def METHOD_NAME(
    net: Net,
    testloader: torch.utils.data.DataLoader,
    device: torch.device,  # pylint: disable=no-member
) -> Tuple[float, float]:
    """Validate the network on the entire test set."""
    # Define loss and metrics
    criterion = nn.CrossEntropyLoss()
    correct, loss = 0, 0.0
    # Evaluate the network
    net.to(device)
    net.eval()
    with torch.no_grad():
        for data in testloader:
            images, labels = data[0].to(device), data[1].to(device)
            outputs = net(images)
            loss += criterion(outputs, labels).item()
            _, predicted = torch.max(outputs.data, 1)  # pylint: disable=no-member
            correct += (predicted == labels).sum().item()
    accuracy = correct / len(testloader.dataset)
    return loss, accuracy