Uses of Class
oracle.pgx.config.mllib.GraphWiseBaseConvLayerConfig
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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. -
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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 forGraphWiseBaseConvLayerConfig
.Methods in oracle.pgx.api.mllib that return GraphWiseBaseConvLayerConfig Modifier and Type Method Description GraphWiseBaseConvLayerConfig[]
EdgeWiseModel. getConvLayerConfigs()
Gets the configuration objects for the convolutional layersGraphWiseBaseConvLayerConfig[]
GraphWiseModel. getConvLayerConfigs()
Gets the configuration objects for the convolutional layersMethods 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 (SeeGraphWiseConvLayerConfig
andGraphWiseAttentionLayerConfig
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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 (SeeGraphWiseBaseConvLayerConfig
)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, GraphWiseValidationConfig validationConfig)
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, GraphWiseValidationConfig validationConfig)
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, GraphWiseValidationConfig validationConfig)
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, GraphWiseValidationConfig validationConfig)
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, GraphWiseValidationConfig validationConfig)
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, GraphWiseValidationConfig validationConfig)
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, GraphWiseValidationConfig validationConfig)
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