def METHOD_NAME(net, testloader):
    """Validate the model on the test set."""
    criterion = torch.nn.CrossEntropyLoss()
    correct, loss = 0, 0.0
    with torch.no_grad():
        for images, labels in tqdm(testloader):
            outputs = net(images.to(DEVICE))
            labels = labels.to(DEVICE)
            loss += criterion(outputs, labels).item()
            correct += (torch.max(outputs.data, 1)[1] == labels).sum().item()
    accuracy = correct / len(testloader.dataset)
    return loss, accuracy