Package org.nd4j.linalg.api.ops.impl.broadcast

Class BroadcastRDivOp

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.BaseOp

org.nd4j.linalg.api.ops.BaseBroadcastOp

org.nd4j.linalg.api.ops.impl.broadcast.BroadcastRDivOp

All Implemented Interfaces:

BroadcastOp, Op

public class BroadcastRDivOp
extends BaseBroadcastOp

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.BaseBroadcastOp

dimension

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	Description
BroadcastRDivOp()
BroadcastRDivOp(SameDiff sameDiff)
BroadcastRDivOp(SameDiff sameDiff, SDVariable i_v, int[] dimension, boolean inPlace)
BroadcastRDivOp(SameDiff sameDiff, SDVariable i_v, int[] dimension, Object[] extraArgs)
BroadcastRDivOp(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, int[] dimension, Object[] extraArgs)
BroadcastRDivOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BroadcastRDivOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BroadcastRDivOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)
BroadcastRDivOp(INDArray x, INDArray y, INDArray z, int... dimension)

Method Summary

Modifier and Type	Method	Description
List<SDVariable>	doDiff(List<SDVariable> f1)	The actual implementation for automatic differentiation.
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)
String	tensorflowName()	The opName of this function tensorflow

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

calculateOutputShape, getDimension, getOpType, initFromOnnx, initFromTensorFlow, opType, setDimension, validateDataTypes

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

clearArrays, computeVariables, 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, calculateOutputDataTypes, calculateOutputShape, configFieldName, configureWithSameDiff, diff, dup, getBooleanFromProperty, getDoubleValueFromProperty, getIntValueFromProperty, getLongValueFromProperty, getStringFromProperty, 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.BroadcastOp

dimensions

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

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

Constructor Detail

BroadcastRDivOp

public BroadcastRDivOp()

BroadcastRDivOp

public BroadcastRDivOp(INDArray x,
                       INDArray y,
                       INDArray z,
                       int... dimension)

BroadcastRDivOp

public BroadcastRDivOp(SameDiff sameDiff,
                       SDVariable i_v1,
                       SDVariable i_v2,
                       int[] dimension)

BroadcastRDivOp

public BroadcastRDivOp(SameDiff sameDiff,
                       SDVariable i_v1,
                       SDVariable i_v2,
                       boolean inPlace,
                       int[] dimension)

BroadcastRDivOp

public BroadcastRDivOp(SameDiff sameDiff)

BroadcastRDivOp

public BroadcastRDivOp(SameDiff sameDiff,
                       SDVariable i_v1,
                       SDVariable i_v2,
                       int[] dimension,
                       Object[] extraArgs)

BroadcastRDivOp

public BroadcastRDivOp(SameDiff sameDiff,
                       SDVariable i_v,
                       int[] dimension,
                       boolean inPlace)

BroadcastRDivOp

public BroadcastRDivOp(SameDiff sameDiff,
                       SDVariable i_v,
                       long[] shape,
                       boolean inPlace,
                       int[] dimension,
                       Object[] extraArgs)

BroadcastRDivOp

public BroadcastRDivOp(SameDiff sameDiff,
                       SDVariable i_v,
                       int[] dimension,
                       Object[] extraArgs)

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:

tensorflowName

public String tensorflowName()

Description copied from class: DifferentialFunction

The opName of this function tensorflow

Overrides:

tensorflowName in class BaseOp

Returns:

doDiff

public List<SDVariable> doDiff(List<SDVariable> f1)

Description copied from class: DifferentialFunction

The actual implementation for automatic differentiation.

Specified by:

doDiff in class DifferentialFunction

Returns: