public class Choose extends DynamicCustomOp
DynamicCustomOp.DynamicCustomOpsBuilderaxis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, tArgumentsdimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue| Constructor and Description |
|---|
Choose() |
Choose(INDArray[] inputs,
Condition condition) |
Choose(INDArray[] inputs,
List<Integer> iArgs,
List<Double> tArgs,
Condition condition)
Note that iArgs (integer arguments) and tArgs(double/float arguments)
may end up being used under the following conditions:
scalar operations (if a scalar is specified the you do not need to specify an ndarray)
otherwise, if an ndarray is needed as a second input then put it in the inputs
Usually, you only need 1 input (the equivalent of the array you're trying to do indexing on)
|
Choose(SameDiff sameDiff,
SDVariable[] args,
Condition condition) |
Choose(String opName,
INDArray[] inputs,
Condition condition) |
Choose(String opName,
INDArray[] inputs,
INDArray[] outputs,
List<Double> tArguments,
List<Integer> iArguments) |
Choose(String opName,
SameDiff sameDiff,
SDVariable[] args,
boolean inPlace) |
| 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, addTArgument, assertValidForExecution, bArgs, builder, calculateOutputShape, calculateOutputShape, clearArrays, dArgs, doDiff, 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, wrapOrNullarg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, diff, dup, equals, getNumOutputs, getValue, hashCode, isConfigProperties, larg, mappingsForFunction, onnxNames, outputs, outputVariable, outputVariablesNames, propertiesForFunction, rarg, replaceArg, setInstanceId, setPropertiesForFunction, setValueFor, tensorflowNamesclone, finalize, getClass, notify, notifyAll, wait, wait, waitisInplaceCallpublic Choose(SameDiff sameDiff, SDVariable[] args, Condition condition)
public Choose(String opName, INDArray[] inputs, INDArray[] outputs, List<Double> tArguments, List<Integer> iArguments)
public Choose(INDArray[] inputs, List<Integer> iArgs, List<Double> tArgs, Condition condition)
inputs - the inputs in to the opiArgs - the integer arguments as neededtArgs - the argumentscondition - the condition to filter onpublic Choose(String opName, SameDiff sameDiff, SDVariable[] args, boolean inPlace)
public Choose()
public String opName()
DynamicCustomOpopName in interface CustomOpopName in class DynamicCustomOppublic List<DataType> calculateOutputDataTypes(List<DataType> dataTypes)
DifferentialFunctionDifferentialFunction.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 DifferentialFunctiondataTypes - The data types of the inputsCopyright © 2021. All rights reserved.