Uses of Class
oracle.pgx.config.mllib.GraphWiseDgiLayerConfig

Packages that use GraphWiseDgiLayerConfig

Package	Description
oracle.pgx.api.mllib	This package contains graph machine learning tools for use with PGX.
oracle.pgx.config.mllib	This package contains APIs to all graph machine learning features of PGX.

Uses of GraphWiseDgiLayerConfig in oracle.pgx.api.mllib

Methods in oracle.pgx.api.mllib that return GraphWiseDgiLayerConfig

Modifier and Type	Method	Description
GraphWiseDgiLayerConfig	GraphWiseDgiLayerConfigBuilder.build()	Build the configuration
GraphWiseDgiLayerConfig	UnsupervisedEdgeWiseModel.getDgiLayerConfigs()	Gets the configuration object for the dgi layer

Methods in oracle.pgx.api.mllib with parameters of type GraphWiseDgiLayerConfig

Modifier and Type	Method	Description
UnsupervisedEdgeWiseModelBuilder	UnsupervisedEdgeWiseModelBuilder.setDgiLayerConfig(GraphWiseDgiLayerConfig layerConfig)	Set the dgi layer configurations (See GraphWiseDgiLayerConfig.

Uses of GraphWiseDgiLayerConfig in oracle.pgx.config.mllib

Fields in oracle.pgx.config.mllib declared as GraphWiseDgiLayerConfig

Modifier and Type	Field	Description
static GraphWiseDgiLayerConfig	UnsupervisedEdgeWiseModelConfig.DEFAULT_DGI_LAYER_CONFIG	one default initialized config (See GraphWiseDgiLayerConfig)
static GraphWiseDgiLayerConfig	UnsupervisedGraphWiseModelConfig.DEFAULT_DGI_LAYER_CONFIG	one default initialized config (See GraphWisePredictionLayerConfig)

Methods in oracle.pgx.config.mllib that return GraphWiseDgiLayerConfig

Modifier and Type	Method	Description
GraphWiseDgiLayerConfig	UnsupervisedEdgeWiseModelConfig.getDgiLayerConfig()

Methods in oracle.pgx.config.mllib with parameters of type GraphWiseDgiLayerConfig

Modifier and Type	Method	Description
void	UnsupervisedEdgeWiseModelConfig.setDgiLayerConfig(GraphWiseDgiLayerConfig dgiLayerConfig)

Constructors in oracle.pgx.config.mllib with parameters of type GraphWiseDgiLayerConfig

Constructor	Description
UnsupervisedEdgeWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, int embeddingDim, java.lang.Integer edgeEmbeddingDim, java.lang.Integer seed, GraphWiseBaseConvLayerConfig[] convLayerConfigs, boolean standardize, boolean shuffle, java.util.List<java.lang.String> vertexInputPropertyNames, java.util.List<java.lang.String> edgeInputPropertyNames, java.util.Map<java.lang.String,InputPropertyConfig> vertexInputPropertyConfigs, java.util.Map<java.lang.String,InputPropertyConfig> edgeInputPropertyConfigs, oracle.pgx.config.internal.categorymapping.CategoryMappingConfig categoryMappingConfig, java.util.List<java.util.Set<java.lang.String>> targetEdgeLabelSets, boolean fitted, double trainingLoss, int inputFeatureDim, int edgeInputFeatureDim, UnsupervisedEdgeWiseModelConfig.LossFunction lossFunction, boolean normalize, GraphWiseBaseModelConfig.Backend backend, EdgeCombinationMethod edgeCombinationMethod, EdgeWiseModelConfig.EdgeWiseConvModelVariant variant, GraphWiseDgiLayerConfig dgiLayerConfig, boolean enableAccelerator)
UnsupervisedGraphWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, int embeddingDim, java.lang.Integer seed, GraphWiseBaseConvLayerConfig[] convLayerConfigs, boolean standardize, boolean normalize, boolean shuffle, java.util.List<java.lang.String> vertexInputPropertyNames, java.util.List<java.lang.String> edgeInputPropertyNames, java.util.Map<java.lang.String,InputPropertyConfig> vertexInputPropertyConfigs, java.util.Map<java.lang.String,InputPropertyConfig> edgeInputPropertyConfigs, oracle.pgx.config.internal.categorymapping.CategoryMappingConfig categoryMappingConfig, java.util.List<java.util.Set<java.lang.String>> targetVertexLabels, boolean fitted, double trainingLoss, int inputFeatureDim, int inputEdgeFeatureDim, UnsupervisedGraphWiseModelConfig.LossFunction lossFunction, GraphWiseDgiLayerConfig dgiLayerConfig, GraphWiseEmbeddingConfig embeddingConfig, GraphWiseBaseModelConfig.Backend backend, GraphWiseModelConfig.GraphConvModelVariant variant, boolean enableAccelerator)