def apply_default_prefetch(input_source_or_dataflow, trainer):
    """
    Apply a set of default rules to make a fast :class:`InputSource`.

    Args:
        input_source_or_dataflow(InputSource | DataFlow):
        trainer (Trainer):

    Returns:
        InputSource
    """
    if not isinstance(input_source_or_dataflow, InputSource):
        # to mimic same behavior of the old trainer interface
        if type(trainer) == SimpleTrainer:
            input = FeedInput(input_source_or_dataflow)
        else:
            logger.info("Automatically applying QueueInput on the DataFlow.")
            input = QueueInput(input_source_or_dataflow)
    else:
        input = input_source_or_dataflow
    if hasattr(trainer, 'devices'):
        towers = trainer.devices
        if len(towers) > 1:  # seem to only help on >1 GPUs
            assert not isinstance(trainer, SimpleTrainer)

            if isinstance(input, QueueInput):
                logger.info("Automatically applying StagingInput on the DataFlow.")
                input = StagingInput(input)
    return input

    Apply a set of default rules to make a fast :class:`InputSource`.

    Args:
        input_source_or_dataflow(InputSource | DataFlow):
        trainer (Trainer):

    Returns:
        InputSource
    
tensorpack/train/interface.py