TypeError: setup() takes from 1 to 2 positional arguments but 3 were given

[muellerzr]

Seems to be an issue with a recent commit, when attempting to databunch COCO I receive the following stack trace:

path = untar_data(URLs.COCO_SAMPLE)
dblock = DataBlock(blocks=(ImageBlock, ImageBlock),
                   get_items=get_image_files,
                   splitter=RandomSplitter(0.1, seed=42))
dbunch = dblock.databunch(path, bs=22, item_tfms=[Resize(224)],
                       batch_tfms=[Normalize.from_stats(*imagenet_stats)])

Stack Trace:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-129-76a6dc7939cf> in <module>()
      1 dbunch = dblock.databunch(path, bs=22, item_tfms=[Resize(224)],
----> 2                        batch_tfms=[Normalize.from_stats(*imagenet_stats)])

6 frames
/usr/local/lib/python3.6/dist-packages/fastai2/data/block.py in databunch(self, source, path, type_tfms, item_tfms, batch_tfms, **kwargs)
     80 
     81     def databunch(self, source, path='.', type_tfms=None, item_tfms=None, batch_tfms=None, **kwargs):
---> 82         dsrc = self.datasource(source, type_tfms=type_tfms)
     83         item_tfms  = _merge_tfms(self.default_item_tfms,  item_tfms)
     84         batch_tfms = _merge_tfms(self.default_batch_tfms, batch_tfms)

/usr/local/lib/python3.6/dist-packages/fastai2/data/block.py in datasource(self, source, type_tfms)
     77         type_tfms = L([self.default_type_tfms, type_tfms, labellers]).map_zip(
     78             lambda tt,tfm,l: L(l) + _merge_tfms(tt, tfm))
---> 79         return DataSource(items, tfms=type_tfms, splits=splits, dl_type=self.dl_type, n_inp=self.n_inp)
     80 
     81     def databunch(self, source, path='.', type_tfms=None, item_tfms=None, batch_tfms=None, **kwargs):

/usr/local/lib/python3.6/dist-packages/fastai2/data/core.py in __init__(self, items, tfms, tls, n_inp, dl_type, **kwargs)
    227     def __init__(self, items=None, tfms=None, tls=None, n_inp=None, dl_type=None, **kwargs):
    228         super().__init__(dl_type=dl_type)
--> 229         self.tls = L(tls if tls else [TfmdList(items, t, **kwargs) for t in L(ifnone(tfms,[None]))])
    230         self.n_inp = (1 if len(self.tls)==1 else len(self.tls)-1) if n_inp is None else n_inp
    231 

/usr/local/lib/python3.6/dist-packages/fastai2/data/core.py in <listcomp>(.0)
    227     def __init__(self, items=None, tfms=None, tls=None, n_inp=None, dl_type=None, **kwargs):
    228         super().__init__(dl_type=dl_type)
--> 229         self.tls = L(tls if tls else [TfmdList(items, t, **kwargs) for t in L(ifnone(tfms,[None]))])
    230         self.n_inp = (1 if len(self.tls)==1 else len(self.tls)-1) if n_inp is None else n_inp
    231 

/usr/local/lib/python3.6/dist-packages/fastcore/foundation.py in __call__(cls, x, *args, **kwargs)
     39             return x
     40 
---> 41         res = super().__call__(*((x,) + args), **kwargs)
     42         res._newchk = 0
     43         return res

/usr/local/lib/python3.6/dist-packages/fastai2/data/core.py in __init__(self, items, tfms, use_list, do_setup, as_item, split_idx, train_setup, splits, types)
    173         self.tfms = Pipeline(tfms, as_item=as_item, split_idx=split_idx)
    174         self.types = types
--> 175         if do_setup: self.setup(train_setup=train_setup)
    176 
    177     def _new(self, items, **kwargs): return super()._new(items, tfms=self.tfms, do_setup=False, types=self.types, **kwargs)

/usr/local/lib/python3.6/dist-packages/fastai2/data/core.py in setup(self, train_setup)
    186 
    187     def setup(self, train_setup=True):
--> 188         self.tfms.setup(self, train_setup)
    189         if len(self) != 0:
    190             x,self.types = super().__getitem__(0),[]

TypeError: setup() takes from 1 to 2 positional arguments but 3 were given

[sgugger]

I think you have a conflict between latest fastcore and not latest fastai2. This should be fixed now (please reopen if it is not).