b6a7c304c68fe4a1300970459a3807ee7bce6c87,examples/cora.py,,,#,55

Before Change

    return pred.eq(data.target[mask]).sum().item() / mask.size(0)


acc = []
for run in range(1, 101):
    model.conv1.reset_parameters()
    model.conv2.reset_parameters()

    for _ in range(200):
        train()

    acc.append(test(test_mask))
    print("Run: {:03d}, Test: {:.4f}".format(run, acc[-1]))

mean = torch.tensor(acc).mean().item()
std = torch.tensor(acc).std().item()
print("Mean: {:.4f}, Stddev: {:.4f}".format(mean, std))

After Change

for epoch in range(1, 101):
    train()
    log = "Epoch: {:03d}, Train: {:.4f}, Test: {:.4f}"
    print(log.format(epoch, *test()))

Instances