public class ConfusionMatrix extends DynamicCustomOp
DynamicCustomOp.DynamicCustomOpsBuilder
Modifier and Type | Field and Description |
---|---|
static DataType |
DEFAULT_DTYPE |
axis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, tArguments
dimensions, extraArgs, inPlace, sameDiff, scalarValue
Constructor and Description |
---|
ConfusionMatrix() |
ConfusionMatrix(@NonNull INDArray labels,
@NonNull INDArray predicted,
@NonNull DataType dataType) |
ConfusionMatrix(@NonNull INDArray labels,
@NonNull INDArray predicted,
INDArray weights) |
ConfusionMatrix(@NonNull INDArray labels,
@NonNull INDArray predicted,
INDArray weights,
Integer numClasses) |
ConfusionMatrix(@NonNull INDArray labels,
@NonNull INDArray predicted,
INDArray weights,
Integer numClasses,
@NonNull DataType dataType) |
ConfusionMatrix(@NonNull INDArray labels,
@NonNull INDArray predicted,
int numClasses) |
ConfusionMatrix(@NonNull INDArray labels,
@NonNull INDArray predicted,
Integer numClasses,
@NonNull 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) |
ConfusionMatrix(SameDiff sameDiff,
SDVariable labels,
SDVariable pred,
SDVariable weights,
DataType dataType) |
ConfusionMatrix(SameDiff sameDiff,
SDVariable labels,
SDVariable pred,
SDVariable weights,
Integer numClasses) |
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
|
addBArgument, addDArgument, addIArgument, addIArgument, addInputArgument, addOutputArgument, addTArgument, assertValidForExecution, bArgs, builder, calculateOutputShape, calculateOutputShape, clearArrays, dArgs, getBArgument, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getTArgument, iArgs, initFromOnnx, inputArguments, numBArguments, numDArguments, numIArguments, numInputArguments, numOutputArguments, numTArguments, onnxName, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, removeIArgument, removeInputArgument, removeOutputArgument, removeTArgument, setInputArgument, setInputArguments, setOutputArgument, tArgs, toString, wrapFilterNull, wrapOrNull, wrapOrNull
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
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
isInplaceCall
public static final DataType DEFAULT_DTYPE
public ConfusionMatrix()
public ConfusionMatrix(@NonNull @NonNull INDArray labels, @NonNull @NonNull INDArray predicted, @NonNull @NonNull DataType dataType)
public ConfusionMatrix(@NonNull @NonNull INDArray labels, @NonNull @NonNull INDArray predicted, int numClasses)
public ConfusionMatrix(@NonNull @NonNull INDArray labels, @NonNull @NonNull INDArray predicted, INDArray weights)
public ConfusionMatrix(@NonNull @NonNull INDArray labels, @NonNull @NonNull INDArray predicted, INDArray weights, Integer numClasses)
public ConfusionMatrix(@NonNull @NonNull INDArray labels, @NonNull @NonNull INDArray predicted, Integer numClasses, @NonNull @NonNull DataType dataType)
public ConfusionMatrix(@NonNull @NonNull INDArray labels, @NonNull @NonNull INDArray predicted, INDArray weights, Integer numClasses, @NonNull @NonNull DataType dataType)
public ConfusionMatrix(SameDiff sameDiff, SDVariable labels, SDVariable pred, SDVariable weights, DataType dataType)
public ConfusionMatrix(SameDiff sameDiff, SDVariable labels, SDVariable pred, DataType dataType)
public ConfusionMatrix(SameDiff sameDiff, SDVariable labels, SDVariable pred, SDVariable weights)
public ConfusionMatrix(SameDiff sameDiff, SDVariable labels, SDVariable pred, Integer numClasses)
public ConfusionMatrix(SameDiff sameDiff, SDVariable labels, SDVariable pred, SDVariable weights, Integer numClasses)
public ConfusionMatrix(SameDiff sameDiff, SDVariable labels, SDVariable pred, Integer numClasses, SDVariable weights)
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
DifferentialFunction
NodeDef
initFromTensorFlow
in class DynamicCustomOp
public String opName()
DynamicCustomOp
opName
in interface CustomOp
opName
in class DynamicCustomOp
public String tensorflowName()
DifferentialFunction
tensorflowName
in class DynamicCustomOp
public List<SDVariable> doDiff(List<SDVariable> i_v)
DifferentialFunction
doDiff
in class DynamicCustomOp
public List<DataType> calculateOutputDataTypes(List<DataType> dataTypes)
DifferentialFunction
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.calculateOutputDataTypes
in class DifferentialFunction
dataTypes
- The data types of the inputsCopyright © 2020. All rights reserved.