public class FusedBatchNorm extends DynamicCustomOp
DynamicCustomOp.DynamicCustomOpsBuilder
axis, bArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, tArguments
dimensions, extraArgs, inPlace, sameDiff, scalarValue
Constructor and Description |
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FusedBatchNorm() |
FusedBatchNorm(INDArray x,
INDArray scale,
INDArray offset,
int dataFormat,
int isTraining,
INDArray yOut,
INDArray batchMeanOut,
INDArray batchMeanVar) |
FusedBatchNorm(SameDiff sameDiff,
SDVariable x,
SDVariable scale,
SDVariable offset,
SDVariable dataFormat,
SDVariable isTraining) |
Modifier and Type | Method and Description |
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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, addIArgument, addIArgument, addInputArgument, addOutputArgument, addTArgument, assertValidForExecution, bArgs, builder, calculateOutputShape, clearArrays, doDiff, getBArgument, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getTArgument, iArgs, initFromOnnx, initFromTensorFlow, inputArguments, numBArguments, numIArguments, numInputArguments, numOutputArguments, numTArguments, onnxName, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, removeIArgument, removeInputArgument, removeOutputArgument, removeTArgument, setInputArgument, setInputArguments, setOutputArgument, tArgs, toString, wrapFilterNull, wrapOrNull
arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, diff, dup, equals, f, getNumOutputs, getValue, hashCode, isConfigProperties, larg, mappingsForFunction, onnxNames, outputVariable, outputVariablesNames, propertiesForFunction, rarg, replaceArg, setInstanceId, setPropertiesForFunction, setValueFor, tensorflowNames
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
isInplaceCall
public FusedBatchNorm()
public FusedBatchNorm(@NonNull INDArray x, @NonNull INDArray scale, @NonNull INDArray offset, int dataFormat, int isTraining, INDArray yOut, INDArray batchMeanOut, INDArray batchMeanVar)
public FusedBatchNorm(@NonNull SameDiff sameDiff, @NonNull SDVariable x, @NonNull SDVariable scale, @NonNull SDVariable offset, @NonNull SDVariable dataFormat, @NonNull SDVariable isTraining)
public String opName()
DynamicCustomOp
opName
in interface CustomOp
opName
in class DynamicCustomOp
public String tensorflowName()
DifferentialFunction
tensorflowName
in class DynamicCustomOp
public List<DataType> calculateOutputDataTypes(List<DataType> inputDataTypes)
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
inputDataTypes
- The data types of the inputsCopyright © 2019. All rights reserved.