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

Class BroadcastGradientArgs

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.BroadcastGradientArgs

All Implemented Interfaces:

BroadcastOp, Op

public class BroadcastGradientArgs
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
BroadcastGradientArgs()
BroadcastGradientArgs(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BroadcastGradientArgs(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BroadcastGradientArgs(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)
BroadcastGradientArgs(INDArray x, INDArray y, INDArray z, int... dimension)

Method Summary

Modifier and Type	Method	Description
List<DataType>	calculateOutputDataTypes(List<DataType> dataTypes)	Calculate the data types for the output arrays.
List<SDVariable>	doDiff(List<SDVariable> f1)	The actual implementation for automatic differentiation.
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.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, onnxName, outputVariables, setX, setY, setZ, tensorflowName, toCustomOp, toString, x, y, z

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

arg, arg, argNames, args, attributeAdaptersForFunction, 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

BroadcastGradientArgs

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

BroadcastGradientArgs

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

BroadcastGradientArgs

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

BroadcastGradientArgs

public BroadcastGradientArgs()

BroadcastGradientArgs

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

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

calculateOutputDataTypes

public List<DataType> calculateOutputDataTypes(List<DataType> dataTypes)

Description copied from class: DifferentialFunction

Calculate the data types for the output arrays. Though datatypes can also be inferred from DifferentialFunction.calculateOutputShape(), this method differs in that it does not require the input arrays to be populated. This is important as it allows us to do greedy datatype inference for the entire net - even if arrays are not available.

Overrides:

calculateOutputDataTypes in class DifferentialFunction

Parameters:

dataTypes - The data types of the inputs

Returns:

The data types of the outputs

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: