fairnr_cli/render.py [26:72]:
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    assert args.path is not None, '--path required for generation!'

    if args.results_path is not None:
        os.makedirs(args.results_path, exist_ok=True)
        output_path = os.path.join(args.results_path, 'generate-{}.txt'.format(args.gen_subset))
        with open(output_path, 'w', buffering=1) as h:
            return _main(args, h)
    else:
        return _main(args, sys.stdout)


def _main(args, output_file):
    logging.basicConfig(
        format='%(asctime)s | %(levelname)s | %(name)s | %(message)s',
        datefmt='%Y-%m-%d %H:%M:%S',
        level=logging.INFO,
        stream=output_file,
    )
    logger = logging.getLogger('fairnr_cli.render')

    utils.import_user_module(args)

    if args.max_tokens is None and args.max_sentences is None:
        args.max_tokens = 12000
    logger.info(args)

    use_cuda = torch.cuda.is_available() and not args.cpu

    # Load dataset splits
    task = tasks.setup_task(args)
    task.load_dataset(args.gen_subset)


    # Load ensemble
    logger.info('loading model(s) from {}'.format(args.path))
    models, _model_args = checkpoint_utils.load_model_ensemble(
        args.path.split(os.pathsep),
        arg_overrides=eval(args.model_overrides),
        task=task,
    )

    # Optimize ensemble for generation
    for model in models:
        if args.fp16:
            model.half()
        if use_cuda:
            model.cuda()
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fairnr_cli/render_multigpu.py [27:73]:
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    assert args.path is not None, '--path required for generation!'

    if args.results_path is not None:
        os.makedirs(args.results_path, exist_ok=True)
        output_path = os.path.join(args.results_path, 'generate-{}.txt'.format(args.gen_subset))
        with open(output_path, 'w', buffering=1) as h:
            return _main(args, h)
    else:
        return _main(args, sys.stdout)


def _main(args, output_file):
    logging.basicConfig(
        format='%(asctime)s | %(levelname)s | %(name)s | %(message)s',
        datefmt='%Y-%m-%d %H:%M:%S',
        level=logging.INFO,
        stream=output_file,
    )
    logger = logging.getLogger('fairnr_cli.render')

    utils.import_user_module(args)

    if args.max_tokens is None and args.max_sentences is None:
        args.max_tokens = 12000
    logger.info(args)

    use_cuda = torch.cuda.is_available() and not args.cpu

    # Load dataset splits
    task = tasks.setup_task(args)
    task.load_dataset(args.gen_subset)


    # Load ensemble
    logger.info('loading model(s) from {}'.format(args.path))
    models, _model_args = checkpoint_utils.load_model_ensemble(
        args.path.split(os.pathsep),
        arg_overrides=eval(args.model_overrides),
        task=task,
    )

    # Optimize ensemble for generation
    for model in models:
        if args.fp16:
            model.half()
        if use_cuda:
            model.cuda()
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