Package org.nd4j.linalg.api.ops.impl.loss.bp

Class MeanPairwiseSquaredErrorLossBp

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.DynamicCustomOp

org.nd4j.linalg.api.ops.impl.loss.bp.BaseLossBp

org.nd4j.linalg.api.ops.impl.loss.bp.MeanPairwiseSquaredErrorLossBp

All Implemented Interfaces:

CustomOp

public class MeanPairwiseSquaredErrorLossBp
extends BaseLossBp

Nested Class Summary

Nested classes/interfaces inherited from class org.nd4j.linalg.api.ops.DynamicCustomOp

DynamicCustomOp.DynamicCustomOpsBuilder

Field Summary

Fields inherited from class org.nd4j.linalg.api.ops.impl.loss.bp.BaseLossBp

lossReduce

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

axis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, sArguments, tArguments

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

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

Constructor Summary

Constructors

Constructor	Description
MeanPairwiseSquaredErrorLossBp()
MeanPairwiseSquaredErrorLossBp(SameDiff sameDiff, LossReduce lossReduce, SDVariable predictions, SDVariable weights, SDVariable labels)

Method Summary

Modifier and Type	Method	Description
List<SDVariable>	doDiff(List<SDVariable> grad)	The actual implementation for automatic differentiation.
String	opName()	This method returns op opName as string

Methods inherited from class org.nd4j.linalg.api.ops.impl.loss.bp.BaseLossBp

addArgs, calculateOutputDataTypes, getNumOutputs

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

addBArgument, addDArgument, addIArgument, addIArgument, addInputArgument, addOutputArgument, addOutputsToOp, addSArgument, addTArgument, assertValidForExecution, bArgs, builder, calculateOutputShape, calculateOutputShape, clearArrays, computeArrays, configureFromArguments, dArgs, generateFake, generateFake, getBArgument, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getSArgument, getTArgument, getValue, iArgs, initFromOnnx, initFromTensorFlow, inputArguments, mappingsForFunction, numBArguments, numDArguments, numIArguments, numInputArguments, numOutputArguments, numSArguments, numTArguments, onnxName, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, propertiesForFunction, removeIArgument, removeInputArgument, removeOutputArgument, removeSArgument, removeTArgument, sArgs, setInputArgument, setInputArguments, setOutputArgument, setPropertiesForFunction, setValueFor, tArgs, tensorflowName, toString, wrapFilterNull, wrapOrNull, wrapOrNull

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

arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, configureWithSameDiff, diff, dup, equals, getBooleanFromProperty, getDoubleValueFromProperty, getIntValueFromProperty, getLongValueFromProperty, getStringFromProperty, hashCode, isConfigProperties, larg, onnxNames, outputs, outputVariable, outputVariablesNames, rarg, replaceArg, setInstanceId, 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.CustomOp

isInplaceCall

Constructor Detail

MeanPairwiseSquaredErrorLossBp

public MeanPairwiseSquaredErrorLossBp(SameDiff sameDiff,
                                      LossReduce lossReduce,
                                      SDVariable predictions,
                                      SDVariable weights,
                                      SDVariable labels)

MeanPairwiseSquaredErrorLossBp

public MeanPairwiseSquaredErrorLossBp()

Method Detail

opName

public String opName()

Description copied from class: DynamicCustomOp

This method returns op opName as string

Specified by:

opName in interface CustomOp

Specified by:

opName in class BaseLossBp

Returns:

doDiff

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

Description copied from class: DifferentialFunction

The actual implementation for automatic differentiation.

Overrides:

doDiff in class BaseLossBp

Returns: