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

Packages that use GraphWiseConvLayerConfig

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 GraphWiseConvLayerConfig in oracle.pgx.api.mllib

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

Modifier and Type	Method and Description
GraphWiseConvLayerConfig	GraphWiseConvLayerConfigBuilder.build() Build the configuration
GraphWiseConvLayerConfig[]	EdgeWiseModel.getConvLayerConfigs() Gets the configuration objects for the convolutional layers
GraphWiseConvLayerConfig[]	GraphWiseModel.getConvLayerConfigs() Gets the configuration objects for the convolutional layers

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

Modifier and Type	Method and Description
Self	WiseModelBuilder.setConvLayerConfigs(GraphWiseConvLayerConfig... layerConfigs) Set the convolutional layer configurations (See GraphWiseConvLayerConfig).

Uses of GraphWiseConvLayerConfig in oracle.pgx.config.mllib

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

Modifier and Type	Field and Description
static GraphWiseConvLayerConfig[]	GraphWiseBaseModelConfig.DEFAULT_CONV_LAYER_CONFIGS two default initialized layer configs (See GraphWiseConvLayerConfig)

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

Modifier and Type	Method and Description
GraphWiseConvLayerConfig[]	GraphWiseBaseModelConfig.getConvLayerConfigs()

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

Modifier and Type	Method and Description
void	GraphWiseBaseModelConfig.setConvLayerConfigs(GraphWiseConvLayerConfig... convLayerConfigs)

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

Constructor and Description
EdgeWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, 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, java.util.List<java.util.Set<java.lang.String>> targetEdgeLabelSets, GraphWiseBaseModelConfig.Backend backend, java.lang.Integer edgeEmbeddingDim, EdgeWiseModelConfig.EdgeWiseConvModelVariant variant, EdgeCombinationMethod edgeCombinationMethod)
GraphWiseBaseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, 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, GraphWiseBaseModelConfig.Backend backend)
GraphWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, 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, java.util.List<java.util.Set<java.lang.String>> targetVertexLabelSets, GraphWiseBaseModelConfig.Backend backend, GraphWiseModelConfig.GraphConvModelVariant variant)
SupervisedEdgeWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, int embeddingDim, java.lang.Integer edgeEmbeddingDim, java.lang.Integer seed, GraphWiseConvLayerConfig[] convLayerConfigs, boolean standardize, boolean shuffle, java.util.List<java.lang.String> vertexInputPropertyNames, java.util.List<java.lang.String> edgeInputPropertyNames, java.util.List<java.util.Set<java.lang.String>> targetEdgeLabelSets, boolean fitted, double trainingLoss, int inputFeatureDim, int edgeInputFeatureDim, oracle.pgx.config.mllib.SupervisedEdgeWiseModelConfig.LossFunction lossFunction, LossFunction lossFunctionClass, BatchGenerator batchGenerator, GraphWisePredictionLayerConfig[] predictionLayerConfigs, boolean normalize, java.lang.String edgeTargetPropertyName, LabelMaps labelMaps, GraphWiseBaseModelConfig.Backend backend, EdgeCombinationMethod edgeCombinationMethod, EdgeWiseModelConfig.EdgeWiseConvModelVariant variant)
SupervisedGraphWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, 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, java.util.List<java.util.Set<java.lang.String>> targetVertexLabelSets, boolean fitted, double trainingLoss, int inputFeatureDim, int edgeInputFeatureDim, oracle.pgx.config.mllib.SupervisedGraphWiseModelConfig.LossFunction lossFunction, LossFunction lossFunctionClass, BatchGenerator batchGenerator, GraphWisePredictionLayerConfig[] predictionLayerConfigs, boolean normalize, java.lang.String vertexTargetPropertyName, LabelMaps labelMaps, GraphWiseBaseModelConfig.Backend backend, GraphWiseModelConfig.GraphConvModelVariant variant)
UnsupervisedGraphWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, 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, java.util.List<java.util.Set<java.lang.String>> targetVertexLabels, boolean fitted, double trainingLoss, int inputFeatureDim, int inputEdgeFeatureDim, UnsupervisedGraphWiseModelConfig.LossFunction lossFunction, GraphWiseDgiLayerConfig dgiLayerConfig, GraphWiseBaseModelConfig.Backend backend, GraphWiseModelConfig.GraphConvModelVariant variant)