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

Class DeConv2DDerivative

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.DynamicCustomOp

org.nd4j.linalg.api.ops.impl.layers.convolution.DeConv2D

org.nd4j.linalg.api.ops.impl.layers.convolution.DeConv2DDerivative

All Implemented Interfaces:

CustomOp

public class DeConv2DDerivative
extends DeConv2D

DeConv2DDerivative operation

Nested Class Summary

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

DynamicCustomOp.DynamicCustomOpsBuilder, DynamicCustomOp.SameDiffBuilder

Field Summary

Fields inherited from class org.nd4j.linalg.api.ops.impl.layers.convolution.DeConv2D

config

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

inplaceCall, outputVariables

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

dimensions, extraArgs, inPlace, sameDiff, scalarValue

Constructor Summary

Constructors

Constructor and Description
DeConv2DDerivative()
DeConv2DDerivative(SameDiff sameDiff, SDVariable[] inputs, INDArray[] inputArrays, INDArray[] outputs, DeConv2DConfig config)

Method Summary

Modifier and Type	Method and Description
List<SDVariable>	doDiff(List<SDVariable> f1) The actual implementation for automatic differentiation.
String	onnxName() The opName of this function in onnx
String	opName() This method returns op opName as string
String	tensorflowName() The opName of this function tensorflow

Methods inherited from class org.nd4j.linalg.api.ops.impl.layers.convolution.DeConv2D

configFieldName, getValue, initFromOnnx, initFromTensorFlow, isConfigProperties, mappingsForFunction, propertiesForFunction, setValueFor

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

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

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

arg, args, attributeAdaptersForFunction, diff, dup, equals, f, hashCode, hasPlaceHolderInputs, larg, onnxNames, rarg, resolvePropertiesFromSameDiffBeforeExecution, 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

Constructor Detail

DeConv2DDerivative

public DeConv2DDerivative()

DeConv2DDerivative

public DeConv2DDerivative(SameDiff sameDiff,
                          SDVariable[] inputs,
                          INDArray[] inputArrays,
                          INDArray[] outputs,
                          DeConv2DConfig config)

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 DeConv2D

Returns:

onnxName

public String onnxName()

Description copied from class: DifferentialFunction

The opName of this function in onnx

Overrides:

onnxName in class DeConv2D

Returns:

tensorflowName

public String tensorflowName()

Description copied from class: DifferentialFunction

The opName of this function tensorflow

Overrides:

tensorflowName in class DeConv2D

Returns:

doDiff

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

Description copied from class: DifferentialFunction

The actual implementation for automatic differentiation.

Overrides:

doDiff in class DeConv2D

Returns: