Package org.nd4j.linalg.api.ops.impl.controlflow.compat

Class LoopCond

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.DynamicCustomOp

org.nd4j.linalg.api.ops.impl.controlflow.compat.BaseCompatOp

org.nd4j.linalg.api.ops.impl.controlflow.compat.LoopCond

All Implemented Interfaces:

CustomOp

public class LoopCond
extends BaseCompatOp

Nested Class Summary

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

DynamicCustomOp.DynamicCustomOpsBuilder

Field Summary

Fields

Modifier and Type	Field	Description
static String	OP_NAME

Fields inherited from class org.nd4j.linalg.api.ops.impl.controlflow.compat.BaseCompatOp

frameName

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
LoopCond()

Method Summary

Modifier and Type	Method	Description
List<DataType>	calculateOutputDataTypes(List<DataType> inputDataTypes)	Calculate the data types for the output arrays.
int	getNumOutputs()
void	initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)	Initialize the function from the given NodeDef
String	opName()	This method returns op opName as string
Op.Type	opType()	The type of the op
SDVariable[]	outputVariables()	Return the output variables for this differential function.
String	tensorflowName()	The opName of this function tensorflow

Methods inherited from class org.nd4j.linalg.api.ops.impl.controlflow.compat.BaseCompatOp

addSArgument, attributeAdaptersForFunction, calculateOutputShape, computeArrays, configureFromArguments, configureWithSameDiff, getFrameName, mappingsForFunction, propertiesForFunction, setFrameName, setPropertiesForFunction

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

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

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

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

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

Field Detail

OP_NAME

public static final String OP_NAME

See Also:

Constant Field Values

Constructor Detail

LoopCond

public LoopCond()

Method Detail

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:

outputVariables

public SDVariable[] outputVariables()

Description copied from class: DifferentialFunction

Return the output variables for this differential function. Note that this op *may* dynamically generate variable outputs.

Overrides:

outputVariables in class DynamicCustomOp

Returns:

tensorflowName

public String tensorflowName()

Description copied from class: DifferentialFunction

The opName of this function tensorflow

Overrides:

tensorflowName in class DynamicCustomOp

Returns:

opType

public Op.Type opType()

Description copied from class: DifferentialFunction

The type of the op

Overrides:

opType in class DynamicCustomOp

Returns:

initFromTensorFlow

public void initFromTensorFlow(NodeDef nodeDef,
                               SameDiff initWith,
                               Map<String,AttrValue> attributesForNode,
                               GraphDef graph)

Description copied from class: DifferentialFunction

Initialize the function from the given NodeDef

Overrides:

initFromTensorFlow in class BaseCompatOp

getNumOutputs

public int getNumOutputs()

Overrides:

getNumOutputs in class DifferentialFunction

calculateOutputDataTypes

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

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:

inputDataTypes - The data types of the inputs

Returns:

The data types of the outputs