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self._write_stats(self.recorder.metric_names)
begin_epoch(self)
getattr(self, 'mbar', False)
self.mbar.update(self.epoch)
begin_train(self)
self._launch_pbar()
begin_validate(self)
self._launch_pbar()
after_train(self)
self.pbar.on_iter_end()
after_validate(self)
self.pbar.on_iter_end()
after_batch(self)
self.pbar.update(self.iter+1)
hasattr(self, 'smooth_loss')
_launch_pbar(self)
progress_bar(self.dl, parent=getattr(self, 'mbar', None)
self.pbar.update(0)
after_fit(self)
getattr(self, 'mbar', False)
self.mbar.on_iter_end()
delattr(self, 'mbar')
_write_stats(self, log)
getattr(self, 'mbar', False)
self.mbar.write([f'{l:.6f}' if isinstance(l, float)
str(l)
no_bar(self:Learner)
hasattr(self, 'progress')
self.remove_cb(self.progress)
self.add_cb(ProgressCallback()
ShowGraphCallback(Callback)
begin_fit(self)
hasattr(self.learn, 'lr_finder')
hasattr(self, "gather_preds")
hasattr(self.learn, 'progress')
after_train(self)
self.nb_batches.append(self.train_iter)
after_epoch(self)
range_of(rec.losses)
len(self.nb_batches)
len(rec.losses)
max((max(Tensor(rec.losses)
max(Tensor(val_losses)
self.progress.mbar.update_graph([(iters, rec.losses)
CSVLogger(Callback)
__init__(self, fname='history.csv', append=False)
Path(fname)
read_log(self)
pd.read_csv(self.path/self.fname)
begin_fit(self)
self.path.parent.mkdir(parents=True, exist_ok=True)
open('a' if self.append else 'w')
self.file.write(','.join(self.recorder.metric_names)
_write_line(self, log)
self.file.write(','.join([str(t)
self.old_logger(log)
after_fit(self)
self.file.close()
sys.path.append(os.path.normpath(os.path.join(os.path.dirname(__file__)
len(sys.argv)
print(usage)
sys.exit(1)
gentariumlib.deserialise(sys.argv[1])
pdb.set_trace()
setup()
size(600, 600)
range(60)
random(10)
balls.append(BouncingBall()
boxes.append(BouncingBox()
draw()
background("#2b3e50")
ball.move()
ball.display()
box.move()
box.display()
Copyright (c)
Copyright (c)
TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
debug_print(enabled_or_option='debug')
debug_print('debug_media')
some_func()
_debug_media('My debug statement')
isinstance(enabled_or_option, bool)
pyglet.options.get(enabled_or_option, False)
_debug_print(*args, **kwargs)
print(*args, **kwargs)
_debug_print(*args, **kwargs)
cobinhood (Exchange)
describe(self)
self.deep_extend(super(cobinhood, self)
describe()
fetch_currencies(self, params={})
self.publicGetMarketCurrencies(params)
range(0, len(currencies)
self.common_currency_code(id)
self.safe_float(currency, 'min_unit')
self.precision_from_string(currency['min_unit'])
self.safe_float(currency, 'withdrawal_fee')
self.safe_float(currency, 'deposit_fee')