org.nd4j.linalg.api.ops.impl.summarystats

Class StandardDeviation

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.BaseOp

org.nd4j.linalg.api.ops.BaseReduceOp

org.nd4j.linalg.api.ops.impl.summarystats.Variance

org.nd4j.linalg.api.ops.impl.summarystats.StandardDeviation

All Implemented Interfaces:

Op, ReduceOp

public class StandardDeviation
extends Variance

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.impl.summarystats.Variance

bias, biasCorrected, mean

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

isComplex, isEmptyReduce, keepDims

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

dimensionz, extraArgz, x, xVertexId, y, yVertexId, z, zVertexId

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

dimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue

Constructor Summary

Constructors

Constructor and Description
StandardDeviation()
StandardDeviation(INDArray x)
StandardDeviation(INDArray x, boolean biasCorrected, boolean keepDims, int... dimension)
StandardDeviation(INDArray x, boolean biasCorrected, int... dimension)
StandardDeviation(INDArray x, INDArray z, boolean newFormat, boolean keepDims, int[] dimensions)
StandardDeviation(INDArray x, INDArray z, boolean biasCorrected, int... dimension)
StandardDeviation(SameDiff sameDiff, SDVariable i_v, boolean biasCorrected, boolean keepDims, int[] dimensions)

Method Summary

Modifier and Type	Method and Description
List<LongShapeDescriptor>	calculateOutputShape() Calculate the output shape for this op
List<SDVariable>	doDiff(List<SDVariable> grad) 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.impl.summarystats.Variance

calculateOutputDataTypes, calculateOutputShape, isBiasCorrected, noOp, resultType, resultType, setBiasCorrected, validateDataTypes

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

hasReductionIndices, initFromOnnx, initFromTensorFlow, isComplexAccumulation, isKeepDims, setDimensions

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

clearArrays, defineDimensions, dimensions, equals, extraArgs, extraArgsBuff, extraArgsDataBuff, getFinalResult, getInputArgument, getNumOutputs, getOpType, hashCode, outputVariables, setX, setY, setZ, toCustomOp, toString, x, y, z

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

arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, diff, dup, getValue, isConfigProperties, larg, mappingsForFunction, onnxNames, outputs, outputVariable, outputVariables, outputVariablesNames, propertiesForFunction, rarg, replaceArg, setInstanceId, setPropertiesForFunction, 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.ReduceOp

dimensions, getFinalResult

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

clearArrays, extraArgs, extraArgsBuff, extraArgsDataBuff, setExtraArgs, setX, setY, setZ, toCustomOp, x, y, z

Constructor Detail

StandardDeviation

public StandardDeviation(SameDiff sameDiff,
                         SDVariable i_v,
                         boolean biasCorrected,
                         boolean keepDims,
                         int[] dimensions)

StandardDeviation

public StandardDeviation(INDArray x,
                         boolean biasCorrected,
                         boolean keepDims,
                         int... dimension)

StandardDeviation

public StandardDeviation(INDArray x,
                         boolean biasCorrected,
                         int... dimension)

StandardDeviation

public StandardDeviation()

StandardDeviation

public StandardDeviation(INDArray x)

StandardDeviation

public StandardDeviation(INDArray x,
                         INDArray z,
                         boolean biasCorrected,
                         int... dimension)

StandardDeviation

public StandardDeviation(INDArray x,
                         INDArray z,
                         boolean newFormat,
                         boolean keepDims,
                         int[] dimensions)

Method Detail

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 Variance

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 Variance

Returns:

the opName of this operation

onnxName

public String onnxName()

Description copied from class: DifferentialFunction

The opName of this function in onnx

Overrides:

onnxName in class Variance

Returns:

tensorflowName

public String tensorflowName()

Description copied from class: DifferentialFunction

The opName of this function tensorflow

Overrides:

tensorflowName in class Variance

Returns:

getOpType

public Op.Type getOpType()

Specified by:

getOpType in interface ReduceOp

Overrides:

getOpType in class Variance

opType

public Op.Type opType()

Description copied from class: DifferentialFunction

The type of the op

Overrides:

opType in class Variance

Returns:

doDiff

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

Description copied from class: DifferentialFunction

The actual implementation for automatic differentiation.

Overrides:

doDiff in class Variance

Returns:

calculateOutputShape

public List<LongShapeDescriptor> calculateOutputShape()

Description copied from class: DifferentialFunction

Calculate the output shape for this op

Overrides:

calculateOutputShape in class Variance

Returns:

List of output shape descriptors