def METHOD_NAME(loader):
    mse = []
    for data in loader:
        data = data.to(device)
        out = model(data.x, data.edge_index, data.edge_attr, data.batch)
        mse.append(F.mse_loss(out, data.y, reduction='none').cpu())
    return float(torch.cat(mse, dim=0).mean().sqrt())