Java Code Examples for org.nd4j.linalg.api.shape.Shape#assertBroadcastable()

The following examples show how to use org.nd4j.linalg.api.shape.Shape#assertBroadcastable() . 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: BaseDynamicTransformOp.java    From nd4j with Apache License 2.0 5 votes vote down vote up 
@Override
public List<long[]> calculateOutputShape() {
    val args = args();
    if(args.length < 2) {
        if(args[0] == null || args[0].getShape() == null) {
            return Collections.emptyList();
        }

        return Arrays.asList(args[0].getShape());
    }

    val firstArgShape = args[0].getShape();
    val secondArgShape = args[1].getShape();
    if(args[0] == null || args[0].getShape() == null) {
        return Collections.emptyList();
    }

    if(args[1] == null || args[1].getShape() == null) {
        return Collections.emptyList();
    }

    if(Arrays.equals(firstArgShape, secondArgShape)){
        return Collections.singletonList(firstArgShape);
    }
    //Handle broadcast shape: [1,4]+[3,1] = [3,4]
    Shape.assertBroadcastable(firstArgShape, secondArgShape);
    val outShape = Shape.broadcastOutputShape(firstArgShape, secondArgShape);

    return Collections.singletonList(outShape);
}
Example 2
Source File: BaseNDArray.java    From deeplearning4j with Apache License 2.0 5 votes vote down vote up 
@Override
public INDArray divi(INDArray other, INDArray result) {
    validateNumericalArray("divi", false);
    Shape.assertBroadcastable("divi", this, other, result);
    Nd4j.exec(new DivOp(this, other, result));
    return result;
}
Example 3
Source File: BaseNDArray.java    From deeplearning4j with Apache License 2.0 5 votes vote down vote up 
@Override
public INDArray muli(INDArray other, INDArray result) {
    validateNumericalArray("muli", false);
    Shape.assertBroadcastable("muli", this, other, result);
    Nd4j.exec(new MulOp(this, other, result));
    return result;
}
Example 4
Source File: BaseNDArray.java    From deeplearning4j with Apache License 2.0 5 votes vote down vote up 
/**
 * in place subtraction of two matrices
 *
 * @param other  the second ndarray to subtract
 * @param result the result ndarray
 * @return the result of the subtraction
 */
@Override
public INDArray subi(INDArray other, INDArray result) {
    validateNumericalArray("subi", false);
    Shape.assertBroadcastable("subi", this, other, result);
    Nd4j.exec(new SubOp(this, other, result));
    return result;
}
Example 5
Source File: BaseNDArray.java    From deeplearning4j with Apache License 2.0 5 votes vote down vote up 
@Override
public INDArray addi(INDArray other, INDArray result) {
    validateNumericalArray("addi", false);
    Shape.assertBroadcastable("addi", this, other, result);
    Nd4j.exec(new AddOp(this, other, result));
    return result;
}
Example 6
Source File: BaseNDArray.java    From deeplearning4j with Apache License 2.0 5 votes vote down vote up 
@Override
public INDArray rdivi(INDArray other, INDArray result) {
    validateNumericalArray("rdivi", false);
    Shape.assertBroadcastable("rdivi", this, other, result);
    Nd4j.exec(new RDivOp(this, other, result));
    return result;
}
Example 7
Source File: BaseNDArray.java    From deeplearning4j with Apache License 2.0 5 votes vote down vote up 
@Override
public INDArray rsubi(INDArray other, INDArray result) {
    validateNumericalArray("rsubi", false);
    Shape.assertBroadcastable("rsubi", this, other, result);
    Nd4j.exec(new RSubOp(this, other, result));
    return result;
}