public class CyclicShiftBits extends BaseDynamicTransformOp
DynamicCustomOp.DynamicCustomOpsBuilderaxis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, tArgumentsdimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue| Constructor and Description |
|---|
CyclicShiftBits() |
CyclicShiftBits(INDArray input,
INDArray shift) |
CyclicShiftBits(INDArray input,
INDArray shift,
INDArray output) |
CyclicShiftBits(SameDiff sameDiff,
SDVariable x,
SDVariable shift) |
| 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.
|
String |
onnxName()
The opName of this function in onnx
|
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, initFromTensorFlow, inputArguments, numBArguments, numDArguments, numIArguments, numInputArguments, numOutputArguments, numTArguments, 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 CyclicShiftBits(SameDiff sameDiff, SDVariable x, SDVariable shift)
public CyclicShiftBits()
public String opName()
DynamicCustomOpopName in interface CustomOpopName in class DynamicCustomOppublic String onnxName()
DifferentialFunctiononnxName in class DynamicCustomOppublic String tensorflowName()
DifferentialFunctiontensorflowName in class DynamicCustomOppublic List<SDVariable> doDiff(List<SDVariable> i_v)
DifferentialFunctiondoDiff 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 BaseDynamicTransformOpdataTypes - The data types of the inputsCopyright © 2021. All rights reserved.