org.nd4j.linalg.api.ops.impl.shape

Class ConfusionMatrix

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.DynamicCustomOp

org.nd4j.linalg.api.ops.impl.shape.ConfusionMatrix

All Implemented Interfaces:

CustomOp

public class ConfusionMatrix
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 and Description
static DataType	DEFAULT_DTYPE

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

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

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

dimensions, extraArgs, inPlace, sameDiff, scalarValue

Constructor Summary

Constructors

Constructor and Description
ConfusionMatrix()
ConfusionMatrix(INDArray labels, INDArray predicted, DataType dataType)
ConfusionMatrix(INDArray labels, INDArray predicted, INDArray weights)
ConfusionMatrix(INDArray labels, INDArray predicted, INDArray weights, Integer numClasses)
ConfusionMatrix(INDArray labels, INDArray predicted, INDArray weights, Integer numClasses, DataType dataType)
ConfusionMatrix(INDArray labels, INDArray predicted, int numClasses)
ConfusionMatrix(INDArray labels, INDArray predicted, Integer numClasses, DataType dataType)
ConfusionMatrix(SameDiff sameDiff, SDVariable labels, SDVariable pred, DataType dataType)
ConfusionMatrix(SameDiff sameDiff, SDVariable labels, SDVariable pred, Integer numClasses)
ConfusionMatrix(SameDiff sameDiff, SDVariable labels, SDVariable pred, Integer numClasses, SDVariable weights)
ConfusionMatrix(SameDiff sameDiff, SDVariable labels, SDVariable pred, SDVariable weights)

Method Summary

Modifier and Type	Method and Description
List<DataType>	calculateOutputDataTypes(List<DataType> dataTypes) Calculate the data types for the output arrays.
List<SDVariable>	doDiff(List<SDVariable> i_v) The actual implementation for automatic differentiation.
void	initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph) Initialize the function from the given NodeDef
String	opName() This method returns op opName as string
String	tensorflowName() The opName of this function tensorflow

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

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

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

arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, diff, dup, equals, f, getNumOutputs, getValue, hashCode, isConfigProperties, larg, mappingsForFunction, onnxNames, 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

Field Detail

DEFAULT_DTYPE

public static final DataType DEFAULT_DTYPE

Constructor Detail

ConfusionMatrix

public ConfusionMatrix()

ConfusionMatrix

public ConfusionMatrix(@NonNull
                       INDArray labels,
                       @NonNull
                       INDArray predicted,
                       @NonNull
                       DataType dataType)

ConfusionMatrix

public ConfusionMatrix(@NonNull
                       INDArray labels,
                       @NonNull
                       INDArray predicted,
                       int numClasses)

ConfusionMatrix

public ConfusionMatrix(@NonNull
                       INDArray labels,
                       @NonNull
                       INDArray predicted,
                       INDArray weights)

ConfusionMatrix

public ConfusionMatrix(@NonNull
                       INDArray labels,
                       @NonNull
                       INDArray predicted,
                       INDArray weights,
                       Integer numClasses)

ConfusionMatrix

public ConfusionMatrix(@NonNull
                       INDArray labels,
                       @NonNull
                       INDArray predicted,
                       Integer numClasses,
                       @NonNull
                       DataType dataType)

ConfusionMatrix

public ConfusionMatrix(@NonNull
                       INDArray labels,
                       @NonNull
                       INDArray predicted,
                       INDArray weights,
                       Integer numClasses,
                       @NonNull
                       DataType dataType)

ConfusionMatrix

public ConfusionMatrix(SameDiff sameDiff,
                       SDVariable labels,
                       SDVariable pred,
                       DataType dataType)

ConfusionMatrix

public ConfusionMatrix(SameDiff sameDiff,
                       SDVariable labels,
                       SDVariable pred,
                       SDVariable weights)

ConfusionMatrix

public ConfusionMatrix(SameDiff sameDiff,
                       SDVariable labels,
                       SDVariable pred,
                       Integer numClasses)

ConfusionMatrix

public ConfusionMatrix(SameDiff sameDiff,
                       SDVariable labels,
                       SDVariable pred,
                       Integer numClasses,
                       SDVariable weights)

Method Detail

initFromTensorFlow

public void initFromTensorFlow(NodeDef nodeDef,
                               SameDiff initWith,
                               Map<String,AttrValue> attributesForNode,
                               GraphDef graph)

Description copied from class: DifferentialFunction

Initialize the function from the given NodeDef

Overrides:

initFromTensorFlow in class DynamicCustomOp

opName

public 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:

tensorflowName

public String tensorflowName()

Description copied from class: DifferentialFunction

The opName of this function tensorflow

Overrides:

tensorflowName in class DynamicCustomOp

Returns:

doDiff

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

Description copied from class: DifferentialFunction

The actual implementation for automatic differentiation.

Overrides:

doDiff in class DynamicCustomOp

Returns:

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