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

Example 1 with Sum

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

the class HalfOpsTests method testReduce1.

@Test
public void testReduce1() throws Exception {
    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 2 with Sum

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

the class GridExecutionerTest method testGridFlow4.

@Test
public void testGridFlow4() throws Exception {
    CudaGridExecutioner executioner = new CudaGridExecutioner();
    INDArray arrayX = Nd4j.create(new float[] { 1f, 1f, 1f, 1f, 1f });
    Sum op = new Sum(arrayX);
    executioner.exec(op);
    assertEquals(0, executioner.getQueueLength());
    assertNotEquals(null, op.getFinalResult());
    assertEquals(5, op.getFinalResult().intValue());
}

Example 3 with Sum

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

the class GridExecutionerTest method testGridFlow5.

@Test
public void testGridFlow5() throws Exception {
    CudaGridExecutioner executioner = new CudaGridExecutioner();
    INDArray arrayX = Nd4j.create(5, 5);
    Sum op = new Sum(arrayX);
    executioner.exec(op, 1);
    assertEquals(0, executioner.getQueueLength());
    assertEquals(0, op.z().getFloat(0), 0.1f);
}

Example 4 with Sum

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

the class GridExecutionerTest method testOpPointerizeReduce2.

/**
 * Reduce along all dimensions
 *
 * @throws Exception
 */
@Test
public void testOpPointerizeReduce2() 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);
    GridPointers pointers = executioner.pointerizeOp(opA, null);
    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(1, opA.z().length());
    assertEquals(1, 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(null, pointers.getDimensions());
    assertEquals(0, pointers.getDimensionsLength());
    assertEquals(null, pointers.getTadShape());
    assertEquals(null, pointers.getTadOffsets());
    assertEquals(null, pointers.getExtraArgs());
}

Example 5 with Sum

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

the class CudaAccumTests method testPinnedSum2.

@Test
public void testPinnedSum2() throws Exception {
    // simple way to stop test if we're not on CUDA backend here
    INDArray array1 = Nd4j.linspace(1, 10000, 100000).reshape(100, 1000);
    Sum sum = new Sum(array1);
    INDArray result;
    /* = Nd4j.getExecutioner().exec(sum, 0);

        assertEquals(495055.44f, result.getFloat(0), 0.01f);
*/
    result = Nd4j.getExecutioner().exec(sum, 1);
    result = Nd4j.getExecutioner().exec(sum, 1);
    assertEquals(50945.52f, result.getFloat(0), 0.01f);
}