org.nd4j.linalg.api.ops.impl.layers.convolution

Class Conv3DDerivative

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.DynamicCustomOp

org.nd4j.linalg.api.ops.impl.layers.convolution.Conv3D

org.nd4j.linalg.api.ops.impl.layers.convolution.Conv3DDerivative

All Implemented Interfaces:

CustomOp

public class Conv3DDerivative
extends Conv3D

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.impl.layers.convolution.Conv3D

config

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

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

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

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

Constructor Summary

Constructors

Constructor and Description
Conv3DDerivative()
Conv3DDerivative(SameDiff sameDiff, SDVariable[] inputFunctions, Conv3DConfig conv3DConfig)

Method Summary

Modifier and Type	Method and Description
List<DataType>	calculateOutputDataTypes(List<DataType> inputDataTypes) Calculate the data types for the output arrays.
List<SDVariable>	doDiff(List<SDVariable> f1) The actual implementation for automatic differentiation.
int	getNumOutputs()
String	onnxName() The opName of this function in onnx
String[]	onnxNames() The opName of this function in onnx
String	opName() This method returns op opName as string
String	tensorflowName() The opName of this function tensorflow
String[]	tensorflowNames() The opName of this function tensorflow

Methods inherited from class org.nd4j.linalg.api.ops.impl.layers.convolution.Conv3D

attributeAdaptersForFunction, configFieldName, getValue, iArgs, initFromTensorFlow, isConfigProperties, mappingsForFunction, propertiesForFunction

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

addBArgument, addDArgument, addIArgument, addIArgument, addInputArgument, addOutputArgument, addTArgument, assertValidForExecution, bArgs, builder, calculateOutputShape, calculateOutputShape, clearArrays, dArgs, getBArgument, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getTArgument, initFromOnnx, inputArguments, numBArguments, numDArguments, numIArguments, numInputArguments, numOutputArguments, numTArguments, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, removeIArgument, removeInputArgument, removeOutputArgument, removeTArgument, setInputArgument, setInputArguments, setOutputArgument, tArgs, toString, wrapFilterNull, wrapOrNull, wrapOrNull

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

arg, arg, argNames, args, diff, dup, equals, hashCode, larg, outputs, outputVariable, outputVariablesNames, rarg, replaceArg, setInstanceId, setPropertiesForFunction, setValueFor

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

Conv3DDerivative

public Conv3DDerivative()

Conv3DDerivative

public Conv3DDerivative(SameDiff sameDiff,
                        SDVariable[] inputFunctions,
                        Conv3DConfig conv3DConfig)

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 Conv3D

Returns:

tensorflowName

public String tensorflowName()

Description copied from class: DifferentialFunction

The opName of this function tensorflow

Overrides:

tensorflowName in class Conv3D

Returns:

tensorflowNames

public String[] tensorflowNames()

Description copied from class: DifferentialFunction

The opName of this function tensorflow

Overrides:

tensorflowNames in class DifferentialFunction

Returns:

onnxName

public String onnxName()

Description copied from class: DifferentialFunction

The opName of this function in onnx

Overrides:

onnxName in class Conv3D

Returns:

onnxNames

public String[] onnxNames()

Description copied from class: DifferentialFunction

The opName of this function in onnx

Overrides:

onnxNames in class DifferentialFunction

Returns:

doDiff

public List<SDVariable> doDiff(List<SDVariable> f1)

Description copied from class: DifferentialFunction

The actual implementation for automatic differentiation.

Overrides:

doDiff in class Conv3D

Returns:

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 Conv3D

Parameters:

inputDataTypes - The data types of the inputs

Returns:

The data types of the outputs