checkTypes(DataType.DOUBLE, d, 3);
                assertEquals(useWs, d.isAttached());
                testDBOps(d);

                d = Nd4j.createBufferDetached(new double[]{1, 2, 3});
                checkTypes(DataType.DOUBLE, d, 3);
                assertFalse(d.isAttached());
                testDBOps(d);

                //Int
                DataBuffer i = Nd4j.createBuffer(new int[]{1, 2, 3});
                checkTypes(DataType.INT, i, 3);
                assertEquals(useWs, i.isAttached());
                testDBOps(i);

                i = Nd4j.createBuffer(new int[]{1, 2, 3});
                checkTypes(DataType.INT, i, 3);
                assertEquals(useWs, i.isAttached());
                testDBOps(i);

                i = Nd4j.createBufferDetached(new int[]{1, 2, 3});
                checkTypes(DataType.INT, i, 3);
                assertFalse(i.isAttached());
                testDBOps(i);

                //Long
                DataBuffer l = Nd4j.createBuffer(new long[]{1, 2, 3});
                checkTypes(DataType.LONG, l, 3);
                assertEquals(useWs, l.isAttached());
                testDBOps(l);

                l = Nd4j.createBuffer(new long[]{1, 2, 3});
                checkTypes(DataType.LONG, l, 3);
                assertEquals(useWs, l.isAttached());
                testDBOps(l);

                l = Nd4j.createBufferDetached(new long[]{1, 2, 3});
                checkTypes(DataType.LONG, l, 3);
                assertFalse(l.isAttached());
                testDBOps(l);

                //byte
//                DataBuffer b = Nd4j.createBuffer(new byte[]{1, 2, 3});
//                checkTypes(DataType.BYTE, b, 3);
//                testDBOps(b);
//
//                b = Nd4j.createBuffer(new byte[]{1, 2, 3}, 0);
//                checkTypes(DataType.BYTE, b, 3);
//                testDBOps(b);
//
//                b = Nd4j.createBufferDetached(new byte[]{1,2,3});
//                checkTypes(DataType.BYTE, b, 3);
//                testDBOps(b);

                //short
                //TODO
            }
        }
    }
 

@Test
    public void testYoloS(){
        //Nd4j.getExecutioner().enableDebugMode(true);
        //Nd4j.getExecutioner().enableVerboseMode(true);
        //Nd4j.setDefaultDataTypes(DataType.DOUBLE, DataType.DOUBLE);

        WorkspaceConfiguration WS_ALL_LAYERS_ACT_CONFIG = WorkspaceConfiguration.builder()
                .initialSize(10 * 1024 * 1024)
                .overallocationLimit(0.05)
                .policyLearning(LearningPolicy.FIRST_LOOP)
                .policyReset(ResetPolicy.BLOCK_LEFT)
                .policySpill(SpillPolicy.REALLOCATE)
                .policyAllocation(AllocationPolicy.OVERALLOCATE)
                .build();


        INDArray labels = Nd4j.create(DataType.DOUBLE, 1,7,5,7);

        for( int i=0; i<10; i++ ){
            try(val ws = Nd4j.getWorkspaceManager().getAndActivateWorkspace(WS_ALL_LAYERS_ACT_CONFIG, "ws")){
//                System.out.println("STARTING: " + i);

                val nhw = new long[]{1, 5, 7};

                val size1 = labels.size(1);
                INDArray classLabels = labels.get(all(), interval(4,size1), all(), all());   //Shape: [minibatch, nClasses, H, W]
                INDArray maskObjectPresent = classLabels.sum(Nd4j.createUninitialized(DataType.DOUBLE, nhw, 'c'), 1).castTo(DataType.BOOL); //Shape: [minibatch, H, W]

                INDArray labelTLXY = labels.get(all(), interval(0,2), all(), all());
                INDArray labelBRXY = labels.get(all(), interval(2,4), all(), all());

                Nd4j.getExecutioner().commit();

                INDArray labelCenterXY = labelTLXY.add(labelBRXY);
                val m = labelCenterXY.muli(0.5);  //In terms of grid units
                INDArray labelsCenterXYInGridBox = labelCenterXY.dup(labelCenterXY.ordering());         //[mb, 2, H, W]
                Nd4j.getExecutioner().commit();
//                System.out.println("DONE: " + i);
            }
        }
    }
 

/**
 * 
 * 构建缓存
 * 
 * @param size
 */
void constructCache(int size) {
    array = new float[size];
    WorkspaceConfiguration configuration = WorkspaceConfiguration.builder().initialSize(size).policyAllocation(AllocationPolicy.STRICT).policyLearning(LearningPolicy.NONE).build();
    space = Nd4j.getWorkspaceManager().createNewWorkspace(configuration, "ND4J");
}