code: def convert_dataloaders_to_fastai(
      dls: List[Union[DataLoader, fastai.DataLoader]], device=None
  ):
      fastai_dls = []
      for dl in dls:
          if isinstance(dl, DataLoader):
              fastai_dl = convert_dataloader_to_fastai(dl)
          elif isinstance(dl, fastai.DataLoader):
              fastai_dl = dl
          else:
              raise ValueError(f"dl type {type(dl)} not supported")
  
          fastai_dls.append(fastai_dl)
  
      device = device or fastai.default_device()
      fastai_dls = fastai.DataLoaders(*fastai_dls).to(device)
      return fastai_dls
  
imports: from icevision.imports import *
  from icevision.engines.fastai.imports import *
  from torch.utils.data import SequentialSampler, RandomSampler
  from torch.utils.data.dataloader import _InfiniteConstantSampler
label_desc: Use image node_id 2 for calling a global function with example usage: convert_dataloaders_to_fastai(dls, device) and returns: fastai_dls