learn.get_preds is very memory hungry and terminates with an error about fastai_dev HOT 3 CLOSED

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RuntimeError                              Traceback (most recent call last)
<ipython-input-19-4975c3720d00> in <module>
----> 1 preds = learn.get_preds(dl=tst_dl)

~/work/fastai_dev/dev/local/learner.py in get_preds(self, ds_idx, dl, with_input, with_loss, decoded, act)
    266         with self.no_logging(), self.added_cbs(cb), self.loss_not_reduced():
    267             self(_before_epoch)
--> 268             self._do_epoch_validate(ds_idx, dl)
    269             self(_after_epoch)
    270             if act is None: act = getattr(self.loss_func, 'activation', noop)

~/work/fastai_dev/dev/local/learner.py in _do_epoch_validate(self, ds_idx, dl)
    232             with torch.no_grad(): self.all_batches()
    233         except CancelValidException:                         self('after_cancel_validate')
--> 234         finally:                                             self('after_validate')
    235 
    236     def fit(self, n_epoch, lr=None, wd=defaults.wd, cbs=None, reset_opt=False):

~/work/fastai_dev/dev/local/learner.py in __call__(self, event_name)
    181         self.remove_cbs(cbs)
    182 
--> 183     def __call__(self, event_name): L(event_name).map(self._call_one)
    184     def _call_one(self, event_name):
    185         assert hasattr(event, event_name)

~/work/fastai_dev/dev/local/core.py in map(self, f, *args, **kwargs)
    333              else f.format if isinstance(f,str)
    334              else f.__getitem__)
--> 335         return self._new(map(g, self))
    336 
    337     def unique(self): return L(dict.fromkeys(self).keys())

~/work/fastai_dev/dev/local/core.py in _new(self, items, *args, **kwargs)
    287         super().__init__(items)
    288 
--> 289     def _new(self, items, *args, **kwargs): return type(self)(items, *args, use_list=None, **kwargs)
    290     def __getitem__(self, idx): return self._get(idx) if is_indexer(idx) else L(self._get(idx), use_list=None)
    291 

~/work/fastai_dev/dev/local/core.py in __call__(cls, x, *args, **kwargs)
     48             return x
     49 
---> 50         res = super().__call__(*((x,) + args), **kwargs)
     51         res._newchk = 0
     52         return res

~/work/fastai_dev/dev/local/core.py in __init__(self, items, use_list, match, *rest)
    281         if items is None: items = []
    282         if (use_list is not None) or not _is_array(items):
--> 283             items = list(items) if use_list else _listify(items)
    284         if match is not None:
    285             if len(items)==1: items = items*len(match)

~/work/fastai_dev/dev/local/core.py in _listify(o)
    225     if isinstance(o, list): return o
    226     if isinstance(o, str) or _is_array(o): return [o]
--> 227     if is_iter(o): return list(o)
    228     return [o]
    229 

~/work/fastai_dev/dev/local/core.py in __call__(self, *args, **kwargs)
    197             if isinstance(v,_Arg): kwargs[k] = args.pop(v.i)
    198         fargs = [args[x.i] if isinstance(x, _Arg) else x for x in self.pargs] + args[self.maxi+1:]
--> 199         return self.fn(*fargs, **kwargs)
    200 
    201 #Cell

~/work/fastai_dev/dev/local/learner.py in _call_one(self, event_name)
    184     def _call_one(self, event_name):
    185         assert hasattr(event, event_name)
--> 186         [cb(event_name) for cb in sort_by_run(self.cbs)]
    187 
    188     def _bn_bias_state(self, with_bias): return bn_bias_params(self.model, with_bias).map(self.opt.state)

~/work/fastai_dev/dev/local/learner.py in <listcomp>(.0)
    184     def _call_one(self, event_name):
    185         assert hasattr(event, event_name)
--> 186         [cb(event_name) for cb in sort_by_run(self.cbs)]
    187 
    188     def _bn_bias_state(self, with_bias): return bn_bias_params(self.model, with_bias).map(self.opt.state)

~/work/fastai_dev/dev/local/learner.py in __call__(self, event_name)
     26     def __call__(self, event_name):
     27         "Call `self.{event_name}` if it's defined"
---> 28         getattr(self, event_name, noop)()
     29 
     30     @property

~/work/fastai_dev/dev/local/learner.py in after_validate(self)
    450     def begin_validate(self): self._valid_mets.map(Self.reset())
    451     def after_train   (self): self.log += self._train_mets.map(_maybe_item)
--> 452     def after_validate(self): self.log += self._valid_mets.map(_maybe_item)
    453     def after_cancel_train(self):    self.cancel_train = True
    454     def after_cancel_validate(self): self.cancel_valid = True

~/work/fastai_dev/dev/local/core.py in map(self, f, *args, **kwargs)
    333              else f.format if isinstance(f,str)
    334              else f.__getitem__)
--> 335         return self._new(map(g, self))
    336 
    337     def unique(self): return L(dict.fromkeys(self).keys())

~/work/fastai_dev/dev/local/core.py in _new(self, items, *args, **kwargs)
    287         super().__init__(items)
    288 
--> 289     def _new(self, items, *args, **kwargs): return type(self)(items, *args, use_list=None, **kwargs)
    290     def __getitem__(self, idx): return self._get(idx) if is_indexer(idx) else L(self._get(idx), use_list=None)
    291 

~/work/fastai_dev/dev/local/core.py in __call__(cls, x, *args, **kwargs)
     48             return x
     49 
---> 50         res = super().__call__(*((x,) + args), **kwargs)
     51         res._newchk = 0
     52         return res

~/work/fastai_dev/dev/local/core.py in __init__(self, items, use_list, match, *rest)
    281         if items is None: items = []
    282         if (use_list is not None) or not _is_array(items):
--> 283             items = list(items) if use_list else _listify(items)
    284         if match is not None:
    285             if len(items)==1: items = items*len(match)

~/work/fastai_dev/dev/local/core.py in _listify(o)
    225     if isinstance(o, list): return o
    226     if isinstance(o, str) or _is_array(o): return [o]
--> 227     if is_iter(o): return list(o)
    228     return [o]
    229 

~/work/fastai_dev/dev/local/core.py in __call__(self, *args, **kwargs)
    197             if isinstance(v,_Arg): kwargs[k] = args.pop(v.i)
    198         fargs = [args[x.i] if isinstance(x, _Arg) else x for x in self.pargs] + args[self.maxi+1:]
--> 199         return self.fn(*fargs, **kwargs)
    200 
    201 #Cell

~/work/fastai_dev/dev/local/learner.py in _maybe_item(t)
    409 
    410 def _maybe_item(t):
--> 411     t = t.value
    412     return t.item() if isinstance(t, Tensor) and t.numel()==1 else t
    413 

~/work/fastai_dev/dev/local/metrics.py in value(self)
     40     @property
     41     def value(self):
---> 42         preds,targs = torch.cat(self.preds),torch.cat(self.targs)
     43         if self.to_np: preds,targs = preds.numpy(),targs.numpy()
     44         return self.func(targs, preds, **self.kwargs) if self.invert_args else self.func(preds, targs, **self.kwargs)

RuntimeError: expected a non-empty list of Tensors