public class Roll extends DynamicCustomOp
DynamicCustomOp.DynamicCustomOpsBuilderaxis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, tArgumentsdimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue| Constructor and Description |
|---|
Roll() |
Roll(@NonNull INDArray input,
@NonNull INDArray shifts,
@NonNull INDArray axes) |
Roll(@NonNull INDArray input,
int shift) |
Roll(@NonNull SameDiff sameDiff,
@NonNull SDVariable input,
int shift) |
Roll(@NonNull SameDiff sameDiff,
@NonNull SDVariable input,
@NonNull SDVariable shift) |
Roll(@NonNull SameDiff sameDiff,
@NonNull SDVariable input,
@NonNull SDVariable shift,
@NonNull SDVariable axes) |
| Modifier and Type | Method and Description |
|---|---|
List<DataType> |
calculateOutputDataTypes(List<DataType> inputDataTypes)
Calculate the data types for the output arrays.
|
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, 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, 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 Roll()
public Roll(@NonNull
@NonNull INDArray input,
@NonNull
@NonNull INDArray shifts,
@NonNull
@NonNull INDArray axes)
public Roll(@NonNull
@NonNull INDArray input,
int shift)
public Roll(@NonNull
@NonNull SameDiff sameDiff,
@NonNull
@NonNull SDVariable input,
@NonNull
@NonNull SDVariable shift)
public Roll(@NonNull
@NonNull SameDiff sameDiff,
@NonNull
@NonNull SDVariable input,
@NonNull
@NonNull SDVariable shift,
@NonNull
@NonNull SDVariable axes)
public Roll(@NonNull
@NonNull SameDiff sameDiff,
@NonNull
@NonNull SDVariable input,
int shift)
public String opName()
DynamicCustomOpopName in interface CustomOpopName in class DynamicCustomOppublic String tensorflowName()
DifferentialFunctiontensorflowName in class DynamicCustomOppublic List<DataType> calculateOutputDataTypes(List<DataType> inputDataTypes)
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 DifferentialFunctioninputDataTypes - The data types of the inputsCopyright © 2021. All rights reserved.