code: def learner(
      dls: List[Union[DataLoader, fastai.DataLoader]],
      model: nn.Module,
      cbs=None,
      loss_func=fastai.CrossEntropyLossFlat(axis=1),
      **kwargs,
  ):
      cbs = L(UnetCallback()) + L(cbs)
  
      learn = adapted_fastai_learner(
          dls=dls,
          model=model,
          cbs=cbs,
          loss_func=loss_func,
          **kwargs,
      )
  
      return learn
  
file_path: icevision/icevision/models/fastai/unet/fastai.py
imports: from icevision.imports import *
  from icevision.engines.fastai import *
  from icevision.models.fastai.unet.prediction import convert_raw_predictions
label_desc: Use image node_id 1 for calling a global function with example usage: learner(dls, model, cbs, loss_func) and returns: learn