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

Packages that use GraphWiseBaseConvLayerConfig

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 GraphWiseBaseConvLayerConfig in oracle.pgx.api.mllib

Classes in oracle.pgx.api.mllib with type parameters of type GraphWiseBaseConvLayerConfig

Modifier and Type	Class	Description
class	GraphWiseBaseConvLayerConfigBuilder<Config extends GraphWiseBaseConvLayerConfig,Self extends GraphWiseBaseConvLayerConfigBuilder>	Builder for GraphWiseBaseConvLayerConfig.

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

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

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

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

Uses of GraphWiseBaseConvLayerConfig in oracle.pgx.config.mllib

Subclasses of GraphWiseBaseConvLayerConfig in oracle.pgx.config.mllib

Modifier and Type	Class	Description
class	GraphWiseAttentionLayerConfig	Configuration class for GraphWise attention layers.
class	GraphWiseConvLayerConfig	Configuration class for GraphWise convolutional layers.

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

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

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

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

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

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

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

Constructor	Description
EdgeWiseModelConfig(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, 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, boolean enableAccelerator)
GraphWiseBaseModelConfig(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, boolean fitted, double trainingLoss, int vertexInputFeatureDim, int edgeInputFeatureDim, GraphWiseBaseModelConfig.Backend backend, boolean enableAccelerator)
GraphWiseModelConfig(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, boolean fitted, double trainingLoss, int vertexInputFeatureDim, int edgeInputFeatureDim, java.util.List<java.util.Set<java.lang.String>> targetVertexLabelSets, GraphWiseBaseModelConfig.Backend backend, GraphWiseModelConfig.GraphConvModelVariant variant, boolean enableAccelerator)
SupervisedEdgeWiseModelConfig(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, 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, boolean enableAccelerator)
SupervisedGraphWiseModelConfig(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>> targetVertexLabelSets, boolean fitted, double trainingLoss, int inputFeatureDim, int edgeInputFeatureDim, oracle.pgx.config.mllib.SupervisedGraphWiseModelConfig.LossFunction lossFunction, LossFunction lossFunctionClass, BatchGenerator batchGenerator, GraphWisePredictionLayerConfig[] predictionLayerConfigs, java.lang.String vertexTargetPropertyName, LabelMaps labelMaps, GraphWiseBaseModelConfig.Backend backend, GraphWiseModelConfig.GraphConvModelVariant variant, boolean enableAccelerator)
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)