Java Code Examples for org.nd4j.linalg.api.shape.Shape#areShapesBroadcastable()
The following examples show how to use
org.nd4j.linalg.api.shape.Shape#areShapesBroadcastable() .
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Example 1
Source File: BaseNDArray.java From deeplearning4j with Apache License 2.0 | 6 votes |
@Override public INDArray fmod(INDArray denominator, INDArray result) { validateNumericalArray("fmod", false); if (Shape.areShapesBroadcastable(this.shape(), denominator.shape())) { val outShape = Shape.broadcastOutputShape(this.shape(), denominator.shape()); Preconditions.checkArgument(Shape.shapeEquals(outShape, result.shape()), "Result shape doesn't match expectations: " + Arrays.toString(result.shape())); Nd4j.exec(new FloorModOp(new INDArray[]{this, denominator}, new INDArray[]{result})); return result; } else { FModOp op = new FModOp(this, denominator, result); Nd4j.getExecutioner().exec(op); return result; } }
Example 2
Source File: BaseNDArray.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Override public INDArray lt(INDArray other) { validateNumericalArray("less than (lt)", false); if (Shape.shapeEquals(this.shape(), other.shape())) { return Nd4j.getExecutioner().exec(new LessThan(this, other, Nd4j.createUninitialized(DataType.BOOL, this.shape(), this.ordering())))[0]; } else if (Shape.areShapesBroadcastable(this.shape(), other.shape())) { return Nd4j.exec(new LessThan(new INDArray[]{this, other}, new INDArray[]{Nd4j.createUninitialized(DataType.BOOL, Shape.broadcastOutputShape(this.shape(), other.shape()))}))[0]; } else throw new IllegalArgumentException("Shapes must be broadcastable"); }
Example 3
Source File: BaseNDArray.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Override public INDArray eq(INDArray other) { if (Shape.shapeEquals(this.shape(), other.shape())) { return Nd4j.getExecutioner().exec(new EqualTo(this, other, Nd4j.createUninitialized(DataType.BOOL, this.shape(), this.ordering())))[0]; } else if (Shape.areShapesBroadcastable(this.shape(), other.shape())) { return Nd4j.exec(new EqualTo(new INDArray[]{this, other}, new INDArray[]{Nd4j.createUninitialized(DataType.BOOL, Shape.broadcastOutputShape(this.shape(), other.shape()))}))[0]; } else throw new IllegalArgumentException("Shapes must be broadcastable"); }
Example 4
Source File: BaseNDArray.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Override public INDArray gt(INDArray other) { validateNumericalArray("greater than (gt)", false); if (Shape.shapeEquals(this.shape(), other.shape())) { return Nd4j.getExecutioner().exec(new GreaterThan(this, other, Nd4j.createUninitialized(DataType.BOOL, this.shape(), this.ordering())))[0]; } else if (Shape.areShapesBroadcastable(this.shape(), other.shape())) { return Nd4j.exec(new GreaterThan(new INDArray[]{this, other}, new INDArray[]{Nd4j.createUninitialized(DataType.BOOL, Shape.broadcastOutputShape(this.shape(), other.shape()))}))[0]; } else throw new IllegalArgumentException("Shapes must be broadcastable"); }
Example 5
Source File: BaseNDArray.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Override public INDArray div(INDArray other) { if (Shape.areShapesBroadcastable(this.shape(), other.shape())) { return divi(other, Nd4j.createUninitialized(Shape.pickPairwiseDataType(this.dataType(), other.dataType()), Shape.broadcastOutputShape(this.shape(), other.shape()), this.ordering())); } else { return divi(other, Nd4j.createUninitialized(Shape.pickPairwiseDataType(this.dataType(), other.dataType()), this.shape(), this.ordering())); } }
Example 6
Source File: BaseNDArray.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Override public INDArray mul(INDArray other) { validateNumericalArray("mul", false); if (Shape.areShapesBroadcastable(this.shape(), other.shape())) { return muli(other, Nd4j.createUninitialized(Shape.pickPairwiseDataType(this.dataType(), other.dataType()), Shape.broadcastOutputShape(this.shape(), other.shape()), this.ordering())); } else { val z = Nd4j.createUninitialized(Shape.pickPairwiseDataType(this.dataType(), other.dataType()), this.shape(), this.ordering()); return muli(other, z); } }
Example 7
Source File: BaseNDArray.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Override public INDArray sub(INDArray other) { validateNumericalArray("sub", false); if (Shape.areShapesBroadcastable(this.shape(), other.shape())) { return subi(other, Nd4j.createUninitialized(Shape.pickPairwiseDataType(this.dataType(), other.dataType()), Shape.broadcastOutputShape(this.shape(), other.shape()), this.ordering())); } else { return subi(other, Nd4j.createUninitialized(Shape.pickPairwiseDataType(this.dataType(), other.dataType()), this.shape(), this.ordering())); } }
Example 8
Source File: BaseNDArray.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Override public INDArray add(INDArray other) { validateNumericalArray("add", false); if (Shape.areShapesBroadcastable(this.shape(), other.shape())) { return addi(other, Nd4j.createUninitialized(Shape.pickPairwiseDataType(this.dataType(), other.dataType()), Shape.broadcastOutputShape(this.shape(), other.shape()), this.ordering())); } else { return addi(other, Nd4j.createUninitialized(Shape.pickPairwiseDataType(this.dataType(), other.dataType()), this.shape(), this.ordering())); } }
Example 9
Source File: BaseNDArray.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Override public INDArray rdiv(INDArray other) { validateNumericalArray("rdiv", false); if (Shape.areShapesBroadcastable(this.shape(), other.shape())) { return rdivi(other, Nd4j.createUninitialized(Shape.pickPairwiseDataType(this.dataType(), other.dataType()), Shape.broadcastOutputShape(this.shape(), other.shape()), this.ordering())); } else { return rdivi(other, this.ulike()); } }
Example 10
Source File: BaseNDArray.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Override public INDArray rsub(INDArray other) { validateNumericalArray("rsub", false); if (Shape.areShapesBroadcastable(this.shape(), other.shape())) { return rsubi(other, Nd4j.createUninitialized(Shape.pickPairwiseDataType(this.dataType(), other.dataType()), Shape.broadcastOutputShape(this.shape(), other.shape()), this.ordering())); } else { return rsubi(other, this.ulike()); } }
Example 11
Source File: BaseNDArray.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Override public INDArray remainder(INDArray denominator) { if (Shape.areShapesBroadcastable(this.shape(), denominator.shape())) { return remainder(denominator, Nd4j.createUninitialized(this.dataType(), Shape.broadcastOutputShape(this.shape(), denominator.shape()))); } else return remainder(denominator, this.ulike()); }
Example 12
Source File: BaseNDArray.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Override public INDArray fmod(INDArray denominator) { validateNumericalArray("fmod", false); if (Shape.areShapesBroadcastable(this.shape(), denominator.shape())) { return fmod(denominator, Nd4j.createUninitialized(Nd4j.defaultFloatingPointType(), Shape.broadcastOutputShape(this.shape(), denominator.shape()))); } else return fmod(denominator, this.ulike()); }
Example 13
Source File: Transforms.java From deeplearning4j with Apache License 2.0 | 5 votes |
protected static long[] broadcastResultShape(INDArray first, INDArray second){ if(first.equalShapes(second)){ return first.shape(); } else if(Shape.areShapesBroadcastable(first.shape(), second.shape())){ return Shape.broadcastOutputShape(first.shape(), second.shape()); } else { throw new IllegalStateException("Array shapes are not broadcastable: " + Arrays.toString(first.shape()) + " vs. " + Arrays.toString(second.shape())); } }