easygraph.model.hypergraphs.dhcf module#

class easygraph.model.hypergraphs.dhcf.DHCF(*args: Any, **kwargs: Any)[source]#

Bases: Module

The DHCF model proposed in Dual Channel Hypergraph Collaborative Filtering paper (KDD 2020).

Note

The user and item embeddings and trainable parameters are initialized with xavier_uniform distribution.

Parameters:

  • num_users (int) – The Number of users.

  • num_items (int) – The Number of items.

  • emb_dim (int) – Embedding dimension.

  • num_layers (int) – The Number of layers. Defaults to 3.

  • drop_rate (float) – The dropout probability. Defaults to 0.5.

forward(hg_ui: Hypergraph, hg_iu: Hypergraph) → Tuple[torch.Tensor, torch.Tensor][source]#

The forward function.

Parameters:

  • hg_ui (eg.Hypergraph) – The hypergraph structure that users as vertices.

  • hg_iu (eg.Hypergraph) – The hypergraph structure that items as vertices.

reset_parameters()[source]#

Initialize learnable parameters.