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 and 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 and 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 and 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 and 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 and 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 and Description
GraphWiseBaseConvLayerConfig[]	GraphWiseBaseModelConfig.getConvLayerConfigs()

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

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

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

Constructor and 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)
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)
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)
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)
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)
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)
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)