def METHOD_NAME():
    args = build_argparser().parse_args()
    if args.labels:
        with open(args.labels) as f:
            labels = [line.strip() for line in f]
    else:
        labels = None
    log.info('OpenVINO Runtime')
    log.info('\tbuild: {}'.format(get_version()))
    core = Core()
    decoder_target_device = 'CPU'
    if args.device != 'CPU':
        encoder_target_device = args.device
    else:
        encoder_target_device = decoder_target_device
    models = [IEModel(args.m_encoder, core, encoder_target_device, model_type='Action Recognition Encoder',
                      num_requests=1)]
    if args.architecture_type == 'en-de':
        if args.m_decoder is None:
            raise RuntimeError('No decoder for encoder-decoder model type (-m_de) provided')
        models.append(IEModel(args.m_decoder, core, decoder_target_device, model_type='Action Recognition Decoder', num_requests=2))
        seq_size = models[1].input_shape[1]
    elif args.architecture_type == 'en-mean':
        models.append(DummyDecoder(num_requests=2))
        seq_size = args.decoder_seq_size
    elif args.architecture_type == 'i3d-rgb':
        seq_size = models[0].input_shape[1]
    presenter = monitors.Presenter(args.utilization_monitors, 70)
    result_presenter = ResultRenderer(no_show=args.no_show, presenter=presenter, output=args.output, limit=args.output_limit, labels=labels,
                                      label_smoothing_window=args.label_smoothing)
    cap = open_images_capture(args.input, args.loop)
    run_pipeline(cap, args.architecture_type, models, result_presenter.render_frame, args.raw_output_message,
                 seq_size=seq_size, fps=cap.fps())
    for rep in presenter.reportMeans():
        log.info(rep)