org.nd4j.linalg.api.ops.impl.reduce.bool

Class IsInf

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.BaseReduceBoolOp

org.nd4j.linalg.api.ops.impl.reduce.bool.IsInf

All Implemented Interfaces:

Op, ReduceBoolOp, ReduceOp

public class IsInf
extends BaseReduceBoolOp

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.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
IsInf()
IsInf(INDArray x)
IsInf(INDArray x, INDArray z)
IsInf(SameDiff sameDiff, SDVariable i_v, int[] dims)
IsInf(SameDiff sameDiff, SDVariable i_v, int[] dims, boolean keepDims)

Method Summary

Modifier and Type	Method and Description
List<SDVariable>	doDiff(List<SDVariable> i_v) The actual implementation for automatic differentiation.
boolean	emptyValue()
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)

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

calculateOutputDataTypes, calculateOutputShape, calculateOutputShape, getOpType, opType, resultType, resultType, validateDataTypes

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

hasReductionIndices, initFromOnnx, initFromTensorFlow, isComplexAccumulation, isKeepDims, noOp, 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, tensorflowName, 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, isComplexAccumulation, isKeepDims, noOp, setDimensions

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

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

Constructor Detail

IsInf

public IsInf(SameDiff sameDiff,
             SDVariable i_v,
             int[] dims)

IsInf

public IsInf(SameDiff sameDiff,
             SDVariable i_v,
             int[] dims,
             boolean keepDims)

IsInf

public IsInf()

IsInf

public IsInf(INDArray x,
             INDArray z)

IsInf

public IsInf(INDArray x)

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 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

onnxName

public String onnxName()

Description copied from class: DifferentialFunction

The opName of this function in onnx

Overrides:

onnxName in class BaseOp

Returns:

doDiff

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

Description copied from class: DifferentialFunction

The actual implementation for automatic differentiation.

Specified by:

doDiff in class DifferentialFunction

Returns:

emptyValue

public boolean emptyValue()

Specified by:

emptyValue in class BaseReduceBoolOp