Examples with Sum org.nd4j.linalg.api.ops.impl.accum.Sum used on opensource projects

Example 6 with Sum

use of org.nd4j.linalg.api.ops.impl.accum.Sum in project nd4j by deeplearning4j.

the class CudaAccumTests method testPinnedSum.

/**
 * Sum call
 * @throws Exception
 */
@Test
public void testPinnedSum() throws Exception {
    // simple way to stop test if we're not on CUDA backend here
    assertEquals("JcublasLevel1", Nd4j.getBlasWrapper().level1().getClass().getSimpleName());
    INDArray array1 = Nd4j.create(new float[] { 2.01f, 2.01f, 1.01f, 1.01f, 1.01f, 1.01f, 1.01f, 1.01f, 1.01f, 1.01f, 1.01f, 1.01f, 1.01f, 1.01f, 1.01f });
    Sum sum = new Sum(array1);
    Nd4j.getExecutioner().exec(sum, 1);
    Number resu = sum.getFinalResult();
    System.out.println("Result: " + resu);
    assertEquals(17.15f, resu.floatValue(), 0.01f);
}

Example 7 with Sum

use of org.nd4j.linalg.api.ops.impl.accum.Sum in project nd4j by deeplearning4j.

the class Nd4jTestsC method testScalarReduction1.

@Test
public void testScalarReduction1() {
    Accumulation op = new Norm2(Nd4j.create(1).assign(1.0));
    double norm2 = Nd4j.getExecutioner().execAndReturn(op).getFinalResult().doubleValue();
    double norm1 = Nd4j.getExecutioner().execAndReturn(new Norm1(Nd4j.create(1).assign(1.0))).getFinalResult().doubleValue();
    double sum = Nd4j.getExecutioner().execAndReturn(new Sum(Nd4j.create(1).assign(1.0))).getFinalResult().doubleValue();
    assertEquals(1.0, norm2, 0.001);
    assertEquals(1.0, norm1, 0.001);
    assertEquals(1.0, sum, 0.001);
}

Example 8 with Sum

use of org.nd4j.linalg.api.ops.impl.accum.Sum in project nd4j by deeplearning4j.

the class GridExecutionerTest method testOpPointerizeReduce1.

/**
 * Reduce along dimensions
 *
 * @throws Exception
 */
@Test
public void testOpPointerizeReduce1() throws Exception {
    CudaGridExecutioner executioner = new CudaGridExecutioner();
    INDArray array = Nd4j.create(10, 10);
    Sum opA = new Sum(array);
    // we need exec here, to init Op.Z for specific dimension
    executioner.exec(opA, 1);
    GridPointers pointers = executioner.pointerizeOp(opA, 1);
    assertEquals(opA.opNum(), pointers.getOpNum());
    assertEquals(Op.Type.REDUCE, pointers.getType());
    CudaContext context = (CudaContext) AtomicAllocator.getInstance().getDeviceContext().getContext();
    Pointer x = AtomicAllocator.getInstance().getPointer(array, context);
    Pointer xShapeInfo = AtomicAllocator.getInstance().getPointer(array.shapeInfoDataBuffer(), context);
    Pointer z = AtomicAllocator.getInstance().getPointer(opA.z(), context);
    Pointer zShapeInfo = AtomicAllocator.getInstance().getPointer(opA.z().shapeInfoDataBuffer(), context);
    DataBuffer dimBuff = Nd4j.getConstantHandler().getConstantBuffer(new int[] { 1 });
    Pointer ptrBuff = AtomicAllocator.getInstance().getPointer(dimBuff, context);
    assertEquals(x, pointers.getX());
    assertEquals(null, pointers.getY());
    assertNotEquals(null, pointers.getZ());
    assertEquals(z, pointers.getZ());
    assertEquals(10, opA.z().length());
    assertEquals(10, pointers.getZLength());
    /*      // We dont really care about EWS here, since we're testing TAD-based operation

        assertEquals(1, pointers.getXStride());
        assertEquals(-1, pointers.getYStride());
        assertEquals(1, pointers.getZStride());
*/
    assertEquals(xShapeInfo, pointers.getXShapeInfo());
    assertEquals(null, pointers.getYShapeInfo());
    assertEquals(zShapeInfo, pointers.getZShapeInfo());
    assertEquals(ptrBuff, pointers.getDimensions());
    assertEquals(1, pointers.getDimensionsLength());
    assertNotEquals(null, pointers.getTadShape());
    assertNotEquals(null, pointers.getTadOffsets());
    assertEquals(null, pointers.getExtraArgs());
}

Example 9 with Sum

use of org.nd4j.linalg.api.ops.impl.accum.Sum in project nd4j by deeplearning4j.

the class MetaOpTests method testPredicateReduce2.

/**
 * Predicate test for scalar + reduceScalar
 *
 * @throws Exception
 */
@Ignore
@Test
public void testPredicateReduce2() throws Exception {
    CudaGridExecutioner executioner = new CudaGridExecutioner();
    INDArray arrayX = Nd4j.create(5, 5);
    ScalarAdd opA = new ScalarAdd(arrayX, 1.0f);
    Sum opB = new Sum(arrayX);
    PredicateMetaOp metaOp = new PredicateMetaOp(opA, opB);
    executioner.exec(metaOp);
    INDArray result = opB.z();
    assertNotEquals(null, result);
    assertTrue(result.isScalar());
    assertEquals(25f, result.getFloat(0), 0.1f);
}