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

Example 51 with MemoryWorkspace

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

the class SpecialWorkspaceTests method testViewDetach_1.

@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);
}

Example 52 with MemoryWorkspace

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

the class SpecialWorkspaceTests method testVariableTimeSeries2.

@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());
}

Example 53 with MemoryWorkspace

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

the class OperationProfilerTests method testScopePanicPerf.

@Test
public void testScopePanicPerf() {
    try (MemoryWorkspace workspace = Nd4j.getWorkspaceManager().getAndActivateWorkspace("WS121")) {
        INDArray x = Nd4j.create(1000, 1000).assign(1.0);
        INDArray y = Nd4j.create(1000, 1000).assign(1.0);
        for (int e = 0; e < 10000; e++) {
            x.addi(y);
        }
        Nd4j.getExecutioner().setProfilingMode(OpExecutioner.ProfilingMode.SCOPE_PANIC);
        val nanosC = System.nanoTime();
        for (int e = 0; e < 10000; e++) {
            x.addi(y);
        }
        val nanosD = System.nanoTime();
        val avgB = (nanosD - nanosC) / 10000;
        Nd4j.getExecutioner().setProfilingMode(OpExecutioner.ProfilingMode.DISABLED);
        val nanosA = System.nanoTime();
        for (int e = 0; e < 10000; e++) {
            x.addi(y);
        }
        val nanosB = System.nanoTime();
        val avgA = (nanosB - nanosA) / 10000;
        log.info("A: {}; B: {}", avgA, avgB);
    }
}

Example 54 with MemoryWorkspace

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

the class OperationProfilerTests method testScopePanic2.

@Test(expected = ND4JIllegalStateException.class)
public void testScopePanic2() throws Exception {
    Nd4j.getExecutioner().setProfilingMode(OpExecutioner.ProfilingMode.SCOPE_PANIC);
    INDArray array;
    try (MemoryWorkspace workspace = Nd4j.getWorkspaceManager().getAndActivateWorkspace("WS120")) {
        array = Nd4j.create(10);
        assertTrue(array.isAttached());
        assertEquals(1, workspace.getGenerationId());
    }
    try (MemoryWorkspace workspace = Nd4j.getWorkspaceManager().getAndActivateWorkspace("WS120")) {
        assertEquals(2, workspace.getGenerationId());
        array.add(1.0);
        assertTrue(array.isAttached());
    }
}

Example 55 with MemoryWorkspace

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

the class WorkspaceProviderTests method testMemcpy1.

@Ignore
@Test
public void testMemcpy1() {
    INDArray warmUp = Nd4j.create(100000);
    for (int x = 0; x < 5000; x++) {
        warmUp.addi(0.1);
    }
    WorkspaceConfiguration configuration = WorkspaceConfiguration.builder().policyMirroring(MirroringPolicy.HOST_ONLY).initialSize(1024L * 1024L * 1024L).policyLearning(LearningPolicy.NONE).build();
    INDArray array = Nd4j.createUninitialized(150000000);
    MemoryWorkspace workspace = (Nd4jWorkspace) Nd4j.getWorkspaceManager().createNewWorkspace(configuration, "HOST");
    workspace.notifyScopeEntered();
    INDArray memcpy = array.unsafeDuplication(false);
    workspace.notifyScopeLeft();
}