global_mean_pool(x: Tensor, batch: Optional[Tensor], size: Optional[int] = None) Tensor[source]

Returns batch-wise graph-level-outputs by averaging node features across the node dimension, so that for a single graph \(\mathcal{G}_i\) its output is computed by

\[\mathbf{r}_i = \frac{1}{N_i} \sum_{n=1}^{N_i} \mathbf{x}_n.\]

Functional method of the MeanAggregation module.

  • x (torch.Tensor) – Node feature matrix \(\mathbf{X} \in \mathbb{R}^{(N_1 + \ldots + N_B) \times F}\).

  • batch (torch.Tensor, optional) – The batch vector \(\mathbf{b} \in {\{ 0, \ldots, B-1\}}^N\), which assigns each node to a specific example.

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