db28ee240981457335c6fd9c38e542066df214cb,examples/cluster_gcn.py,,test,#,59

Before Change

    logits = model(data.x, data.edge_index)
    accs = []
    for _, mask in data("train_mask", "val_mask", "test_mask"):
        pred = logits[mask].max(1)[1]
        acc = pred.eq(data.y[mask]).sum().item() / mask.sum().item()
        accs.append(acc)
    return accs

After Change

@torch.no_grad()
def test():
    model.eval()
    total_correct, total_nodes = [0, 0, 0], [0, 0, 0]
    for data in test_loader:
        data = data.to(device)
        logits = model(data.x, data.edge_index)

Instances