(encoder_model, data)
| 112 | |
| 113 | |
| 114 | def test(encoder_model, data): |
| 115 | encoder_model.eval() |
| 116 | h1, h2, _, _, _, _ = encoder_model(data.x, data.edge_index) |
| 117 | z = torch.cat([h1, h2], dim=1) |
| 118 | split = get_split(num_samples=z.size()[0], train_ratio=0.1, test_ratio=0.8) |
| 119 | result = LREvaluator()(z, data.y, split) |
| 120 | return result |
| 121 | |
| 122 | |
| 123 | def main(): |
no test coverage detected