Package org.nd4j.linalg.api.ops.impl.transforms.custom

Class Dilation2D

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.DynamicCustomOp

org.nd4j.linalg.api.ops.impl.transforms.custom.Dilation2D

All Implemented Interfaces:

CustomOp

public class Dilation2D
extends DynamicCustomOp

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
protected boolean	isSameMode
protected int	r0
protected int	r1
protected int	r2
protected int	r3
protected int	s0
protected int	s1
protected int	s2
protected int	s3

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
Dilation2D()
Dilation2D(SameDiff sameDiff, SDVariable[] inputAndWeights, int[] strides, int[] rates, boolean isSameMode, boolean inPlace)
Dilation2D(SameDiff sameDiff, SDVariable df, SDVariable weights, int[] strides, int[] rates, boolean isSameMode)
Dilation2D(INDArray[] inputArrays, INDArray[] outputs)
Dilation2D(INDArray df, INDArray weights, int[] strides, int[] rates, boolean isSameMode)

Method Summary

Modifier and Type	Method	Description
protected void	addArgs()
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.
List<DataType>	calculateOutputDataTypes(List<DataType> inputDataTypes)	Calculate the data types for the output arrays.
void	initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)	Initialize the function from the given NodeDef
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
String	tensorflowName()	The opName of this function tensorflow

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

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

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

arg, arg, argNames, args, configFieldName, configureWithSameDiff, diff, dup, equals, getBooleanFromProperty, getDoubleValueFromProperty, getIntValueFromProperty, getLongValueFromProperty, getNumOutputs, 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

isSameMode

protected boolean isSameMode

r0

protected int r0

r1

protected int r1

r2

protected int r2

r3

protected int r3

s0

protected int s0

s1

protected int s1

s2

protected int s2

s3

protected int s3

Constructor Detail

Dilation2D

public Dilation2D()

Dilation2D

public Dilation2D(SameDiff sameDiff,
                  SDVariable df,
                  SDVariable weights,
                  int[] strides,
                  int[] rates,
                  boolean isSameMode)

Dilation2D

public Dilation2D(SameDiff sameDiff,
                  SDVariable[] inputAndWeights,
                  int[] strides,
                  int[] rates,
                  boolean isSameMode,
                  boolean inPlace)

Dilation2D

public Dilation2D(INDArray[] inputArrays,
                  INDArray[] outputs)

Dilation2D

public Dilation2D(INDArray df,
                  INDArray weights,
                  int[] strides,
                  int[] rates,
                  boolean isSameMode)

Method Detail

addArgs

protected void addArgs()

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

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 DynamicCustomOp

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:

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:

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