I am getting the following exception when trying to use TensorBoardCallback in fastai v2:
AttributeError: ‘Learner’ object has no attribute ‘smooth_loss’
Here is my code and the detailed exception:
learn = Learner(dls, model, cbs=[ParamScheduler(scheds), AnnealedLossCallback(), TensorBoardCallback('logs', trace_model=False)], loss_func=loss_fn, metrics=[BCEMetric(), KLDMetric(), MUMetric(), StdMetric()])
learn = learn.to_fp16()
learn.fit_one_cycle(200)
AttributeError Traceback (most recent call last)
c:\work\ml\fastai2\fastai2\learner.py in _with_events(self, f, event_type, ex, final)
154 def _with_events(self, f, event_type, ex, final=noop):
--> 155 try: self(f'before_{event_type}') ;f()
156 except ex: self(f'after_cancel_{event_type}')
c:\work\ml\fastai2\fastai2\learner.py in _do_epoch(self)
187 def _do_epoch(self):
--> 188 self._do_epoch_train()
189 self._do_epoch_validate()
c:\work\ml\fastai2\fastai2\learner.py in _do_epoch_train(self)
179 self.dl = self.dls.train
--> 180 self._with_events(self.all_batches, 'train', CancelTrainException)
181
c:\work\ml\fastai2\fastai2\learner.py in _with_events(self, f, event_type, ex, final)
154 def _with_events(self, f, event_type, ex, final=noop):
--> 155 try: self(f'before_{event_type}') ;f()
156 except ex: self(f'after_cancel_{event_type}')
c:\work\ml\fastai2\fastai2\learner.py in all_batches(self)
160 self.n_iter = len(self.dl)
--> 161 for o in enumerate(self.dl): self.one_batch(*o)
162
c:\work\ml\fastai2\fastai2\learner.py in one_batch(self, i, b)
175 self._split(b)
--> 176 self._with_events(self._do_one_batch, 'batch', CancelBatchException)
177
c:\work\ml\fastai2\fastai2\learner.py in _with_events(self, f, event_type, ex, final)
156 except ex: self(f'after_cancel_{event_type}')
--> 157 finally: self(f'after_{event_type}') ;final()
158
c:\work\ml\fastai2\fastai2\learner.py in __call__(self, event_name)
132
--> 133 def __call__(self, event_name): L(event_name).map(self._call_one)
134
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\foundation.py in map(self, f, *args, **kwargs)
382 else f.__getitem__)
--> 383 return self._new(map(g, self))
384
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\foundation.py in _new(self, items, *args, **kwargs)
332 def _xtra(self): return None
--> 333 def _new(self, items, *args, **kwargs): return type(self)(items, *args, use_list=None, **kwargs)
334 def __getitem__(self, idx): return self._get(idx) if is_indexer(idx) else L(self._get(idx), use_list=None)
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\foundation.py in __call__(cls, x, *args, **kwargs)
46
---> 47 res = super().__call__(*((x,) + args), **kwargs)
48 res._newchk = 0
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\foundation.py in __init__(self, items, use_list, match, *rest)
323 if (use_list is not None) or not _is_array(items):
--> 324 items = list(items) if use_list else _listify(items)
325 if match is not None:
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\foundation.py in _listify(o)
259 if isinstance(o, str) or _is_array(o): return [o]
--> 260 if is_iter(o): return list(o)
261 return [o]
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\foundation.py in __call__(self, *args, **kwargs)
225 fargs = [args[x.i] if isinstance(x, _Arg) else x for x in self.pargs] + args[self.maxi+1:]
--> 226 return self.fn(*fargs, **kwargs)
227
c:\work\ml\fastai2\fastai2\learner.py in _call_one(self, event_name)
136 assert hasattr(event, event_name), event_name
--> 137 [cb(event_name) for cb in sort_by_run(self.cbs)]
138
c:\work\ml\fastai2\fastai2\learner.py in <listcomp>(.0)
136 assert hasattr(event, event_name), event_name
--> 137 [cb(event_name) for cb in sort_by_run(self.cbs)]
138
c:\work\ml\fastai2\fastai2\callback\core.py in __call__(self, event_name)
43 res = None
---> 44 if self.run and _run: res = getattr(self, event_name, noop)()
45 if event_name=='after_fit': self.run=True #Reset self.run to True at each end of fit
c:\work\ml\fastai2\fastai2\callback\tensorboard.py in after_batch(self)
29 def after_batch(self):
---> 30 self.writer.add_scalar('train_loss', self.smooth_loss, self.train_iter)
31 for i,h in enumerate(self.opt.hypers):
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\foundation.py in __getattr__(self, k)
239 attr = getattr(self,self._default,None)
--> 240 if attr is not None: return getattr(attr,k)
241 raise AttributeError(k)
AttributeError: 'Learner' object has no attribute 'smooth_loss'
During handling of the above exception, another exception occurred:
AttributeError Traceback (most recent call last)
<ipython-input-14-625883747759> in <module>
----> 1 learn.fit_one_cycle(200)
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\utils.py in _f(*args, **kwargs)
450 init_args.update(log)
451 setattr(inst, 'init_args', init_args)
--> 452 return inst if to_return else f(*args, **kwargs)
453 return _f
454
c:\work\ml\fastai2\fastai2\callback\schedule.py in fit_one_cycle(self, n_epoch, lr_max, div, div_final, pct_start, wd, moms, cbs, reset_opt)
111 scheds = {'lr': combined_cos(pct_start, lr_max/div, lr_max, lr_max/div_final),
112 'mom': combined_cos(pct_start, *(self.moms if moms is None else moms))}
--> 113 self.fit(n_epoch, cbs=ParamScheduler(scheds)+L(cbs), reset_opt=reset_opt, wd=wd)
114
115 # Cell
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\utils.py in _f(*args, **kwargs)
450 init_args.update(log)
451 setattr(inst, 'init_args', init_args)
--> 452 return inst if to_return else f(*args, **kwargs)
453 return _f
454
c:\work\ml\fastai2\fastai2\learner.py in fit(self, n_epoch, lr, wd, cbs, reset_opt)
202 self.opt.set_hypers(lr=self.lr if lr is None else lr)
203 self.n_epoch,self.loss = n_epoch,tensor(0.)
--> 204 self._with_events(self._do_fit, 'fit', CancelFitException, self._end_cleanup)
205
206 def _end_cleanup(self): self.dl,self.xb,self.yb,self.pred,self.loss = None,(None,),(None,),None,None
c:\work\ml\fastai2\fastai2\learner.py in _with_events(self, f, event_type, ex, final)
153
154 def _with_events(self, f, event_type, ex, final=noop):
--> 155 try: self(f'before_{event_type}') ;f()
156 except ex: self(f'after_cancel_{event_type}')
157 finally: self(f'after_{event_type}') ;final()
c:\work\ml\fastai2\fastai2\learner.py in _do_fit(self)
192 for epoch in range(self.n_epoch):
193 self.epoch=epoch
--> 194 self._with_events(self._do_epoch, 'epoch', CancelEpochException)
195
196 @log_args(but='cbs')
c:\work\ml\fastai2\fastai2\learner.py in _with_events(self, f, event_type, ex, final)
155 try: self(f'before_{event_type}') ;f()
156 except ex: self(f'after_cancel_{event_type}')
--> 157 finally: self(f'after_{event_type}') ;final()
158
159 def all_batches(self):
c:\work\ml\fastai2\fastai2\learner.py in __call__(self, event_name)
131 def ordered_cbs(self, event): return [cb for cb in sort_by_run(self.cbs) if hasattr(cb, event)]
132
--> 133 def __call__(self, event_name): L(event_name).map(self._call_one)
134
135 def _call_one(self, event_name):
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\foundation.py in map(self, f, *args, **kwargs)
381 else f.format if isinstance(f,str)
382 else f.__getitem__)
--> 383 return self._new(map(g, self))
384
385 def filter(self, f, negate=False, **kwargs):
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\foundation.py in _new(self, items, *args, **kwargs)
331 @property
332 def _xtra(self): return None
--> 333 def _new(self, items, *args, **kwargs): return type(self)(items, *args, use_list=None, **kwargs)
334 def __getitem__(self, idx): return self._get(idx) if is_indexer(idx) else L(self._get(idx), use_list=None)
335 def copy(self): return self._new(self.items.copy())
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\foundation.py in __call__(cls, x, *args, **kwargs)
45 return x
46
---> 47 res = super().__call__(*((x,) + args), **kwargs)
48 res._newchk = 0
49 return res
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\foundation.py in __init__(self, items, use_list, match, *rest)
322 if items is None: items = []
323 if (use_list is not None) or not _is_array(items):
--> 324 items = list(items) if use_list else _listify(items)
325 if match is not None:
326 if is_coll(match): match = len(match)
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\foundation.py in _listify(o)
258 if isinstance(o, list): return o
259 if isinstance(o, str) or _is_array(o): return [o]
--> 260 if is_iter(o): return list(o)
261 return [o]
262
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\foundation.py in __call__(self, *args, **kwargs)
224 if isinstance(v,_Arg): kwargs[k] = args.pop(v.i)
225 fargs = [args[x.i] if isinstance(x, _Arg) else x for x in self.pargs] + args[self.maxi+1:]
--> 226 return self.fn(*fargs, **kwargs)
227
228 # Cell
c:\work\ml\fastai2\fastai2\learner.py in _call_one(self, event_name)
135 def _call_one(self, event_name):
136 assert hasattr(event, event_name), event_name
--> 137 [cb(event_name) for cb in sort_by_run(self.cbs)]
138
139 def _bn_bias_state(self, with_bias): return norm_bias_params(self.model, with_bias).map(self.opt.state)
c:\work\ml\fastai2\fastai2\learner.py in <listcomp>(.0)
135 def _call_one(self, event_name):
136 assert hasattr(event, event_name), event_name
--> 137 [cb(event_name) for cb in sort_by_run(self.cbs)]
138
139 def _bn_bias_state(self, with_bias): return norm_bias_params(self.model, with_bias).map(self.opt.state)
c:\work\ml\fastai2\fastai2\callback\core.py in __call__(self, event_name)
42 (self.run_valid and not getattr(self, 'training', False)))
43 res = None
---> 44 if self.run and _run: res = getattr(self, event_name, noop)()
45 if event_name=='after_fit': self.run=True #Reset self.run to True at each end of fit
46 return res
c:\work\ml\fastai2\fastai2\callback\tensorboard.py in after_epoch(self)
37 if self.log_preds:
38 b = self.dls.valid.one_batch()
---> 39 self.learn.one_batch(0, b)
40 preds = getattr(self.loss_func, 'activation', noop)(self.pred)
41 out = getattr(self.loss_func, 'decodes', noop)(preds)
c:\work\ml\fastai2\fastai2\learner.py in one_batch(self, i, b)
174 self.iter = i
175 self._split(b)
--> 176 self._with_events(self._do_one_batch, 'batch', CancelBatchException)
177
178 def _do_epoch_train(self):
c:\work\ml\fastai2\fastai2\learner.py in _with_events(self, f, event_type, ex, final)
155 try: self(f'before_{event_type}') ;f()
156 except ex: self(f'after_cancel_{event_type}')
--> 157 finally: self(f'after_{event_type}') ;final()
158
159 def all_batches(self):
c:\work\ml\fastai2\fastai2\learner.py in __call__(self, event_name)
131 def ordered_cbs(self, event): return [cb for cb in sort_by_run(self.cbs) if hasattr(cb, event)]
132
--> 133 def __call__(self, event_name): L(event_name).map(self._call_one)
134
135 def _call_one(self, event_name):
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\foundation.py in map(self, f, *args, **kwargs)
381 else f.format if isinstance(f,str)
382 else f.__getitem__)
--> 383 return self._new(map(g, self))
384
385 def filter(self, f, negate=False, **kwargs):
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\foundation.py in _new(self, items, *args, **kwargs)
331 @property
332 def _xtra(self): return None
--> 333 def _new(self, items, *args, **kwargs): return type(self)(items, *args, use_list=None, **kwargs)
334 def __getitem__(self, idx): return self._get(idx) if is_indexer(idx) else L(self._get(idx), use_list=None)
335 def copy(self): return self._new(self.items.copy())
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\foundation.py in __call__(cls, x, *args, **kwargs)
45 return x
46
---> 47 res = super().__call__(*((x,) + args), **kwargs)
48 res._newchk = 0
49 return res
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\foundation.py in __init__(self, items, use_list, match, *rest)
322 if items is None: items = []
323 if (use_list is not None) or not _is_array(items):
--> 324 items = list(items) if use_list else _listify(items)
325 if match is not None:
326 if is_coll(match): match = len(match)
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\foundation.py in _listify(o)
258 if isinstance(o, list): return o
259 if isinstance(o, str) or _is_array(o): return [o]
--> 260 if is_iter(o): return list(o)
261 return [o]
262
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\foundation.py in __call__(self, *args, **kwargs)
224 if isinstance(v,_Arg): kwargs[k] = args.pop(v.i)
225 fargs = [args[x.i] if isinstance(x, _Arg) else x for x in self.pargs] + args[self.maxi+1:]
--> 226 return self.fn(*fargs, **kwargs)
227
228 # Cell
c:\work\ml\fastai2\fastai2\learner.py in _call_one(self, event_name)
135 def _call_one(self, event_name):
136 assert hasattr(event, event_name), event_name
--> 137 [cb(event_name) for cb in sort_by_run(self.cbs)]
138
139 def _bn_bias_state(self, with_bias): return norm_bias_params(self.model, with_bias).map(self.opt.state)
c:\work\ml\fastai2\fastai2\learner.py in <listcomp>(.0)
135 def _call_one(self, event_name):
136 assert hasattr(event, event_name), event_name
--> 137 [cb(event_name) for cb in sort_by_run(self.cbs)]
138
139 def _bn_bias_state(self, with_bias): return norm_bias_params(self.model, with_bias).map(self.opt.state)
c:\work\ml\fastai2\fastai2\callback\core.py in __call__(self, event_name)
42 (self.run_valid and not getattr(self, 'training', False)))
43 res = None
---> 44 if self.run and _run: res = getattr(self, event_name, noop)()
45 if event_name=='after_fit': self.run=True #Reset self.run to True at each end of fit
46 return res
c:\work\ml\fastai2\fastai2\callback\tensorboard.py in after_batch(self)
28
29 def after_batch(self):
---> 30 self.writer.add_scalar('train_loss', self.smooth_loss, self.train_iter)
31 for i,h in enumerate(self.opt.hypers):
32 for k,v in h.items(): self.writer.add_scalar(f'{k}_{i}', v, self.train_iter)
~\Anaconda3\envs\fastai2\lib\site-packages\fastcore\foundation.py in __getattr__(self, k)
238 if self._component_attr_filter(k):
239 attr = getattr(self,self._default,None)
--> 240 if attr is not None: return getattr(attr,k)
241 raise AttributeError(k)
242 def __dir__(self): return custom_dir(self,self._dir())
AttributeError: 'Learner' object has no attribute 'smooth_loss'