Package org.nd4j.linalg.api.ops.impl.shape.tensorops

Class TensorArrayScatter

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.DynamicCustomOp

org.nd4j.linalg.api.ops.impl.shape.tensorops.BaseTensorOp

org.nd4j.linalg.api.ops.impl.shape.tensorops.TensorArrayScatter

All Implemented Interfaces:

CustomOp

public class TensorArrayScatter
extends BaseTensorOp

Nested Class Summary

Nested classes/interfaces inherited from class org.nd4j.linalg.api.ops.DynamicCustomOp

DynamicCustomOp.DynamicCustomOpsBuilder

Field Summary

Fields inherited from class org.nd4j.linalg.api.ops.DynamicCustomOp

axis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, sArguments, tArguments

Fields inherited from class org.nd4j.autodiff.functions.DifferentialFunction

dimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue

Constructor Summary

Constructors

Constructor	Description
TensorArrayScatter()
TensorArrayScatter(String name, SameDiff sameDiff, SDVariable[] args)
TensorArrayScatter(SameDiff sameDiff, SDVariable[] args)
TensorArrayScatter(SameDiff sd, SDVariable input, SDVariable indices, SDVariable scatter)
TensorArrayScatter(INDArray input, INDArray indices, INDArray scatter)

Method Summary

Modifier and Type	Method	Description
List<DataType>	calculateOutputDataTypes(List<DataType> inputDataType)	Calculate the data types for the output arrays.
void	initFromOnnx(Onnx.NodeProto node, SameDiff initWith, Map<String,Onnx.AttributeProto> attributesForNode, Onnx.GraphProto graph)	Iniitialize the function from the given Onnx.NodeProto
String	opName()	This method returns op opName as string
String[]	tensorflowNames()	The opName of this function tensorflow
String	toString()

Methods inherited from class org.nd4j.linalg.api.ops.impl.shape.tensorops.BaseTensorOp

calculateOutputShape, computeArrays, doDiff, getNumOutputs, initFromTensorFlow, onnxName, opType

Methods inherited from class org.nd4j.linalg.api.ops.DynamicCustomOp

addBArgument, addDArgument, addIArgument, addIArgument, addInputArgument, addOutputArgument, addOutputsToOp, addSArgument, addTArgument, assertValidForExecution, bArgs, builder, calculateOutputShape, clearArrays, configureFromArguments, dArgs, generateFake, generateFake, getBArgument, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getSArgument, getTArgument, getValue, iArgs, inputArguments, mappingsForFunction, numBArguments, numDArguments, numIArguments, numInputArguments, numOutputArguments, numSArguments, numTArguments, opHash, opNum, outputArguments, outputVariables, outputVariables, propertiesForFunction, removeIArgument, removeInputArgument, removeOutputArgument, removeSArgument, removeTArgument, sArgs, setInputArgument, setInputArguments, setOutputArgument, setPropertiesForFunction, setValueFor, tArgs, tensorflowName, wrapFilterNull, wrapOrNull, wrapOrNull

Methods inherited from class org.nd4j.autodiff.functions.DifferentialFunction

arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, configureWithSameDiff, diff, dup, equals, getBooleanFromProperty, getDoubleValueFromProperty, getIntValueFromProperty, getLongValueFromProperty, getStringFromProperty, hashCode, isConfigProperties, larg, onnxNames, outputs, outputVariable, outputVariablesNames, rarg, replaceArg, setInstanceId

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface org.nd4j.linalg.api.ops.CustomOp

isInplaceCall

Constructor Detail

TensorArrayScatter

public TensorArrayScatter(String name,
                          SameDiff sameDiff,
                          SDVariable[] args)

TensorArrayScatter

public TensorArrayScatter(SameDiff sameDiff,
                          SDVariable[] args)

TensorArrayScatter

public TensorArrayScatter()

TensorArrayScatter

public TensorArrayScatter(SameDiff sd,
                          SDVariable input,
                          SDVariable indices,
                          SDVariable scatter)

TensorArrayScatter

public TensorArrayScatter(INDArray input,
                          INDArray indices,
                          INDArray scatter)

Method Detail

tensorflowNames

public String[] tensorflowNames()

Description copied from class: DifferentialFunction

The opName of this function tensorflow

Overrides:

tensorflowNames in class DifferentialFunction

Returns:

toString

public String toString()

Overrides:

toString in class BaseTensorOp

opName

public String opName()

Description copied from class: DynamicCustomOp

This method returns op opName as string

Specified by:

opName in interface CustomOp

Overrides:

opName in class DynamicCustomOp

Returns:

initFromOnnx

public void initFromOnnx(Onnx.NodeProto node,
                         SameDiff initWith,
                         Map<String,Onnx.AttributeProto> attributesForNode,
                         Onnx.GraphProto graph)

Description copied from class: DifferentialFunction

Iniitialize the function from the given Onnx.NodeProto

Overrides:

initFromOnnx in class DynamicCustomOp

calculateOutputDataTypes

public List<DataType> calculateOutputDataTypes(List<DataType> inputDataType)

Description copied from class: DifferentialFunction

Calculate the data types for the output arrays. Though datatypes can also be inferred from 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.

Overrides:

calculateOutputDataTypes in class DifferentialFunction

Parameters:

inputDataType - The data types of the inputs

Returns:

The data types of the outputs