public class UnsupervisedGraphWiseModelConfig extends GraphWiseModelConfig
UnsupervisedGraphWiseModel
. See UnsupervisedGraphWiseModel
for a description of the hyperparameters.Modifier and Type | Class and Description |
---|---|
static class |
UnsupervisedGraphWiseModelConfig.LossFunction |
GraphWiseModelConfig.Backend, GraphWiseModelConfig.GraphConvModelVariant
Modifier and Type | Field and Description |
---|---|
static GraphWiseDgiLayerConfig |
DEFAULT_DGI_LAYER_CONFIG
one default initialized config (See
GraphWisePredictionLayerConfig ) |
static UnsupervisedGraphWiseModelConfig.LossFunction |
DEFAULT_LOSS_FUNCTION
|
DEFAULT_BACKEND, DEFAULT_BATCH_SIZE, DEFAULT_CONV_LAYER_CONFIGS, DEFAULT_EMBEDDING_DIM, DEFAULT_LEARNING_RATE, DEFAULT_MODE, DEFAULT_NUM_EPOCHS, DEFAULT_SEED, DEFAULT_SHUFFLE, DEFAULT_STANDARDIZE, DEFAULT_WEIGHT_DECAY, SUPPORTED_INPUT_TYPES
Constructor and Description |
---|
UnsupervisedGraphWiseModelConfig() |
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, GraphWiseModelConfig.Backend backend, GraphWiseModelConfig.GraphConvModelVariant variant) |
UnsupervisedGraphWiseModelConfig(UnsupervisedGraphWiseModelConfig source) |
Modifier and Type | Method and Description |
---|---|
GraphWiseDgiLayerConfig |
getDgiLayerConfig() |
UnsupervisedGraphWiseModelConfig.LossFunction |
getLossFunction() |
void |
setDgiLayerConfig(GraphWiseDgiLayerConfig dgiLayerConfig) |
void |
setLossFunction(UnsupervisedGraphWiseModelConfig.LossFunction lossFunction) |
getBackend, getBatchSize, getConvLayerConfigs, getEdgeInputFeatureDim, getEdgeInputPropertyNames, getEmbeddingDim, getInputFeatureDim, getLearningRate, getNumEpochs, getSeed, getTargetVertexLabelSets, getTrainingLoss, getVariant, getVertexInputPropertyNames, getWeightDecay, isFitted, isShuffle, isStandardize, setBatchSize, setConvLayerConfigs, setEdgeInputFeatureDim, setEdgeInputPropertyNames, setEmbeddingDim, setFitted, setInputFeatureDim, setLearningRate, setNumEpochs, setSeed, setShuffle, setStandardize, setTargetVertexLabels, setTargetVertexLabelSets, setTrainingLoss, setVariant, setVertexInputPropertyNames, setWeightDecay
public static final GraphWiseDgiLayerConfig DEFAULT_DGI_LAYER_CONFIG
GraphWisePredictionLayerConfig
)public static final UnsupervisedGraphWiseModelConfig.LossFunction DEFAULT_LOSS_FUNCTION
public UnsupervisedGraphWiseModelConfig()
public 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, GraphWiseModelConfig.Backend backend, GraphWiseModelConfig.GraphConvModelVariant variant)
public UnsupervisedGraphWiseModelConfig(UnsupervisedGraphWiseModelConfig source)
public GraphWiseDgiLayerConfig getDgiLayerConfig()
public UnsupervisedGraphWiseModelConfig.LossFunction getLossFunction()
public final void setDgiLayerConfig(GraphWiseDgiLayerConfig dgiLayerConfig)
public final void setLossFunction(UnsupervisedGraphWiseModelConfig.LossFunction lossFunction)