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

Class MeanSquaredErrorLoss

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.DynamicCustomOp

org.nd4j.linalg.api.ops.impl.loss.BaseLoss

org.nd4j.linalg.api.ops.impl.loss.MeanSquaredErrorLoss

All Implemented Interfaces:

CustomOp

public class MeanSquaredErrorLoss
extends BaseLoss

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.BaseLoss

lossReduce

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

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

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

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

Constructor Summary

Constructors

Constructor and Description
MeanSquaredErrorLoss()
MeanSquaredErrorLoss(INDArray labels, INDArray predictions, INDArray weights, LossReduce lossReduce)
MeanSquaredErrorLoss(SameDiff sameDiff, LossReduce lossReduce, SDVariable predictions, SDVariable weights, SDVariable labels)
MeanSquaredErrorLoss(SameDiff sameDiff, SDVariable labels, SDVariable predictions, SDVariable weights, LossReduce lossReduce)

Method Summary

Modifier and Type	Method and 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.BaseLoss

addArgs, calculateOutputDataTypes, getWeights, getWeights

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

addBArgument, addDArgument, addIArgument, addIArgument, addInputArgument, addOutputArgument, addTArgument, assertValidForExecution, bArgs, builder, calculateOutputShape, calculateOutputShape, clearArrays, dArgs, getBArgument, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getTArgument, iArgs, initFromOnnx, initFromTensorFlow, inputArguments, numBArguments, numDArguments, numIArguments, numInputArguments, numOutputArguments, numTArguments, onnxName, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, removeIArgument, removeInputArgument, removeOutputArgument, removeTArgument, setInputArgument, setInputArguments, setOutputArgument, tArgs, tensorflowName, toString, wrapFilterNull, wrapOrNull, wrapOrNull

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

arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, diff, dup, equals, getNumOutputs, getValue, hashCode, isConfigProperties, larg, mappingsForFunction, onnxNames, outputs, outputVariable, 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.CustomOp

isInplaceCall

Constructor Detail

MeanSquaredErrorLoss

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

MeanSquaredErrorLoss

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

MeanSquaredErrorLoss

public MeanSquaredErrorLoss(INDArray labels,
                            INDArray predictions,
                            INDArray weights,
                            LossReduce lossReduce)

MeanSquaredErrorLoss

public MeanSquaredErrorLoss()

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 BaseLoss

Returns:

doDiff

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

Description copied from class: DifferentialFunction

The actual implementation for automatic differentiation.

Overrides:

doDiff in class DynamicCustomOp

Returns: