gammagl.models.GPRGNNModel

class GPRGNNModel(feature_dim, hidden_dim, num_class, drop_rate, K, Init, alpha, dprate, Gamma=None)[source]

Graph Convolutional Network proposed in “Adaptive Universal Generalized PageRank Graph Neural Network” paper.

Parameters:

  • feature_dim – input feature dim.

  • hidden_dim – hidden feature dim.

  • num_class – output feature dim.

  • drop_rate – drop rate for dropout layer.

  • K – K steps to propagate.

  • Init – initialization method.

  • alpha – help to initial the value of gamma.

  • dprate – special dropout for GPR-GNN (before starting GPR propagation) to dropout some nodes.

  • Gamma – Only used when Init == “WS”, self-defined initial value of gamma.

reset_parameters()[source]
forward(x, edge_index, edge_weight, num_nodes)[source]