public class EncodeThreshold extends DynamicCustomOp
DynamicCustomOp.DynamicCustomOpsBuilder
Modifier and Type | Field and Description |
---|---|
protected int |
boundary |
protected float |
threshold |
axis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, sArguments, tArguments
dimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue
Constructor and Description |
---|
EncodeThreshold() |
EncodeThreshold(@NonNull INDArray updates,
float threshold) |
EncodeThreshold(@NonNull INDArray updates,
float threshold,
@NonNull Integer boundary) |
EncodeThreshold(@NonNull INDArray updates,
@NonNull INDArray encoded,
float threshold,
@NonNull Integer boundary) |
Modifier and Type | Method and Description |
---|---|
List<DataType> |
calculateOutputDataTypes(List<DataType> dataTypes)
Calculate the data types for the output arrays.
|
String |
opName()
This method returns op opName as string
|
addBArgument, addDArgument, addIArgument, addIArgument, addInputArgument, addOutputArgument, 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
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
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
isInplaceCall
public EncodeThreshold()
public EncodeThreshold(@NonNull @NonNull INDArray updates, float threshold)
public EncodeThreshold(@NonNull @NonNull INDArray updates, @NonNull @NonNull INDArray encoded, float threshold, @NonNull @NonNull Integer boundary)
public String opName()
DynamicCustomOp
opName
in interface CustomOp
opName
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 © 2022. All rights reserved.