org.nd4j.linalg.api.ops.impl.accum.distances

Class CosineDistance

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.BaseOp

org.nd4j.linalg.api.ops.BaseAccumulation

org.nd4j.linalg.api.ops.impl.accum.distances.CosineDistance

All Implemented Interfaces:

Accumulation, Op

public class CosineDistance
extends BaseAccumulation

Cosine distance Note that you need to initialize a scaling constant equal to the norm2 of the vector

Author:

raver119@gmail.com

Nested Class Summary

Nested classes/interfaces inherited from interface org.nd4j.linalg.api.ops.Op

Op.Type

Field Summary

Fields inherited from class org.nd4j.linalg.api.ops.BaseAccumulation

finalResult, isComplex, keepDims, newFormat

Fields inherited from class org.nd4j.linalg.api.ops.BaseOp

extraArgs, extraArgz, n, numProcessed, passThrough, x, xVertexId, y, yVertexId, z, zVertexId

Fields inherited from class org.nd4j.autodiff.functions.DifferentialFunction

dimensions, inPlace, sameDiff, scalarValue

Constructor Summary

Constructors

Constructor and Description
CosineDistance()
CosineDistance(INDArray x)
CosineDistance(INDArray x, INDArray y)
CosineDistance(INDArray x, INDArray y, boolean allDistances)
CosineDistance(INDArray x, INDArray y, INDArray z, boolean allDistances)
CosineDistance(INDArray x, INDArray y, INDArray z, long n)
CosineDistance(INDArray x, INDArray y, long n)
CosineDistance(SameDiff sameDiff, SDVariable i_v, int[] dimensions, Number constantNormalizedByNorm2X, Number constantNormalizedByNorm2Y)
CosineDistance(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int... dimensions)

Method Summary

Modifier and Type	Method and Description
List<SDVariable>	doDiff(List<SDVariable> i_v1) The actual implementation for automatic differentiation.
Op.Type	getOpType()
String	onnxName() The opName of this function in onnx
String	opName() The name of the op
int	opNum() The number of the op (mainly for old legacy XYZ ops like Op)
Op.Type	opType() The type of the op
String	tensorflowName() The opName of this function tensorflow

Methods inherited from class org.nd4j.linalg.api.ops.BaseAccumulation

calculateOutputShape, getFinalResult, hasReductionIndices, initFromOnnx, initFromTensorFlow, isComplexAccumulation, isKeepDims, noOp, setFinalResult, zeroDouble, zeroFloat, zeroHalf

Methods inherited from class org.nd4j.linalg.api.ops.BaseOp

equals, exec, exec, extraArgs, extraArgsBuff, extraArgsDataBuff, getOpType, hashCode, init, isExecSpecial, isPassThrough, n, numProcessed, outputVariables, setN, setX, setY, setZ, toCustomOp, toString, x, y, z

Methods inherited from class org.nd4j.autodiff.functions.DifferentialFunction

arg, args, asProperties, attributeAdaptersForFunction, configFieldName, diff, dup, f, getValue, hasPlaceHolderInputs, isConfigProperties, larg, mappingsForFunction, onnxNames, outputVariables, propertiesForFunction, rarg, resolvePropertiesFromSameDiffBeforeExecution, setInstanceId, setValueFor, tensorflowNames

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface org.nd4j.linalg.api.ops.Op

exec, exec, extraArgs, extraArgsBuff, extraArgsDataBuff, init, isExecSpecial, isPassThrough, n, numProcessed, setExtraArgs, setN, setX, setY, setZ, toCustomOp, x, y, z

Constructor Detail

CosineDistance

public CosineDistance(SameDiff sameDiff,
                      SDVariable i_v,
                      int[] dimensions,
                      Number constantNormalizedByNorm2X,
                      Number constantNormalizedByNorm2Y)

CosineDistance

public CosineDistance(SameDiff sameDiff,
                      SDVariable i_v,
                      SDVariable i_v2,
                      int... dimensions)

CosineDistance

public CosineDistance()

CosineDistance

public CosineDistance(INDArray x,
                      INDArray y,
                      INDArray z,
                      long n)

CosineDistance

public CosineDistance(INDArray x,
                      INDArray y,
                      long n)

CosineDistance

public CosineDistance(INDArray x)

CosineDistance

public CosineDistance(INDArray x,
                      INDArray y)

CosineDistance

public CosineDistance(INDArray x,
                      INDArray y,
                      INDArray z,
                      boolean allDistances)

CosineDistance

public CosineDistance(INDArray x,
                      INDArray y,
                      boolean allDistances)

Method Detail

opType

public Op.Type opType()

Description copied from class: DifferentialFunction

The type of the op

Overrides:

opType in class BaseAccumulation

Returns:

getOpType

public Op.Type getOpType()

opNum

public int opNum()

Description copied from class: DifferentialFunction

The number of the op (mainly for old legacy XYZ ops like Op)

Specified by:

opNum in interface Op

Overrides:

opNum in class DifferentialFunction

Returns:

opName

public String opName()

Description copied from class: DifferentialFunction

The name of the op

Specified by:

opName in interface Op

Overrides:

opName in class DifferentialFunction

Returns:

the opName of this operation

doDiff

public List<SDVariable> doDiff(List<SDVariable> i_v1)

Description copied from class: DifferentialFunction

The actual implementation for automatic differentiation.

Specified by:

doDiff in class DifferentialFunction

Returns:

onnxName

public String onnxName()

Description copied from class: DifferentialFunction

The opName of this function in onnx

Specified by:

onnxName in class DifferentialFunction

Returns:

tensorflowName

public String tensorflowName()

Description copied from class: DifferentialFunction

The opName of this function tensorflow

Specified by:

tensorflowName in class DifferentialFunction

Returns: