torch_geometric.nn.norm.GraphSizeNorm

class GraphSizeNorm[source]

Bases: Module

Applies Graph Size Normalization over each individual graph in a batch of node features as described in the “Benchmarking Graph Neural Networks” paper.

\[\mathbf{x}^{\prime}_i = \frac{\mathbf{x}_i}{\sqrt{|\mathcal{V}|}}\]
forward(x: Tensor, batch: Optional[Tensor] = None, batch_size: Optional[int] = None) → Tensor[source]

Forward pass.

Parameters:

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

  • batch (torch.Tensor, optional) – The batch vector \(\mathbf{b} \in {\{ 0, \ldots, B-1\}}^N\), which assigns each element to a specific example. (default: None)

  • batch_size (int, optional) – The number of examples \(B\). Automatically calculated if not given. (default: None)