(self, x, edge_index)
| 45 | return x[torch.randperm(x.size(0))], edge_index |
| 46 | |
| 47 | def forward(self, x, edge_index): |
| 48 | z = self.encoder(x, edge_index) |
| 49 | g = self.project(torch.sigmoid(z.mean(dim=0, keepdim=True))) |
| 50 | zn = self.encoder(*self.corruption(x, edge_index)) |
| 51 | return z, g, zn |
| 52 | |
| 53 | |
| 54 | def train(encoder_model, contrast_model, data, optimizer): |
nothing calls this directly
no test coverage detected