If i am using this line of code dls = bears.dataloaders(path) then I am getting this error.
TypeError Traceback (most recent call last)
Input In [20], in <cell line: 1>()
----> 1 dls = bears.dataloaders(path)
File ~\anaconda3\envs\torch\lib\site-packages\fastai\data\block.py:158, in DataBlock.dataloaders(self, source, path, verbose, **kwargs)
152 def dataloaders(self,
153 source, # The data source
154 path:str='.', # Data source and default `Learner` path
155 verbose:bool=False, # Show verbose messages
156 **kwargs
157 ) -> DataLoaders:
--> 158 dsets = self.datasets(source, verbose=verbose)
159 kwargs = {**self.dls_kwargs, **kwargs, 'verbose': verbose}
160 return dsets.dataloaders(path=path, after_item=self.item_tfms, after_batch=self.batch_tfms, **kwargs)
File ~\anaconda3\envs\torch\lib\site-packages\fastai\data\block.py:150, in DataBlock.datasets(self, source, verbose)
148 splits = (self.splitter or RandomSplitter())(items)
149 pv(f"{len(splits)} datasets of sizes {','.join([str(len(s)) for s in splits])}", verbose)
--> 150 return Datasets(items, tfms=self._combine_type_tfms(), splits=splits, dl_type=self.dl_type, n_inp=self.n_inp, verbose=verbose)
File ~\anaconda3\envs\torch\lib\site-packages\fastai\data\core.py:454, in Datasets.__init__(self, items, tfms, tls, n_inp, dl_type, **kwargs)
445 def __init__(self,
446 items:list=None, # List of items to create `Datasets`
447 tfms:list|Pipeline=None, # List of `Transform`(s) or `Pipeline` to apply
(...)
451 **kwargs
452 ):
453 super().__init__(dl_type=dl_type)
--> 454 self.tls = L(tls if tls else [TfmdLists(items, t, **kwargs) for t in L(ifnone(tfms,[None]))])
455 self.n_inp = ifnone(n_inp, max(1, len(self.tls)-1))
File ~\anaconda3\envs\torch\lib\site-packages\fastai\data\core.py:454, in <listcomp>(.0)
445 def __init__(self,
446 items:list=None, # List of items to create `Datasets`
447 tfms:list|Pipeline=None, # List of `Transform`(s) or `Pipeline` to apply
(...)
451 **kwargs
452 ):
453 super().__init__(dl_type=dl_type)
--> 454 self.tls = L(tls if tls else [TfmdLists(items, t, **kwargs) for t in L(ifnone(tfms,[None]))])
455 self.n_inp = ifnone(n_inp, max(1, len(self.tls)-1))
File ~\anaconda3\envs\torch\lib\site-packages\fastcore\foundation.py:98, in _L_Meta.__call__(cls, x, *args, **kwargs)
96 def __call__(cls, x=None, *args, **kwargs):
97 if not args and not kwargs and x is not None and isinstance(x,cls): return x
---> 98 return super().__call__(x, *args, **kwargs)
File ~\anaconda3\envs\torch\lib\site-packages\fastai\data\core.py:368, in TfmdLists.__init__(self, items, tfms, use_list, do_setup, split_idx, train_setup, splits, types, verbose, dl_type)
366 if do_setup:
367 pv(f"Setting up {self.tfms}", verbose)
--> 368 self.setup(train_setup=train_setup)
File ~\anaconda3\envs\torch\lib\site-packages\fastai\data\core.py:397, in TfmdLists.setup(self, train_setup)
395 x = f(x)
396 self.types.append(type(x))
--> 397 types = L(t if is_listy(t) else [t] for t in self.types).concat().unique()
398 self.pretty_types = '\n'.join([f' - {t}' for t in types])
TypeError: 'NoneType' object is not iterable
