Just a beginner taking course at https://course.fast.ai/
Setup new environment on my laptop:
Anaconda3-2020.07-Windows-x86_64
conda install pytorch torchvision torchaudio cpuonly -c pytorch
conda install -c fastai -c pytorch fastai
conda install -c fastai fastbook
Installed versions:
pytorch 1.7.0
fastai 2.0.16
fastbook 0.0.11
In …notebooks/fastbook/clean/01_intro.ipynb executing cell:
# CLICK ME
from fastai.vision.all import *
path = untar_data(URLs.PETS)/'images'
def is_cat(x): return x[0].isupper()
dls = ImageDataLoaders.from_name_func(
path, get_image_files(path), valid_pct=0.2, seed=42,
label_func=is_cat, item_tfms=Resize(224))
learn = cnn_learner(dls, resnet34, metrics=error_rate)
learn.fine_tune(1)
Resulted in error:
AttributeError Traceback (most recent call last)
in
9
10 learn = cnn_learner(dls, resnet34, metrics=error_rate)
—> 11 learn.fine_tune(1)D:\ProgramData\Anaconda3\envs\IP-Fastai\lib\site-packages\fastcore\logargs.py in _f(*args, **kwargs)
54 init_args.update(log)
55 setattr(inst, ‘init_args’, init_args)
—> 56 return inst if to_return else f(*args, **kwargs)
57 return _fD:\ProgramData\Anaconda3\envs\IP-Fastai\lib\site-packages\fastai\callback\schedule.py in fine_tune(self, epochs, base_lr, freeze_epochs, lr_mult, pct_start, div, **kwargs)
159 “Fine tune withfreezeforfreeze_epochsthen withunfreezefromepochsusing discriminative LR”
160 self.freeze()
–> 161 self.fit_one_cycle(freeze_epochs, slice(base_lr), pct_start=0.99, **kwargs)
162 base_lr /= 2
163 self.unfreeze()D:\ProgramData\Anaconda3\envs\IP-Fastai\lib\site-packages\fastcore\logargs.py in _f(*args, **kwargs)
54 init_args.update(log)
55 setattr(inst, ‘init_args’, init_args)
—> 56 return inst if to_return else f(*args, **kwargs)
57 return _fD:\ProgramData\Anaconda3\envs\IP-Fastai\lib\site-packages\fastai\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 # CellD:\ProgramData\Anaconda3\envs\IP-Fastai\lib\site-packages\fastcore\logargs.py in _f(*args, **kwargs)
54 init_args.update(log)
55 setattr(inst, ‘init_args’, init_args)
—> 56 return inst if to_return else f(*args, **kwargs)
57 return _fD:\ProgramData\Anaconda3\envs\IP-Fastai\lib\site-packages\fastai\learner.py in fit(self, n_epoch, lr, wd, cbs, reset_opt)
205 self.opt.set_hypers(lr=self.lr if lr is None else lr)
206 self.n_epoch = n_epoch
–> 207 self._with_events(self._do_fit, ‘fit’, CancelFitException, self._end_cleanup)
208
209 def _end_cleanup(self): self.dl,self.xb,self.yb,self.pred,self.loss = None,(None,),(None,),None,NoneD:\ProgramData\Anaconda3\envs\IP-Fastai\lib\site-packages\fastai\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()D:\ProgramData\Anaconda3\envs\IP-Fastai\lib\site-packages\fastai\learner.py in _do_fit(self)
195 for epoch in range(self.n_epoch):
196 self.epoch=epoch
–> 197 self._with_events(self._do_epoch, ‘epoch’, CancelEpochException)
198
199 @log_args(but=‘cbs’)D:\ProgramData\Anaconda3\envs\IP-Fastai\lib\site-packages\fastai\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()D:\ProgramData\Anaconda3\envs\IP-Fastai\lib\site-packages\fastai\learner.py in _do_epoch(self)
189
190 def _do_epoch(self):
–> 191 self._do_epoch_train()
192 self._do_epoch_validate()
193D:\ProgramData\Anaconda3\envs\IP-Fastai\lib\site-packages\fastai\learner.py in _do_epoch_train(self)
181 def _do_epoch_train(self):
182 self.dl = self.dls.train
–> 183 self._with_events(self.all_batches, ‘train’, CancelTrainException)
184
185 def _do_epoch_validate(self, ds_idx=1, dl=None):D:\ProgramData\Anaconda3\envs\IP-Fastai\lib\site-packages\fastai\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()D:\ProgramData\Anaconda3\envs\IP-Fastai\lib\site-packages\fastai\learner.py in all_batches(self)
159 def all_batches(self):
160 self.n_iter = len(self.dl)
–> 161 for o in enumerate(self.dl): self.one_batch(*o)
162
163 def _do_one_batch(self):D:\ProgramData\Anaconda3\envs\IP-Fastai\lib\site-packages\fastai\data\load.py in iter(self)
100 self.before_iter()
101 self.__idxs=self.get_idxs() # called in context of main process (not workers/subprocesses)
–> 102 for b in _loadersself.fake_l.num_workers==0:
103 if self.device is not None: b = to_device(b, self.device)
104 yield self.after_batch(b)D:\ProgramData\Anaconda3\envs\IP-Fastai\lib\site-packages\torch\utils\data\dataloader.py in init(self, loader)
761
762 def init(self, loader):
–> 763 super(_MultiProcessingDataLoaderIter, self).init(loader)
764
765 assert self._num_workers > 0D:\ProgramData\Anaconda3\envs\IP-Fastai\lib\site-packages\torch\utils\data\dataloader.py in init(self, loader)
413 self._sampler_iter = iter(self._index_sampler)
414 self.base_seed = torch.empty((), dtype=torch.int64).random(generator=loader.generator).item()
–> 415 self._persistent_workers = loader.persistent_workers
416 self._num_yielded = 0
417AttributeError: ‘_FakeLoader’ object has no attribute ‘persistent_workers’
Any suggestions?
Regards