Hi there,

I am quite new to PyTorch (and geometric deep learning) and am trying to use the PyTorch geometric package to implement the ‘Label propagation’ algorithm for node classification.

**Question:** I am struggling to understand the documentation and don’t quite know how to implement it in code. Would someone be able to help me?

**Context**: The class is called `LabelPropagation`

and is listed in the readthedocs.io page.

**Attempt:** Should the ‘main’ portion of the implementation look like:

```
class LabelPropagation(torch.nn.Module):
def __init__(self, num_layers, alpha):
super(LabelPropagation, self).__init__()
self.num_layers = num_layers
self.alpha = alpha
def forward(self, x, edge_index):
# I don't really know what to put here
return x
```

Any help would be greatly appreciated as I am still learning how to understand and interpret documentation.