oracle.pgx.config.mllib

Class GraphWiseModelConfig

java.lang.Object

oracle.pgx.config.mllib.GraphWiseModelConfig

Direct Known Subclasses:

SupervisedGraphWiseModelConfig, UnsupervisedGraphWiseModelConfig

public abstract class GraphWiseModelConfig
extends java.lang.Object

Abstract configuration class for GraphWise models

Since:

19.4

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	GraphWiseModelConfig.Backend

Field Summary

Fields

Modifier and Type	Field and Description
static GraphWiseModelConfig.Backend	DEFAULT_BACKEND LibTorch
static int	DEFAULT_BATCH_SIZE 128
static GraphWiseConvLayerConfig[]	DEFAULT_CONV_LAYER_CONFIGS two default initialized layer configs (See GraphWiseConvLayerConfig)
static int	DEFAULT_EMBEDDING_DIM 128
static double	DEFAULT_LEARNING_RATE 0.01
static int	DEFAULT_NUM_EPOCHS 3
static java.lang.Integer	DEFAULT_SEED null
static boolean	DEFAULT_SHUFFLE true
static boolean	DEFAULT_STANDARDIZE false
static java.util.EnumSet<PropertyType>	SUPPORTED_INPUT_TYPES BOOLEAN, FLOAT, DOUBLE

Constructor Summary

Constructors

Constructor and Description

GraphWiseModelConfig(int batchSize, int numEpochs, double learningRate, int embeddingDim, java.lang.Integer seed, GraphWiseConvLayerConfig[] convLayerConfigs, boolean standardize, boolean shuffle, java.util.List<java.lang.String> vertexInputPropertyNames, java.util.List<java.lang.String> edgeInputPropertyNames, boolean fitted, double trainingLoss, int vertexInputFeatureDim, int edgeInputFeatureDim, GraphWiseModelConfig.Backend backend)

Method Summary

Modifier and Type	Method and Description
GraphWiseModelConfig.Backend	getBackend()
int	getBatchSize()
GraphWiseConvLayerConfig[]	getConvLayerConfigs()
int	getEdgeInputFeatureDim()
java.util.List<java.lang.String>	getEdgeInputPropertyNames()
int	getEmbeddingDim()
int	getInputFeatureDim()
double	getLearningRate()
int	getNumEpochs()
java.lang.Integer	getSeed()
double	getTrainingLoss()
java.util.List<java.lang.String>	getVertexInputPropertyNames()
boolean	isFitted()
boolean	isShuffle()
boolean	isStandardize()
void	setBatchSize(int batchSize)
void	setConvLayerConfigs(GraphWiseConvLayerConfig... convLayerConfigs)
void	setEdgeInputFeatureDim(int edgeInputFeatureDim)
void	setEdgeInputPropertyNames(java.util.List<java.lang.String> edgeInputPropertyNames)
void	setEmbeddingDim(int embeddingDim)
void	setFitted(boolean fitted)
void	setInputFeatureDim(int vertexInputFeatureDim)
void	setLearningRate(double learningRate)
void	setNumEpochs(int numEpochs)
void	setSeed(int seed)
void	setShuffle(boolean shuffle)
void	setStandardize(boolean standardize)
void	setTrainingLoss(double trainingLoss)
void	setVertexInputPropertyNames(java.util.List<java.lang.String> vertexInputPropertyNames)

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

DEFAULT_BACKEND

public static final GraphWiseModelConfig.Backend DEFAULT_BACKEND

LibTorch

DEFAULT_BATCH_SIZE

public static final int DEFAULT_BATCH_SIZE

128

See Also:

Constant Field Values

DEFAULT_CONV_LAYER_CONFIGS

public static final GraphWiseConvLayerConfig[] DEFAULT_CONV_LAYER_CONFIGS

two default initialized layer configs (See GraphWiseConvLayerConfig)

DEFAULT_EMBEDDING_DIM

public static final int DEFAULT_EMBEDDING_DIM

128

See Also:

Constant Field Values

DEFAULT_LEARNING_RATE

public static final double DEFAULT_LEARNING_RATE

0.01

See Also:

Constant Field Values

DEFAULT_NUM_EPOCHS

public static final int DEFAULT_NUM_EPOCHS

3

See Also:

Constant Field Values

DEFAULT_SEED

public static final java.lang.Integer DEFAULT_SEED

null

DEFAULT_SHUFFLE

public static final boolean DEFAULT_SHUFFLE

true

See Also:

Constant Field Values

DEFAULT_STANDARDIZE

public static final boolean DEFAULT_STANDARDIZE

false

See Also:

Constant Field Values

SUPPORTED_INPUT_TYPES

public static final java.util.EnumSet<PropertyType> SUPPORTED_INPUT_TYPES

BOOLEAN, FLOAT, DOUBLE

Constructor Detail

GraphWiseModelConfig

public GraphWiseModelConfig(int batchSize,
                            int numEpochs,
                            double learningRate,
                            int embeddingDim,
                            java.lang.Integer seed,
                            GraphWiseConvLayerConfig[] convLayerConfigs,
                            boolean standardize,
                            boolean shuffle,
                            java.util.List<java.lang.String> vertexInputPropertyNames,
                            java.util.List<java.lang.String> edgeInputPropertyNames,
                            boolean fitted,
                            double trainingLoss,
                            int vertexInputFeatureDim,
                            int edgeInputFeatureDim,
                            GraphWiseModelConfig.Backend backend)

Method Detail

getBackend

public GraphWiseModelConfig.Backend getBackend()

getBatchSize

public int getBatchSize()

getConvLayerConfigs

public GraphWiseConvLayerConfig[] getConvLayerConfigs()

getEdgeInputFeatureDim

public int getEdgeInputFeatureDim()

getEdgeInputPropertyNames

public java.util.List<java.lang.String> getEdgeInputPropertyNames()

getEmbeddingDim

public int getEmbeddingDim()

getInputFeatureDim

public int getInputFeatureDim()

getLearningRate

public double getLearningRate()

getNumEpochs

public int getNumEpochs()

getSeed

public java.lang.Integer getSeed()

getTrainingLoss

public double getTrainingLoss()

getVertexInputPropertyNames

public java.util.List<java.lang.String> getVertexInputPropertyNames()

isFitted

public boolean isFitted()

isShuffle

public boolean isShuffle()

isStandardize

public boolean isStandardize()

setBatchSize

public void setBatchSize(int batchSize)

setConvLayerConfigs

public void setConvLayerConfigs(GraphWiseConvLayerConfig... convLayerConfigs)

setEdgeInputFeatureDim

public void setEdgeInputFeatureDim(int edgeInputFeatureDim)

setEdgeInputPropertyNames

public void setEdgeInputPropertyNames(java.util.List<java.lang.String> edgeInputPropertyNames)

setEmbeddingDim

public void setEmbeddingDim(int embeddingDim)

setFitted

public void setFitted(boolean fitted)

setInputFeatureDim

public void setInputFeatureDim(int vertexInputFeatureDim)

setLearningRate

public void setLearningRate(double learningRate)

setNumEpochs

public void setNumEpochs(int numEpochs)

setSeed

public void setSeed(int seed)

setShuffle

public void setShuffle(boolean shuffle)

setStandardize

public void setStandardize(boolean standardize)

setTrainingLoss

public void setTrainingLoss(double trainingLoss)

setVertexInputPropertyNames

public void setVertexInputPropertyNames(java.util.List<java.lang.String> vertexInputPropertyNames)