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

Class Pooling3D

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.DynamicCustomOp

org.nd4j.linalg.api.ops.impl.layers.convolution.Pooling3D

All Implemented Interfaces:

CustomOp

Direct Known Subclasses:

AvgPooling3D, MaxPooling3D, Pooling3DDerivative

public abstract class Pooling3D
extends DynamicCustomOp

Pooling3D operation

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	Pooling3D.Pooling3DType

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

DynamicCustomOp.DynamicCustomOpsBuilder

Field Summary

Fields

Modifier and Type	Field	Description
protected Pooling3DConfig	config

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
Pooling3D(SameDiff sameDiff, SDVariable[] inputs, INDArray[] inputArrays, INDArray[] outputs, boolean inPlace, Pooling3DConfig pooling3DConfig, Pooling3D.Pooling3DType type)

Method Summary

Modifier and Type	Method	Description
protected void	addArgs()
List<DataType>	calculateOutputDataTypes(List<DataType> inputDataTypes)	Calculate the data types for the output arrays.
String	configFieldName()	Returns the name of the field to be used for looking up field names.
protected void	createConfigFromArgs(Pooling3D.Pooling3DType type)
List<SDVariable>	doDiff(List<SDVariable> f1)	The actual implementation for automatic differentiation.
protected Pooling3D.Pooling3DType	getDefaultType()
String	getPoolingPrefix()
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.
String	onnxName()	The opName of this function in onnx
Map<String,Object>	propertiesForFunction()	Returns the properties for a given function
void	setPropertiesForFunction(Map<String,Object> properties)
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, generateFake, generateFake, getBArgument, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getSArgument, getTArgument, getValue, initFromOnnx, inputArguments, mappingsForFunction, numBArguments, numDArguments, numIArguments, numInputArguments, numOutputArguments, numSArguments, numTArguments, opHash, opName, opNum, opType, outputArguments, outputVariables, 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, attributeAdaptersForFunction, configureWithSameDiff, diff, dup, equals, getBooleanFromProperty, getDoubleValueFromProperty, getIntValueFromProperty, getLongValueFromProperty, getNumOutputs, getStringFromProperty, hashCode, 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

config

protected Pooling3DConfig config

Constructor Detail

Pooling3D

public Pooling3D(SameDiff sameDiff,
                 SDVariable[] inputs,
                 INDArray[] inputArrays,
                 INDArray[] outputs,
                 boolean inPlace,
                 Pooling3DConfig pooling3DConfig,
                 Pooling3D.Pooling3DType type)

Method Detail

iArgs

public long[] iArgs()

Specified by:

iArgs in interface CustomOp

Overrides:

iArgs in class DynamicCustomOp

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:

propertiesForFunction

public Map<String,Object> propertiesForFunction()

Description copied from class: DifferentialFunction

Returns the properties for a given function

Overrides:

propertiesForFunction in class DynamicCustomOp

Returns:

getDefaultType

protected Pooling3D.Pooling3DType getDefaultType()

setPropertiesForFunction

public void setPropertiesForFunction(Map<String,Object> properties)

Overrides:

setPropertiesForFunction in class DynamicCustomOp

createConfigFromArgs

protected void createConfigFromArgs(Pooling3D.Pooling3DType type)

addArgs

protected void addArgs()

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:

getPoolingPrefix

public String getPoolingPrefix()

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

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