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

Class BaseLoss

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.DynamicCustomOp

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

All Implemented Interfaces:

CustomOp

Direct Known Subclasses:

AbsoluteDifferenceLoss, CosineDistanceLoss, HingeLoss, HuberLoss, LogLoss, LogPoissonLoss, MeanPairwiseSquaredErrorLoss, MeanSquaredErrorLoss, SigmoidCrossEntropyLoss, SoftmaxCrossEntropyLoss, WeightedCrossEntropyLoss

public abstract class BaseLoss
extends DynamicCustomOp

Nested Class Summary

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

DynamicCustomOp.DynamicCustomOpsBuilder

Field Summary

Fields

Modifier and Type	Field	Description
protected LossReduce	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

Modifier	Constructor	Description
protected	BaseLoss()
	BaseLoss(@NonNull LossReduce lossReduce, @NonNull INDArray predictions, INDArray weights, @NonNull INDArray labels)
	BaseLoss(@NonNull SameDiff sameDiff, @NonNull LossReduce lossReduce, @NonNull SDVariable predictions, SDVariable weights, @NonNull SDVariable labels)

Method Summary

Modifier and Type	Method	Description
protected void	addArgs()
List<DataType>	calculateOutputDataTypes(List<DataType> inputDataTypes)	Calculate the data types for the output arrays.
protected static SDVariable	getWeights(SameDiff sd, SDVariable weights, SDVariable predictions)
protected static INDArray	getWeights(INDArray weights, INDArray predictions)
abstract String	opName()	This method returns op opName as string

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, doDiff, 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, getNumOutputs, 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

Field Detail

lossReduce

protected LossReduce lossReduce

Constructor Detail

BaseLoss

public BaseLoss(@NonNull
                @NonNull SameDiff sameDiff,
                @NonNull
                @NonNull LossReduce lossReduce,
                @NonNull
                @NonNull SDVariable predictions,
                SDVariable weights,
                @NonNull
                @NonNull SDVariable labels)

BaseLoss

public BaseLoss(@NonNull
                @NonNull LossReduce lossReduce,
                @NonNull
                @NonNull INDArray predictions,
                INDArray weights,
                @NonNull
                @NonNull INDArray labels)

BaseLoss

protected BaseLoss()

Method Detail

getWeights

protected static INDArray getWeights(INDArray weights,
                                     INDArray predictions)

getWeights

protected static SDVariable getWeights(SameDiff sd,
                                       SDVariable weights,
                                       SDVariable predictions)

addArgs

protected void addArgs()

opName

public abstract String opName()

Description copied from class: DynamicCustomOp

This method returns op opName as string

Specified by:

opName in interface CustomOp

Overrides:

opName in class DynamicCustomOp

Returns:

calculateOutputDataTypes

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

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:

inputDataTypes - The data types of the inputs

Returns:

The data types of the outputs