public class Repeat extends DynamicCustomOp
DynamicCustomOp.DynamicCustomOpsBuilder, DynamicCustomOp.SameDiffBuilder
inplaceCall, outputVariables
dimensions, extraArgs, inPlace, sameDiff, scalarValue
Constructor and Description |
---|
Repeat(INDArray[] inputs,
INDArray[] outputs,
int axis) |
Repeat(INDArray[] inputs,
INDArray[] outputs,
List<Double> tArguments,
List<Integer> iArguments,
int axis) |
Repeat(int axis) |
Repeat(SameDiff sameDiff,
SDVariable[] args,
boolean inPlace,
int axis) |
Repeat(SameDiff sameDiff,
SDVariable[] args,
int axis) |
Modifier and Type | Method and Description |
---|---|
List<SDVariable> |
doDiff(List<SDVariable> i_v)
The actual implementation for automatic differentiation.
|
void |
initFromOnnx(OnnxProto3.NodeProto node,
SameDiff initWith,
Map<String,OnnxProto3.AttributeProto> attributesForNode,
OnnxProto3.GraphProto graph)
Iniitialize the function from the given
OnnxProto3.NodeProto |
void |
initFromTensorFlow(NodeDef nodeDef,
SameDiff initWith,
Map<String,AttrValue> attributesForNode,
GraphDef graph)
Initialize the function from the given
NodeDef |
Map<String,Map<String,PropertyMapping>> |
mappingsForFunction()
Returns the mappings for a given function (
for tensorflow and onnx import mapping properties
of this function).
|
String |
onnxName()
The opName of this function in onnx
|
String |
opName()
This method returns op opName as string
|
Map<String,Object> |
propertiesForFunction()
Returns the properties for a given function
|
void |
resolvePropertiesFromSameDiffBeforeExecution()
Resolve properties and arguments right before execution of
this operation.
|
String |
tensorflowName()
The opName of this function tensorflow
|
addIArgument, addInputArgument, addOutputArgument, addTArgument, asProperties, assertValidForExecution, builder, calculateOutputShape, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getTArgument, iArgs, inputArguments, numIArguments, numInputArguments, numOutputArguments, numTArguments, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, populateInputsAndOutputsFromSameDiff, removeIArgument, removeInputArgument, removeOutputArgument, removeTArgument, sameDiffBuilder, setInputArgument, setOutputArgument, tArgs, toString, updateInputsFromSameDiff
arg, args, attributeAdaptersForFunction, configFieldName, diff, dup, equals, f, getValue, hashCode, hasPlaceHolderInputs, isConfigProperties, larg, onnxNames, rarg, setInstanceId, setValueFor, tensorflowNames
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
isInplaceCall
public Repeat(int axis)
public Repeat(SameDiff sameDiff, SDVariable[] args, int axis)
public Repeat(INDArray[] inputs, INDArray[] outputs, List<Double> tArguments, List<Integer> iArguments, int axis)
public Repeat(SameDiff sameDiff, SDVariable[] args, boolean inPlace, int axis)
public Map<String,Object> propertiesForFunction()
DifferentialFunction
propertiesForFunction
in class DifferentialFunction
public String opName()
DynamicCustomOp
opName
in interface CustomOp
opName
in class DynamicCustomOp
public Map<String,Map<String,PropertyMapping>> mappingsForFunction()
DifferentialFunction
mappingsForFunction
in class DifferentialFunction
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
DifferentialFunction
NodeDef
initFromTensorFlow
in class DynamicCustomOp
public void initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
DifferentialFunction
OnnxProto3.NodeProto
initFromOnnx
in class DynamicCustomOp
public void resolvePropertiesFromSameDiffBeforeExecution()
DifferentialFunction
resolvePropertiesFromSameDiffBeforeExecution
in class DifferentialFunction
public String onnxName()
DifferentialFunction
onnxName
in class DynamicCustomOp
public String tensorflowName()
DifferentialFunction
tensorflowName
in class DynamicCustomOp
public List<SDVariable> doDiff(List<SDVariable> i_v)
DifferentialFunction
doDiff
in class DynamicCustomOp
Copyright © 2018. All rights reserved.