def METHOD_NAME():
    global model
    global device
    # Get the path where the deployed model can be found.
    model_filename = 'cifar10torch.pt'
    model_file_path = os.path.join(os.environ['AZUREML_MODEL_DIR'], model_filename)
    device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
    model = SimpleDLA()
    model.to(device)
    saved_state_dict = torch.load(model_file_path, map_location=device)
    cleaned_dict = OrderedDict()
    for key, value in saved_state_dict.items():
        if key.startswith("module"):
            first_dot = key.find(".")
            key = key[first_dot + 1:]
        cleaned_dict[key] = value
    model.load_state_dict(cleaned_dict)
    model.eval()