Hello everyone,
these days I am struggling to get the ImageClassifierCleaner to work more properly. While I’ve found a way around (when I delete a pic, I update the cleaner.iwis AND the leaner.dls[0 or 1].dataset to NOT include the removed pic anymore), I sometimes get this error while trying to re-fine_tune the learner:
AttributeError: ‘Tensor’ object has no attribute ‘append’
Full error:
AttributeError Traceback (most recent call last)
~/anaconda3/lib/python3.7/site-packages/fastai2/learner.py in one_batch(self, i, b)
147 try:
--> 148 self._split(b); self('begin_batch')
149 self.pred = self.model(*self.xb); self('after_pred')
~/anaconda3/lib/python3.7/site-packages/fastai2/learner.py in __call__(self, event_name)
123
--> 124 def __call__(self, event_name): L(event_name).map(self._call_one)
125 def _call_one(self, event_name):
~/anaconda3/lib/python3.7/site-packages/fastcore/foundation.py in map(self, f, *args, **kwargs)
371 else f.__getitem__)
--> 372 return self._new(map(g, self))
373
~/anaconda3/lib/python3.7/site-packages/fastcore/foundation.py in _new(self, items, *args, **kwargs)
322 def _xtra(self): return None
--> 323 def _new(self, items, *args, **kwargs): return type(self)(items, *args, use_list=None, **kwargs)
324 def __getitem__(self, idx): return self._get(idx) if is_indexer(idx) else L(self._get(idx), use_list=None)
~/anaconda3/lib/python3.7/site-packages/fastcore/foundation.py in __call__(cls, x, *args, **kwargs)
40
---> 41 res = super().__call__(*((x,) + args), **kwargs)
42 res._newchk = 0
~/anaconda3/lib/python3.7/site-packages/fastcore/foundation.py in __init__(self, items, use_list, match, *rest)
313 if (use_list is not None) or not _is_array(items):
--> 314 items = list(items) if use_list else _listify(items)
315 if match is not None:
~/anaconda3/lib/python3.7/site-packages/fastcore/foundation.py in _listify(o)
249 if isinstance(o, str) or _is_array(o): return [o]
--> 250 if is_iter(o): return list(o)
251 return [o]
~/anaconda3/lib/python3.7/site-packages/fastcore/foundation.py in __call__(self, *args, **kwargs)
215 fargs = [args[x.i] if isinstance(x, _Arg) else x for x in self.pargs] + args[self.maxi+1:]
--> 216 return self.fn(*fargs, **kwargs)
217
~/anaconda3/lib/python3.7/site-packages/fastai2/learner.py in _call_one(self, event_name)
126 assert hasattr(event, event_name)
--> 127 [cb(event_name) for cb in sort_by_run(self.cbs)]
128
~/anaconda3/lib/python3.7/site-packages/fastai2/learner.py in <listcomp>(.0)
126 assert hasattr(event, event_name)
--> 127 [cb(event_name) for cb in sort_by_run(self.cbs)]
128
~/anaconda3/lib/python3.7/site-packages/fastai2/callback/core.py in __call__(self, event_name)
23 (self.run_valid and not getattr(self, 'training', False)))
---> 24 if self.run and _run: getattr(self, event_name, noop)()
25 if event_name=='after_fit': self.run=True #Reset self.run to True at each end of fit
~/anaconda3/lib/python3.7/site-packages/fastai2/callback/core.py in begin_batch(self)
72 def begin_batch(self):
---> 73 if self.with_input: self.inputs.append((to_detach(self.xb)))
74
AttributeError: 'TensorImage' object has no attribute 'append'
During handling of the above exception, another exception occurred:
AttributeError Traceback (most recent call last)
<ipython-input-67-ca61b3aa75fc> in <module>
----> 1 learn.fine_tune(1)
~/anaconda3/lib/python3.7/site-packages/fastai2/callback/schedule.py in fine_tune(self, epochs, base_lr, freeze_epochs, lr_mult, pct_start, div, **kwargs)
155 "Fine tune with `freeze` for `freeze_epochs` then with `unfreeze` from `epochs` using discriminative LR"
156 self.freeze()
--> 157 self.fit_one_cycle(freeze_epochs, slice(base_lr), pct_start=0.99, **kwargs)
158 base_lr /= 2
159 self.unfreeze()
~/anaconda3/lib/python3.7/site-packages/fastai2/callback/schedule.py in fit_one_cycle(self, n_epoch, lr_max, div, div_final, pct_start, wd, moms, cbs, reset_opt)
110 scheds = {'lr': combined_cos(pct_start, lr_max/div, lr_max, lr_max/div_final),
111 'mom': combined_cos(pct_start, *(self.moms if moms is None else moms))}
--> 112 self.fit(n_epoch, cbs=ParamScheduler(scheds)+L(cbs), reset_opt=reset_opt, wd=wd)
113
114 # Cell
~/anaconda3/lib/python3.7/site-packages/fastai2/learner.py in fit(self, n_epoch, lr, wd, cbs, reset_opt)
190 try:
191 self.epoch=epoch; self('begin_epoch')
--> 192 self._do_epoch_train()
193 self._do_epoch_validate()
194 except CancelEpochException: self('after_cancel_epoch')
~/anaconda3/lib/python3.7/site-packages/fastai2/learner.py in _do_epoch_train(self)
163 try:
164 self.dl = self.dls.train; self('begin_train')
--> 165 self.all_batches()
166 except CancelTrainException: self('after_cancel_train')
167 finally: self('after_train')
~/anaconda3/lib/python3.7/site-packages/fastai2/learner.py in all_batches(self)
141 def all_batches(self):
142 self.n_iter = len(self.dl)
--> 143 for o in enumerate(self.dl): self.one_batch(*o)
144
145 def one_batch(self, i, b):
~/anaconda3/lib/python3.7/site-packages/fastai2/learner.py in one_batch(self, i, b)
155 self.opt.zero_grad()
156 except CancelBatchException: self('after_cancel_batch')
--> 157 finally: self('after_batch')
158
159 def _do_begin_fit(self, n_epoch):
~/anaconda3/lib/python3.7/site-packages/fastai2/learner.py in __call__(self, event_name)
122 def ordered_cbs(self, event): return [cb for cb in sort_by_run(self.cbs) if hasattr(cb, event)]
123
--> 124 def __call__(self, event_name): L(event_name).map(self._call_one)
125 def _call_one(self, event_name):
126 assert hasattr(event, event_name)
~/anaconda3/lib/python3.7/site-packages/fastcore/foundation.py in map(self, f, *args, **kwargs)
370 else f.format if isinstance(f,str)
371 else f.__getitem__)
--> 372 return self._new(map(g, self))
373
374 def filter(self, f, negate=False, **kwargs):
~/anaconda3/lib/python3.7/site-packages/fastcore/foundation.py in _new(self, items, *args, **kwargs)
321 @property
322 def _xtra(self): return None
--> 323 def _new(self, items, *args, **kwargs): return type(self)(items, *args, use_list=None, **kwargs)
324 def __getitem__(self, idx): return self._get(idx) if is_indexer(idx) else L(self._get(idx), use_list=None)
325 def copy(self): return self._new(self.items.copy())
~/anaconda3/lib/python3.7/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
~/anaconda3/lib/python3.7/site-packages/fastcore/foundation.py in __init__(self, items, use_list, match, *rest)
312 if items is None: items = []
313 if (use_list is not None) or not _is_array(items):
--> 314 items = list(items) if use_list else _listify(items)
315 if match is not None:
316 if is_coll(match): match = len(match)
~/anaconda3/lib/python3.7/site-packages/fastcore/foundation.py in _listify(o)
248 if isinstance(o, list): return o
249 if isinstance(o, str) or _is_array(o): return [o]
--> 250 if is_iter(o): return list(o)
251 return [o]
252
~/anaconda3/lib/python3.7/site-packages/fastcore/foundation.py in __call__(self, *args, **kwargs)
214 if isinstance(v,_Arg): kwargs[k] = args.pop(v.i)
215 fargs = [args[x.i] if isinstance(x, _Arg) else x for x in self.pargs] + args[self.maxi+1:]
--> 216 return self.fn(*fargs, **kwargs)
217
218 # Cell
~/anaconda3/lib/python3.7/site-packages/fastai2/learner.py in _call_one(self, event_name)
125 def _call_one(self, event_name):
126 assert hasattr(event, event_name)
--> 127 [cb(event_name) for cb in sort_by_run(self.cbs)]
128
129 def _bn_bias_state(self, with_bias): return bn_bias_params(self.model, with_bias).map(self.opt.state)
~/anaconda3/lib/python3.7/site-packages/fastai2/learner.py in <listcomp>(.0)
125 def _call_one(self, event_name):
126 assert hasattr(event, event_name)
--> 127 [cb(event_name) for cb in sort_by_run(self.cbs)]
128
129 def _bn_bias_state(self, with_bias): return bn_bias_params(self.model, with_bias).map(self.opt.state)
~/anaconda3/lib/python3.7/site-packages/fastai2/callback/core.py in __call__(self, event_name)
22 _run = (event_name not in _inner_loop or (self.run_train and getattr(self, 'training', True)) or
23 (self.run_valid and not getattr(self, 'training', False)))
---> 24 if self.run and _run: getattr(self, event_name, noop)()
25 if event_name=='after_fit': self.run=True #Reset self.run to True at each end of fit
26
~/anaconda3/lib/python3.7/site-packages/fastai2/callback/core.py in after_batch(self)
82 "Save predictions, targets and potentially losses"
83 preds,targs = to_detach(self.pred),to_detach(self.yb)
---> 84 if self.save_preds is None: self.preds.append(preds)
85 else: (self.save_preds/str(self.iter)).save_array(preds)
86 if self.save_targs is None: self.targets.append(targs)
AttributeError: 'Tensor' object has no attribute 'append'
Is there a bug in after_batch ?
edit: or is this because I changed the dls and now they have one pic less ?
Have a nice day