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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:

def create_from_ll(cls, lls:LabelLists, bs:int=64, val_bs:int=None, ds_tfms:Optional[TfmList]=None,
                num_workers:int=defaults.cpus, dl_tfms:Optional[Collection[Callable]]=None, device:torch.device=None,
                test:Optional[PathOrStr]=None, collate_fn:Callable=data_collate, size:int=None, no_check:bool=False,
                resize_method:ResizeMethod=None, mult:int=None, padding_mode:str='reflection',
                mode:str='bilinear', tfm_y:bool=False)->'ImageDataBunch':
        "Create an `ImageDataBunch` from `LabelLists` `lls` with potential `ds_tfms`."
        lls = lls.transform(tfms=ds_tfms, size=size, resize_method=resize_method, mult=mult, padding_mode=padding_mode,
                            mode=mode, tfm_y=tfm_y)
        if test is not None: lls.add_test_folder(test)
        return lls.databunch(bs=bs, val_bs=val_bs, dl_tfms=dl_tfms, num_workers=num_workers, collate_fn=collate_fn,
                             device=device, no_check=no_check)