- pylibcugraphops.pytorch.operators.agg_concat_n2n(feat: Union[Tensor, Tuple[Tensor]], graph: CSC, aggr: str = 'sum', edge_weight: Optional[Tensor] = None) Tensor #
PyTorch autograd function for simple aggregation using node features in an node-to-node reduction (n2n) while concatenating the original features of output at the end (agg_concat).
- feattorch.Tensor | Tuple[torch.Tensor]
The input node features. Shape:
(n_src_nodes, dim_in)if graph is non-bipartite. Shape:
(n_dst_nodes, dim_concat)if graph is bipartite.
The graph used for the operation.
- aggrstr, default=”sum”
Aggregation operation. Choose from
- edge_weightOptional[torch.Tensor], default=None
When passing additional edge weights, the aggregation is done in a weighted fashion. Note that for min/max the result after weighting features with those edge weights is returned. Edge weights are indexed in the same fashion as the indices in
The aggregation output. Shape:
(n_dst_nodes, 2 * dim_in).