gammagl.models.HardGATModel

class HardGATModel(feature_dim, hidden_dim, num_class, heads, drop_rate, k, num_layers, name=None)

The graph hard attentional operator from the “Graph Representation Learning via Hard and Channel-Wise Attention Networks” paper.

Parameters:

• feature_dim (int) – input feature dimension.

• hidden_dim (int) – hidden dimension.

• num_class (int) – number of classes.

• heads (int) – number of attention heads.

• drop_rate (float) – dropout rate.

• k (int) – number of neighbors to attention.

• name (str, optional) – model name.

forward(x, edge_index, num_nodes)