CCXN

CCXN class.

class topomodelx.nn.cell.ccxn.CCXN(in_channels_0, in_channels_1, in_channels_2, n_layers=2, att=False, **kwargs)

CCXN [1].

Parameters:

in_channels_0int

Dimension of input features on nodes.

in_channels_1int

Dimension of input features on edges.

in_channels_2int

Dimension of input features on faces.

n_layersint

Number of CCXN layers.

attbool

Whether to use attention.

**kwargsoptional

Additional arguments CCXNLayer.

References

[1]

Hajij, Istvan, Zamzmi. Cell complex neural networks. Topological data analysis and beyond workshop at NeurIPS 2020. https://arxiv.org/pdf/2010.00743.pdf

forward(x_0, x_1, adjacency_0, incidence_2_t)

Forward computation through layers.

Parameters:

x_0torch.Tensor, shape = (n_nodes, in_channels_0)

Input features on the nodes (0-cells).

x_1torch.Tensor, shape = (n_edges, in_channels_1)

Input features on the edges (1-cells).

adjacency_0torch.Tensor, shape = (n_nodes, n_nodes)

Adjacency matrix of rank 0 (up).

incidence_2_ttorch.Tensor, shape = (n_faces, n_edges)

Transpose of boundary matrix of rank 2.

Returns:

x_0torch.Tensor, shape = (n_nodes, in_channels_0)

Final hidden states of the nodes (0-cells).

x_1torch.Tensor, shape = (n_edges, in_channels_1)

Final hidden states the edges (1-cells).

x_2torch.Tensor, shape = (n_faces, in_channels_2)

Final hidden states of the faces (2-cells).