Package org.nd4j.linalg.api.ops

Interface Op

All Known Subinterfaces:

BroadcastOp, GridOp, IndexAccumulation, LossFunction, MetaOp, RandomOp, ReduceBoolOp, ReduceFloatOp, ReduceLongOp, ReduceOp, ReduceSameOp, ScalarOp, TransformBoolOp, TransformFloatOp, TransformOp, TransformSameOp, TransformStrictOp

All Known Implementing Classes:

Abs, ACos, ACosh, All, AlphaDropOut, AMax, AMax, AMean, AMin, AMin, And, Any, ASin, ASinh, Assign, ASum, ATan, ATanh, Axpy, BaseBroadcastBoolOp, BaseBroadcastOp, BaseGridOp, BaseIndexAccumulation, BaseMetaOp, BaseOp, BaseRandomOp, BaseReduce3Op, BaseReduceBoolOp, BaseReduceFloatOp, BaseReduceLongOp, BaseReduceOp, BaseReduceSameOp, BaseScalarBoolOp, BaseScalarOp, BaseTransformAnyOp, BaseTransformBoolOp, BaseTransformFloatOp, BaseTransformOp, BaseTransformSameOp, BaseTransformStrictOp, BernoulliDistribution, BinaryMinimalRelativeError, BinaryRelativeError, BinomialDistribution, BinomialDistributionEx, BooleanNot, BroadcastAddOp, BroadcastAMax, BroadcastAMin, BroadcastCopyOp, BroadcastDivOp, BroadcastEqualTo, BroadcastGradientArgs, BroadcastGreaterThan, BroadcastGreaterThanOrEqual, BroadcastLessThan, BroadcastLessThanOrEqual, BroadcastMax, BroadcastMin, BroadcastMulOp, BroadcastNotEqual, BroadcastRDivOp, BroadcastRSubOp, BroadcastSubOp, Ceil, Choice, CompareAndReplace, CompareAndSet, CopyOp, Cos, Cosh, CosineDistance, CosineSimilarity, CountNonZero, CountZero, Cube, CubeDerivative, Dot, DropOut, DropOutInverted, Entropy, Eps, EqualsWithEps, Erf, Erfc, EuclideanDistance, Exp, Expm1, FirstIndex, Floor, FModOp, FreeGridOp, GaussianDistribution, GELU, GELUDerivative, HammingDistance, HardSigmoid, HardSigmoidDerivative, HardTanh, HardTanhDerivative, InvertedPredicateMetaOp, IsFinite, IsInf, IsInf, IsNaN, IsNaN, JaccardDistance, LastIndex, LeakyReLU, LeakyReLUDerivative, Linspace, Log, Log1p, LogEntropy, LogNormalDistribution, LogSigmoid, LogX, ManhattanDistance, MatchCondition, MatchConditionTransform, Max, Max, MaxOut, Mean, Min, Min, Mish, MishDerivative, Negative, Norm1, Norm2, NormMax, Not, OneMinus, Or, PostulateMetaOp, Pow, PowDerivative, PowPairwise, PreciseGELU, PreciseGELUDerivative, PredicateMetaOp, ProbablisticMerge, Prod, RationalTanh, RationalTanhDerivative, Reciprocal, RectifiedLinear, RectifiedTanh, RectifiedTanhDerivative, ReduceMetaOp, RelativeError, Relu6, RemainderOp, ReplaceNans, Rint, Round, RSqrt, ScalarAdd, ScalarAnd, ScalarDivision, ScalarEps, ScalarEquals, ScalarFMod, ScalarGreaterThan, ScalarGreaterThanOrEqual, ScalarLessThan, ScalarLessThanOrEqual, ScalarMax, ScalarMin, ScalarMultiplication, ScalarNot, ScalarNotEquals, ScalarOr, ScalarRemainder, ScalarReverseDivision, ScalarReverseSubtraction, ScalarSet, ScalarSetValue, ScalarSubtraction, ScalarXor, SELU, SELUDerivative, Set, SetRange, ShannonEntropy, Sigmoid, SigmoidDerivative, Sign, Sin, Sinh, SoftPlus, SoftSign, SoftSignDerivative, Sqrt, Square, SquaredNorm, Stabilize, StandardDeviation, Step, Sum, Swish, SwishDerivative, Tan, TanDerivative, Tanh, TanhDerivative, TimesOneMinus, TruncatedNormalDistribution, UniformDistribution, Variance, Xor

public interface Op

Nested Class Summary

Nested Classes

Modifier and Type	Interface	Description
static class	Op.Type

Method Summary

Modifier and Type	Method	Description
void	clearArrays()	Clear the input and output INDArrays, if any are set
Object[]	extraArgs()	Extra arguments
Buffer	extraArgsBuff()	Returns a buffer of either float or double of the extra args for this buffer
DataBuffer	extraArgsDataBuff(DataType bufferType)	Returns the extra args as a data buffer
String	opName()	The opName of this operation
int	opNum()	An op number.
void	setExtraArgs(Object[] extraArgs)
void	setX(INDArray x)	set x (the input ndarray)
void	setY(INDArray y)	set y(the pairwise ndarray)
void	setZ(INDArray z)	set z (the solution ndarray)
CustomOp	toCustomOp()	Converts this op to be a CustomOp A CustomOp is a more flexible op meant for multiple inputs and outputs.
INDArray	x()	The origin ndarray
INDArray	y()	The pairwise op ndarray
INDArray	z()	The resulting ndarray

Method Detail

extraArgsDataBuff

DataBuffer extraArgsDataBuff(DataType bufferType)

Returns the extra args as a data buffer

Returns:

extraArgsBuff

Buffer extraArgsBuff()

Returns a buffer of either float or double of the extra args for this buffer

Returns:

a buffer of either opType float or double representing the extra args for this op

opNum

int opNum()

An op number. The operation numbers can be found here: deeplearning4j/libnd4jinclude/loops/legacy_ops.h

Returns:

opName

String opName()

The opName of this operation

Returns:

the opName of this operation

x

INDArray x()

The origin ndarray

Returns:

the origin ndarray

y

INDArray y()

The pairwise op ndarray

Returns:

the pairwise op ndarray

z

INDArray z()

The resulting ndarray

Returns:

the resulting ndarray

extraArgs

Object[] extraArgs()

Extra arguments

Returns:

the extra arguments

setX

void setX(INDArray x)

set x (the input ndarray)

Parameters:

x -

setZ

void setZ(INDArray z)

set z (the solution ndarray)

Parameters:

z -

setY

void setY(INDArray y)

set y(the pairwise ndarray)

Parameters:

y -

setExtraArgs

void setExtraArgs(Object[] extraArgs)

Parameters:

extraArgs -

toCustomOp

CustomOp toCustomOp()

Converts this op to be a CustomOp A CustomOp is a more flexible op meant for multiple inputs and outputs. The default implementation in BaseOp converts a simple op to a multi input/output operation by mapping the x and y on to inputs , the op opName and the z on to outputs.

Returns:

the equivalent CustomOp

clearArrays

void clearArrays()

Clear the input and output INDArrays, if any are set