I want to suppress all output from fastai2 and other packages, so I used %%capture magic.
But it seems fastai2 requires stream to display progress bar, so it raised error, can anybody tell me how to disable the progress bar completely?
%%capture --no-stderr
...
learn = Learner(...)
learn.lr_find(show_plot=False)
get AttributeError: 'NBMasterBar' object has no attribute 'out'
<ipython-input-9-886578be0f8a> in run_it(hparam, config, run_name, device)
12 learn.recorder.silent = True
13 # fit
---> 14 lr,_ = learn.lr_find(show_plot=False, num_it=int(46000/hparam['batch_size']/hparam['sequence_length']))
15 config['lr'] = lr
16 learn.fit_one_cycle(hparam['num_epoch'], lr, cbs=[MyWandbCallback(config=config, name=run_name),])
/usr/local/lib/python3.6/dist-packages/fastai2/callback/schedule.py in lr_find(self, start_lr, end_lr, num_it, stop_div, show_plot, suggestions)
217 n_epoch = num_it//len(self.dls.train) + 1
218 cb=LRFinder(start_lr=start_lr, end_lr=end_lr, num_it=num_it, stop_div=stop_div)
--> 219 with self.no_logging(): self.fit(n_epoch, cbs=cb)
220 if show_plot: self.recorder.plot_lr_find()
221 if suggestions:
/usr/local/lib/python3.6/dist-packages/fastai2/learner.py in fit(self, n_epoch, lr, wd, cbs, reset_opt)
180
181 except CancelFitException: self('after_cancel_fit')
--> 182 finally: self('after_fit')
183
184 def validate(self, ds_idx=1, dl=None, cbs=None):
/usr/local/lib/python3.6/dist-packages/fastai2/learner.py in __call__(self, event_name)
106 def ordered_cbs(self, cb_func): return [cb for cb in sort_by_run(self.cbs) if hasattr(cb, cb_func)]
107
--> 108 def __call__(self, event_name): L(event_name).map(self._call_one)
109 def _call_one(self, event_name):
110 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)
109 def _call_one(self, event_name):
110 assert hasattr(event, event_name)
--> 111 [cb(event_name) for cb in sort_by_run(self.cbs)]
112
113 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)
109 def _call_one(self, event_name):
110 assert hasattr(event, event_name)
--> 111 [cb(event_name) for cb in sort_by_run(self.cbs)]
112
113 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/callback/core.py in __call__(self, event_name)
21 _run = (event_name not in _inner_loop or (self.run_train and getattr(self, 'training', True)) or
22 (self.run_valid and not getattr(self, 'training', False)))
---> 23 if self.run and _run: getattr(self, event_name, noop)()
24 if event_name=='after_fit': self.run=True #Reset self.run to True at each end of fit
25
/usr/local/lib/python3.6/dist-packages/fastai2/callback/progress.py in after_fit(self)
37 def after_fit(self):
38 if getattr(self, 'mbar', False):
---> 39 self.mbar.on_iter_end()
40 delattr(self, 'mbar')
41 self.learn.logger = self.old_logger
/usr/local/lib/python3.6/dist-packages/fastprogress/fastprogress.py in on_iter_end(self)
155 total_time = format_time(time.time() - self.main_bar.start_t)
156 self.text = f'Total time: {total_time} <p>' + self.text
--> 157 self.out.update(HTML(self.text))
158
159 def add_child(self, child):