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

Class DeConv2DTF

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.DynamicCustomOp

org.nd4j.linalg.api.ops.impl.layers.convolution.DeConv2DTF

All Implemented Interfaces:

CustomOp

public class DeConv2DTF
extends DynamicCustomOp

DeConv2D operation, TF-wrapper

Nested Class Summary

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

DynamicCustomOp.DynamicCustomOpsBuilder, DynamicCustomOp.SameDiffBuilder

Field Summary

Fields

Modifier and Type	Field and Description
protected DeConv2DConfig	config

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

iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, tArguments

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

dimensions, extraArgs, inPlace, sameDiff, scalarValue

Constructor Summary

Constructors

Constructor and Description
DeConv2DTF(SameDiff sameDiff, SDVariable[] inputs, INDArray[] inputArrays, INDArray[] outputs, DeConv2DConfig config)

Method Summary

Modifier and Type	Method and Description
Map<String,Map<String,AttributeAdapter>>	attributeAdaptersForFunction() Returns the AttributeAdapter s for each of the possible ops for import (typically tensorflow and onnx) See AttributeAdapter for more information on what the adapter does.
String	configFieldName() Returns the name of the field to be used for looking up field names.
List<SDVariable>	doDiff(List<SDVariable> f1) The actual implementation for automatic differentiation.
Object	getValue(Field property) Get the value for a given property for this function
long[]	iArgs()
void	initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph) Initialize the function from the given NodeDef
boolean	isConfigProperties() Returns true if the fields for this class should be looked up from a configuration class.
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	setValueFor(Field target, Object value) Set the value for this function.
String	tensorflowName() The opName of this function tensorflow

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

addIArgument, addIArgument, addInputArgument, addOutputArgument, addTArgument, asProperties, assertValidForExecution, builder, calculateOutputShape, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getTArgument, initFromOnnx, inputArguments, numIArguments, numInputArguments, numOutputArguments, numTArguments, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, populateInputsAndOutputsFromSameDiff, removeIArgument, removeInputArgument, removeOutputArgument, removeTArgument, sameDiffBuilder, setInputArgument, setOutputArgument, tArgs, toString

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

arg, arg, argNames, args, diff, dup, equals, f, getNumOutputs, hashCode, hasPlaceHolderInputs, larg, onnxNames, outputVariable, outputVariablesNames, 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

Field Detail

config

protected DeConv2DConfig config

Constructor Detail

DeConv2DTF

public DeConv2DTF(SameDiff sameDiff,
                  SDVariable[] inputs,
                  INDArray[] inputArrays,
                  INDArray[] outputs,
                  DeConv2DConfig config)

Method Detail

iArgs

public long[] iArgs()

Specified by:

iArgs in interface CustomOp

Overrides:

iArgs in class DynamicCustomOp

propertiesForFunction

public Map<String,Object> propertiesForFunction()

Description copied from class: DifferentialFunction

Returns the properties for a given function

Overrides:

propertiesForFunction in class DifferentialFunction

Returns:

isConfigProperties

public boolean isConfigProperties()

Description copied from class: DifferentialFunction

Returns true if the fields for this class should be looked up from a configuration class.

Overrides:

isConfigProperties in class DifferentialFunction

Returns:

configFieldName

public String configFieldName()

Description copied from class: DifferentialFunction

Returns the name of the field to be used for looking up field names. This should be used in conjunction with DifferentialFunction.isConfigProperties() to facilitate mapping fields for model import.

Overrides:

configFieldName in class DifferentialFunction

Returns:

getValue

public Object getValue(Field property)

Description copied from class: DifferentialFunction

Get the value for a given property for this function

Overrides:

getValue in class DifferentialFunction

Parameters:

property - the property to get

Returns:

the value for the function if it exists

setValueFor

public void setValueFor(Field target,
                        Object value)

Description copied from class: DifferentialFunction

Set the value for this function. Note that if value is null an ND4JIllegalStateException will be thrown.

Overrides:

setValueFor in class DifferentialFunction

Parameters:

target - the target field

value - the value to set

mappingsForFunction

public Map<String,Map<String,PropertyMapping>> mappingsForFunction()

Description copied from class: DifferentialFunction

Returns the mappings for a given function ( for tensorflow and onnx import mapping properties of this function). The mapping is indexed by field name. If the function has no properties, this returned map will be empty. Note that some functions have multiple names. This function returns a map indexed by each alias it has for a given name. These names include both onnx and tensorflow names (which might be 1 or more)

Overrides:

mappingsForFunction in class DifferentialFunction

Returns:

attributeAdaptersForFunction

public Map<String,Map<String,AttributeAdapter>> attributeAdaptersForFunction()

Description copied from class: DifferentialFunction

Returns the AttributeAdapter s for each of the possible ops for import (typically tensorflow and onnx) See AttributeAdapter for more information on what the adapter does. Similar to DifferentialFunction.mappingsForFunction(), the returned map contains a AttributeAdapter for each field name when one is present. (It is optional for one to exist)_

Overrides:

attributeAdaptersForFunction in class DifferentialFunction

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 DynamicCustomOp

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:

onnxName

public String onnxName()

Description copied from class: DifferentialFunction

The opName of this function in onnx

Overrides:

onnxName 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:

doDiff

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

Description copied from class: DifferentialFunction

The actual implementation for automatic differentiation.

Overrides:

doDiff in class DynamicCustomOp

Returns: