get_preds on Point-Based test_dl

[muellerzr]

Leaving this as a GitHub issue so it can be looked later (not a major priority) when the book is done :)

dl = learn.dls.test_dl(imgs[:10])
preds = learn.get_preds(dl=dl)

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-65-9a993e47d6c2> in <module>()
----> 1 preds = learn.get_preds(dl=dl)

12 frames
/usr/local/lib/python3.6/dist-packages/fastai2/learner.py in get_preds(self, ds_idx, dl, with_input, with_decoded, with_loss, act, **kwargs)
    319             self(_before_epoch)
    320             self._do_epoch_validate(dl=dl)
--> 321             self(_after_epoch)
    322             if act is None: act = getattr(self.loss_func, 'activation', noop)
    323             res = cb.all_tensors()

/usr/local/lib/python3.6/dist-packages/fastai2/learner.py in __call__(self, event_name)
    226     def ordered_cbs(self, cb_func:str): return [cb for cb in sort_by_run(self.cbs) if hasattr(cb, cb_func)]
    227 
--> 228     def __call__(self, event_name): L(event_name).map(self._call_one)
    229     def _call_one(self, event_name):
    230         assert hasattr(event, event_name)

/usr/local/lib/python3.6/dist-packages/fastcore/foundation.py in map(self, f, *args, **kwargs)
    360              else f.format if isinstance(f,str)
    361              else f.__getitem__)
--> 362         return self._new(map(g, self))
    363 
    364     def filter(self, f, negate=False, **kwargs):

/usr/local/lib/python3.6/dist-packages/fastcore/foundation.py in _new(self, items, *args, **kwargs)
    313     @property
    314     def _xtra(self): return None
--> 315     def _new(self, items, *args, **kwargs): return type(self)(items, *args, use_list=None, **kwargs)
    316     def __getitem__(self, idx): return self._get(idx) if is_indexer(idx) else L(self._get(idx), use_list=None)
    317     def copy(self): return self._new(self.items.copy())

/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/fastcore/foundation.py in __init__(self, items, use_list, match, *rest)
    304         if items is None: items = []
    305         if (use_list is not None) or not _is_array(items):
--> 306             items = list(items) if use_list else _listify(items)
    307         if match is not None:
    308             if is_coll(match): match = len(match)

/usr/local/lib/python3.6/dist-packages/fastcore/foundation.py in _listify(o)
    240     if isinstance(o, list): return o
    241     if isinstance(o, str) or _is_array(o): return [o]
--> 242     if is_iter(o): return list(o)
    243     return [o]
    244 

/usr/local/lib/python3.6/dist-packages/fastcore/foundation.py in __call__(self, *args, **kwargs)
    206             if isinstance(v,_Arg): kwargs[k] = args.pop(v.i)
    207         fargs = [args[x.i] if isinstance(x, _Arg) else x for x in self.pargs] + args[self.maxi+1:]
--> 208         return self.fn(*fargs, **kwargs)
    209 
    210 # Cell

/usr/local/lib/python3.6/dist-packages/fastai2/learner.py in _call_one(self, event_name)
    229     def _call_one(self, event_name):
    230         assert hasattr(event, event_name)
--> 231         [cb(event_name) for cb in sort_by_run(self.cbs)]
    232 
    233     def _bn_bias_state(self, with_bias): return bn_bias_params(self.model, with_bias).map(self.opt.state)

/usr/local/lib/python3.6/dist-packages/fastai2/learner.py in <listcomp>(.0)
    229     def _call_one(self, event_name):
    230         assert hasattr(event, event_name)
--> 231         [cb(event_name) for cb in sort_by_run(self.cbs)]
    232 
    233     def _bn_bias_state(self, with_bias): return bn_bias_params(self.model, with_bias).map(self.opt.state)

/usr/local/lib/python3.6/dist-packages/fastai2/learner.py in __call__(self, event_name)
     23         _run = (event_name not in _inner_loop or (self.run_train and getattr(self, 'training', True)) or
     24                (self.run_valid and not getattr(self, 'training', False)))
---> 25         if self.run and _run: getattr(self, event_name, noop)()
     26 
     27     def __setattr__(self, name, value):

/usr/local/lib/python3.6/dist-packages/fastai2/learner.py in after_fit(self)
     91         "Concatenate all recorded tensors"
     92         if self.with_input:     self.inputs  = detuplify(to_concat(self.inputs, dim=self.concat_dim))
---> 93         if not self.save_preds: self.preds   = detuplify(to_concat(self.preds, dim=self.concat_dim))
     94         if not self.save_targs: self.targets = detuplify(to_concat(self.targets, dim=self.concat_dim))
     95         if self.with_loss:      self.losses  = to_concat(self.losses)

/usr/local/lib/python3.6/dist-packages/fastcore/foundation.py in __getattr__(self, k)
    221             attr = getattr(self,self._default,None)
    222             if attr is not None: return getattr(attr, k)
--> 223         raise AttributeError(k)
    224     def __dir__(self): return custom_dir(self, self._dir() if self._xtra is None else self._dir())
    225 #     def __getstate__(self): return self.__dict__

AttributeError: preds

[sgugger]

I would need more code as what you gave me worked fine after the example in the transfer learning tutorial.

[muellerzr]

It works fine now, something may have been changed since I last looked at this. Thanks for checking in :)