Java Code Examples for org.nd4j.linalg.api.ndarray.INDArray#addiColumnVector()

The following examples show how to use org.nd4j.linalg.api.ndarray.INDArray#addiColumnVector() . You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.
Example 1
Source File: SporadicTests.java    From nd4j with Apache License 2.0 6 votes vote down vote up 
@Test
public void testBroadcastEquality2() {
    INDArray array = Nd4j.zeros(new int[]{4, 5}, 'c');
    INDArray array2 = Nd4j.zeros(new int[]{4, 5}, 'c');
    INDArray column = Nd4j.create(new float[]{1, 2, 3, 4}).reshape(4,1);

    array.addiColumnVector(column);

    System.out.println(array);

    System.out.println("-------");

    ScalarAdd add = new ScalarAdd(array2, column, array2, array2.length(), 0.0f);
    add.setDimension(1);
    Nd4j.getExecutioner().exec(add);

    System.out.println(array2);
    assertEquals(array, array2);

}
Example 2
Source File: NativeOpExecutionerTest.java    From nd4j with Apache License 2.0 6 votes vote down vote up 
@Test
public void testBroadcastEquality2() {
    INDArray array = Nd4j.zeros(new int[]{4, 5}, 'c');
    INDArray array2 = Nd4j.zeros(new int[]{4, 5}, 'c');
    INDArray column = Nd4j.create(new float[]{1, 2, 3, 4}).reshape(4,1);

    array.addiColumnVector(column);

    System.out.println(array);

    System.out.println("-------");

    ScalarAdd add = new ScalarAdd(array2, column, array2, array2.length(), 0.0f);
    add.setDimension(1);
    Nd4j.getExecutioner().exec(add);

    System.out.println(array2);
    assertEquals(array, array2);

}
Example 3
Source File: Nd4jMatrix.java    From jstarcraft-ai with Apache License 2.0 5 votes vote down vote up 
@Override
public MathMatrix addColumnVector(MathVector vector) {
    if (vector instanceof Nd4jVector) {
        Nd4jEnvironmentThread thread = EnvironmentThread.getThread(Nd4jEnvironmentThread.class);
        try (MemoryWorkspace workspace = thread.getSpace()) {
            INDArray thisArray = this.getArray();
            INDArray thatArray = Nd4jVector.class.cast(vector).getArray();
            thisArray.addiColumnVector(thatArray);
            return this;
        }
    } else {
        return MathMatrix.super.addColumnVector(vector);
    }
}
Example 4
Source File: NDArrayTestsFortran.java    From nd4j with Apache License 2.0 5 votes vote down vote up 
@Test
public void testColumnVectorOpsFortran() {
    INDArray twoByTwo = Nd4j.create(new float[] {1, 2, 3, 4}, new long[] {2, 2});
    INDArray toAdd = Nd4j.create(new float[] {1, 2}, new long[] {2, 1});
    twoByTwo.addiColumnVector(toAdd);
    INDArray assertion = Nd4j.create(new float[] {2, 4, 4, 6}, new long[] {2, 2});
    assertEquals(assertion, twoByTwo);
}
Example 5
Source File: NDArrayTestsFortran.java    From deeplearning4j with Apache License 2.0 5 votes vote down vote up 
@Test
public void testColumnVectorOpsFortran() {
    INDArray twoByTwo = Nd4j.create(new float[] {1, 2, 3, 4}, new long[] {2, 2});
    INDArray toAdd = Nd4j.create(new float[] {1, 2}, new long[] {2, 1});
    twoByTwo.addiColumnVector(toAdd);
    INDArray assertion = Nd4j.create(new float[] {2, 4, 4, 6}, new long[] {2, 2});
    assertEquals(assertion, twoByTwo);
}
Example 6
Source File: CrashTest.java    From nd4j with Apache License 2.0 2 votes vote down vote up 
protected void op(INDArray x, INDArray y, int i) {
    // broadcast along row & column
    INDArray row = Nd4j.ones(64);
    INDArray column = Nd4j.ones(1024, 1);

    x.addiRowVector(row);
    x.addiColumnVector(column);

    // casual scalar
    x.addi(i * 2);

    // reduction along all dimensions
    float sum = x.sumNumber().floatValue();

    // index reduction
    Nd4j.getExecutioner().exec(new IMax(x), Integer.MAX_VALUE);

    // casual transform
    Nd4j.getExecutioner().exec(new Sqrt(x, x));

    //  dup
    INDArray x1 = x.dup(x.ordering());
    INDArray x2 = x.dup(x.ordering());
    INDArray x3 = x.dup('c');
    INDArray x4 = x.dup('f');


    // vstack && hstack
    INDArray vstack = Nd4j.vstack(x, x1, x2, x3, x4);

    INDArray hstack = Nd4j.hstack(x, x1, x2, x3, x4);

    // reduce3 call
    Nd4j.getExecutioner().exec(new ManhattanDistance(x, x2));


    // flatten call
    INDArray flat = Nd4j.toFlattened(x, x1, x2, x3, x4);


    // reduction along dimension: row & column
    INDArray max_0 = x.max(0);
    INDArray max_1 = x.max(1);


    // index reduction along dimension: row & column
    INDArray imax_0 = Nd4j.argMax(x, 0);
    INDArray imax_1 = Nd4j.argMax(x, 1);


    // logisoftmax, softmax & softmax derivative
    Nd4j.getExecutioner().exec(new OldSoftMax(x));
    Nd4j.getExecutioner().exec(new SoftMaxDerivative(x));
    Nd4j.getExecutioner().exec(new LogSoftMax(x));


    // BooleanIndexing
    BooleanIndexing.replaceWhere(x, 5f, Conditions.lessThan(8f));

    // assing on view
    BooleanIndexing.assignIf(x, x1, Conditions.greaterThan(-1000000000f));

    // std var along all dimensions
    float std = x.stdNumber().floatValue();

    // std var along row & col
    INDArray xStd_0 = x.std(0);
    INDArray xStd_1 = x.std(1);

    // blas call
    float dot = (float) Nd4j.getBlasWrapper().dot(x, x1);

    // mmul
    for (boolean tA : paramsA) {
        for (boolean tB : paramsB) {

            INDArray xT = tA ? x.dup() : x.dup().transpose();
            INDArray yT = tB ? y.dup() : y.dup().transpose();

            Nd4j.gemm(xT, yT, tA, tB);
        }
    }

    // specially for views, checking here without dup and rollover
    Nd4j.gemm(x, y, false, false);

    log.debug("Iteration passed: " + i);
}
Example 7
Source File: CrashTest.java    From deeplearning4j with Apache License 2.0 2 votes vote down vote up 
protected void op(INDArray x, INDArray y, int i) {
    // broadcast along row & column
    INDArray row = Nd4j.ones(64);
    INDArray column = Nd4j.ones(1024, 1);

    x.addiRowVector(row);
    x.addiColumnVector(column);

    // casual scalar
    x.addi(i * 2);

    // reduction along all dimensions
    float sum = x.sumNumber().floatValue();

    // index reduction
    Nd4j.getExecutioner().exec(new ArgMax(x));

    // casual transform
    Nd4j.getExecutioner().exec(new Sqrt(x, x));

    //  dup
    INDArray x1 = x.dup(x.ordering());
    INDArray x2 = x.dup(x.ordering());
    INDArray x3 = x.dup('c');
    INDArray x4 = x.dup('f');


    // vstack && hstack
    INDArray vstack = Nd4j.vstack(x, x1, x2, x3, x4);

    INDArray hstack = Nd4j.hstack(x, x1, x2, x3, x4);

    // reduce3 call
    Nd4j.getExecutioner().exec(new ManhattanDistance(x, x2));


    // flatten call
    INDArray flat = Nd4j.toFlattened(x, x1, x2, x3, x4);


    // reduction along dimension: row & column
    INDArray max_0 = x.max(0);
    INDArray max_1 = x.max(1);


    // index reduction along dimension: row & column
    INDArray imax_0 = Nd4j.argMax(x, 0);
    INDArray imax_1 = Nd4j.argMax(x, 1);


    // logisoftmax, softmax & softmax derivative
    Nd4j.getExecutioner().exec((CustomOp) new SoftMax(x));
    Nd4j.getExecutioner().exec((CustomOp) new LogSoftMax(x));


    // BooleanIndexing
    BooleanIndexing.replaceWhere(x, 5f, Conditions.lessThan(8f));

    // assing on view
    BooleanIndexing.assignIf(x, x1, Conditions.greaterThan(-1000000000f));

    // std var along all dimensions
    float std = x.stdNumber().floatValue();

    // std var along row & col
    INDArray xStd_0 = x.std(0);
    INDArray xStd_1 = x.std(1);

    // blas call
    float dot = (float) Nd4j.getBlasWrapper().dot(x, x1);

    // mmul
    for (boolean tA : paramsA) {
        for (boolean tB : paramsB) {

            INDArray xT = tA ? x.dup() : x.dup().transpose();
            INDArray yT = tB ? y.dup() : y.dup().transpose();

            Nd4j.gemm(xT, yT, tA, tB);
        }
    }

    // specially for views, checking here without dup and rollover
    Nd4j.gemm(x, y, false, false);

    log.debug("Iteration passed: " + i);
}