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

Example 1 with WorkspaceConfiguration

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

the class WorkspaceProviderTests method testUnboundedLoop2.

/**
 * This simple test checks for over-time learning with coefficient applied
 *
 * @throws Exception
 */
@Test
public void testUnboundedLoop2() throws Exception {
    WorkspaceConfiguration configuration = WorkspaceConfiguration.builder().initialSize(0).policyReset(ResetPolicy.ENDOFBUFFER_REACHED).policyAllocation(AllocationPolicy.OVERALLOCATE).overallocationLimit(4.0).policyLearning(LearningPolicy.OVER_TIME).cyclesBeforeInitialization(5).build();
    Nd4jWorkspace ws1 = (Nd4jWorkspace) Nd4j.getWorkspaceManager().getWorkspaceForCurrentThread(configuration, "ITER");
    long requiredMemory = 100 * Nd4j.sizeOfDataType();
    long shiftedSize = ((long) (requiredMemory * 1.3)) + (8 - (((long) (requiredMemory * 1.3)) % 8));
    for (int x = 0; x < 100; x++) {
        try (Nd4jWorkspace wsI = (Nd4jWorkspace) Nd4j.getWorkspaceManager().getWorkspaceForCurrentThread(configuration, "ITER").notifyScopeEntered()) {
            INDArray array = Nd4j.create(100);
        }
        // only checking after workspace is initialized
        if (x > 4) {
            assertEquals(shiftedSize, ws1.getInitialBlockSize());
            assertEquals(5 * shiftedSize, ws1.getCurrentSize());
        } else if (x < 4) {
            // we're making sure we're not initialize early
            assertEquals("Failed on iteration " + x, 0, ws1.getCurrentSize());
        }
    }
    // maximum allocation amount is 100 elements during learning, and additional coefficient is 4.0. result is workspace of 500 elements
    assertEquals(5 * shiftedSize, ws1.getCurrentSize());
    assertNull(Nd4j.getMemoryManager().getCurrentWorkspace());
}

Example 2 with WorkspaceConfiguration

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

the class WorkspaceProviderTests method testUnboundedLoop1.

@Test
public void testUnboundedLoop1() throws Exception {
    WorkspaceConfiguration configuration = WorkspaceConfiguration.builder().initialSize(100 * 100 * Nd4j.sizeOfDataType()).policyReset(ResetPolicy.ENDOFBUFFER_REACHED).policyAllocation(AllocationPolicy.STRICT).build();
    for (int x = 0; x < 100; x++) {
        try (Nd4jWorkspace ws1 = (Nd4jWorkspace) Nd4j.getWorkspaceManager().getWorkspaceForCurrentThread(configuration, "ITER").notifyScopeEntered()) {
            INDArray array = Nd4j.create(100);
        }
        Nd4jWorkspace ws1 = (Nd4jWorkspace) Nd4j.getWorkspaceManager().getWorkspaceForCurrentThread(configuration, "ITER");
        assertEquals((x + 1) * 100 * Nd4j.sizeOfDataType(), ws1.getHostOffset());
    }
    Nd4jWorkspace ws1 = (Nd4jWorkspace) Nd4j.getWorkspaceManager().getWorkspaceForCurrentThread(configuration, "ITER");
    assertEquals(100 * 100 * Nd4j.sizeOfDataType(), ws1.getHostOffset());
    // just to trigger reset
    ws1.notifyScopeEntered();
    // confirming reset
    // assertEquals(0, ws1.getHostOffset());
    ws1.notifyScopeLeft();
    assertNull(Nd4j.getMemoryManager().getCurrentWorkspace());
}

Example 3 with WorkspaceConfiguration

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

the class DoubleDataBufferTest method testReallocationWorkspace.

@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();
}

Example 4 with WorkspaceConfiguration

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

the class BasicWorkspaceTests method testAllocation4.

@Test
public void testAllocation4() throws Exception {
    WorkspaceConfiguration failConfig = WorkspaceConfiguration.builder().initialSize(1024 * 1024).maxSize(1024 * 1024).overallocationLimit(0.1).policyAllocation(AllocationPolicy.STRICT).policyLearning(LearningPolicy.FIRST_LOOP).policyMirroring(MirroringPolicy.FULL).policySpill(SpillPolicy.FAIL).build();
    Nd4jWorkspace workspace = (Nd4jWorkspace) Nd4j.getWorkspaceManager().createNewWorkspace(failConfig);
    Nd4j.getMemoryManager().setCurrentWorkspace(workspace);
    assertNotEquals(null, Nd4j.getMemoryManager().getCurrentWorkspace());
    assertEquals(0, workspace.getHostOffset());
    INDArray array = Nd4j.create(new int[] { 1, 5 }, 'c');
    // checking if allocation actually happened
    long reqMem = 5 * Nd4j.sizeOfDataType();
    assertEquals(reqMem + reqMem % 8, workspace.getHostOffset());
    try {
        INDArray array2 = Nd4j.create(10000000);
        assertTrue(false);
    } catch (ND4JIllegalStateException e) {
        assertTrue(true);
    }
    assertEquals(reqMem + reqMem % 8, workspace.getHostOffset());
    INDArray array2 = Nd4j.create(new int[] { 1, 5 }, 'c');
    assertEquals((reqMem + reqMem % 8) * 2, workspace.getHostOffset());
}

Example 5 with WorkspaceConfiguration

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

the class BasicWorkspaceTests method testMmap1.

@Test
public void testMmap1() throws Exception {
    // we don't support MMAP on cuda yet
    if (Nd4j.getExecutioner().getClass().getName().toLowerCase().contains("cuda"))
        return;
    WorkspaceConfiguration mmap = WorkspaceConfiguration.builder().initialSize(1000000).policyLocation(LocationPolicy.MMAP).build();
    MemoryWorkspace ws = Nd4j.getWorkspaceManager().getAndActivateWorkspace(mmap, "M2");
    INDArray mArray = Nd4j.create(100);
    mArray.assign(10f);
    assertEquals(1000f, mArray.sumNumber().floatValue(), 1e-5);
    ws.close();
    ws.notifyScopeEntered();
    INDArray mArrayR = Nd4j.createUninitialized(100);
    assertEquals(1000f, mArrayR.sumNumber().floatValue(), 1e-5);
    ws.close();
}