StellarGraph API¶

Core¶

Data¶

Generators¶

Layers and models¶

GraphSAGE¶

HinSAGE¶

Node2Vec¶

Attri2Vec¶

GCN¶

Cluster-GCN¶

RGCN¶

PPNP¶

APPNP¶

GAT¶

Watch Your Step¶

Knowledge Graph models¶

GCN Supervised Graph Classification¶

Deep Graph Convolutional Neural Network¶

Graph Convolution LSTM¶

Deep Graph Infomax¶

Link prediction¶

Ensembles¶

Calibration¶

Neo4j Connector¶

Loss functions¶

Utilities¶

Datasets¶

Random¶

stellargraph.random contains functions to control the randomness behaviour in StellarGraph.

stellargraph.random.set_seed(seed)[source]¶

Create a new global RandomState using the provided seed. If seed is None, StellarGraph’s global RandomState object simply wraps the global random state for each external module.

When trying to create a reproducible workflow using this function, please note that this seed only controls the randomness of the non-TensorFlow part of the library. Randomness within TensorFlow layers is controlled via TensorFlow’s own global random seed, which can be set using tensorflow.random.set_seed.

Parameters: seed (int, optional) – random seed