TypeError Traceback (most recent call last)
in
3 dbunch = ImageDataBunch.from_name_re(
4 path, fnames, pat=r’(.+)_\d+.jpg$’, item_tfms=crop_func, bs=bs,
----> 5 batch_tfms=[*aug_transforms(size=224), Normalize.from_stats(*imagenet_stats)])
d:\codes\fastai_dev\fastai2\fastai2\vision\data.py in from_name_re(cls, path, fnames, pat, **kwargs)
57 def from_name_re(cls, path, fnames, pat, **kwargs):
58 “Create from name attrs in list of fnames
in path
s with re expression pat
.”
—> 59 return cls.from_name_func(path, fnames, RegexLabeller(pat), **kwargs)
60
61 @classmethod
d:\codes\fastai_dev\fastai2\fastai2\vision\data.py in from_name_func(cls, path, fnames, label_func, valid_pct, seed, **kwargs)
45 "Create from name attrs in list of fnames
in path
s with label_func
"
46 f = using_attr(label_func, ‘name’)
—> 47 return cls.from_path_func(path, fnames, f, valid_pct=valid_pct, seed=seed, **kwargs)
48
49 @classmethod
d:\codes\fastai_dev\fastai2\fastai2\vision\data.py in from_path_func(cls, path, fnames, label_func, valid_pct, seed, **kwargs)
38 splitter=RandomSplitter(valid_pct, seed=seed),
39 get_y=label_func)
—> 40 return cls.from_dblock(dblock, fnames, path=path, **kwargs)
41
42 @classmethod
d:\codes\fastai_dev\fastai2\fastai2\data\core.py in from_dblock(cls, dblock, source, path, type_tfms, item_tfms, batch_tfms, **kwargs)
122 @delegates(TfmdDL.init)
123 def from_dblock(cls, dblock, source, path=’.’, type_tfms=None, item_tfms=None, batch_tfms=None, **kwargs):
–> 124 return dblock.databunch(source, path=path, type_tfms=type_tfms, item_tfms=item_tfms, batch_tfms=batch_tfms, **kwargs)
125
126 _docs=dict(getitem=“Retrieve DataLoader
at i
(0
is training, 1
is validation)”,
d:\codes\fastai_dev\fastai2\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)
d:\codes\fastai_dev\fastai2\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):
d:\codes\fastai_dev\fastai2\fastai2\data\core.py in init(self, items, tfms, tls, n_inp, dl_type, **kwargs)
231 def init(self, items=None, tfms=None, tls=None, n_inp=None, dl_type=None, **kwargs):
232 super().init(dl_type=dl_type)
–> 233 self.tls = L(tls if tls else [TfmdList(items, t, **kwargs) for t in L(ifnone(tfms,[None]))])
234 self.n_inp = (1 if len(self.tls)==1 else len(self.tls)-1) if n_inp is None else n_inp
235
d:\codes\fastai_dev\fastai2\fastai2\data\core.py in (.0)
231 def init(self, items=None, tfms=None, tls=None, n_inp=None, dl_type=None, **kwargs):
232 super().init(dl_type=dl_type)
–> 233 self.tls = L(tls if tls else [TfmdList(items, t, **kwargs) for t in L(ifnone(tfms,[None]))])
234 self.n_inp = (1 if len(self.tls)==1 else len(self.tls)-1) if n_inp is None else n_inp
235
D:\conda3\lib\site-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
d:\codes\fastai_dev\fastai2\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)
d:\codes\fastai_dev\fastai2\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