torch_geometric.nn.aggr.VariancePreservingAggregation

class VariancePreservingAggregation[source]

Bases: Aggregation

执行来自“GNN-VPA: 图神经网络的方差保持聚合策略”论文的方差保持聚合（VPA）。

\[\mathrm{vpa}(\mathcal{X}) = \frac{1}{\sqrt{|\mathcal{X}|}} \sum_{\mathbf{x}_i \in \mathcal{X}} \mathbf{x}_i\]
forward(x: Tensor, index: Optional[Tensor] = None, ptr: Optional[Tensor] = None, dim_size: Optional[int] = None, dim: int = -2) → Tensor[source]

前向传播。

Parameters:

  • x (torch.Tensor) – The source tensor.

  • index (torch.Tensor, optional) – The indices of elements for applying the aggregation. One of index or ptr must be defined. (default: None)

  • ptr (torch.Tensor, optional) – If given, computes the aggregation based on sorted inputs in CSR representation. One of index or ptr must be defined. (default: None)

  • dim_size (int, optional) – The size of the output tensor at dimension dim after aggregation. (default: None)

  • dim (int, optional) – The dimension in which to aggregate. (default: -2)

  • max_num_elements – (int, optional): The maximum number of elements within a single aggregation group. (default: None)

Return type:

Tensor