To anyone looking to solve this issue:
delete the folder by launching a terminal in /storage/data/
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Hi. Iām trying to get set up on Paperspace. For step 3 in the Basic steps above, Iām not seeing the container āPaperspace + Fast.Ai 2.0 (V4).ā When I look under the all containers tab, the only fastai containers Iām seeing are āPaperspace + Fast.AIā and āPaperspace + Fast.AI 1.0 (V3).ā I initially selected āPaperspace + Fast.AIā based on the instructions given here https://course.fast.ai/start_gradient.html#step-2-create-notebook
However, with this container, the import statements in /course-v4/nbs/01_intro.ipynb are failing. Any guidance on what is the correct container I need to use?
Hi @tomg or @dkobran. Should there be a āPaperspace + Fast.Ai 2.0 (V4)ā container available on Paperspace?
Hi @agrahame ā These instructions are correct, this container is the latest and all encompassing container. Meaning it has both fastbook and course-v4 in it and has been tested with both.
Couple of tips for success:
You MUST run on a GPU capable instance, you cannot run fastai without a GPU.
As always, please run a refresh of the repo once inside course-v4 (or fastbook) directory via a git pull.
@tomg thanks for your quick response! Iāve ensured that Iām running on a GPU enabled instance and that my fastbook repository is up-to-date. However, if I try to execute the setup cell inside the /fastbook/01_intro.ipynb notebook, Iām getting the below errors:
I even tried adding āpip install azure-cognitiveservices-search-imagesearchā and āpip install nbdevā but in both cases I get the output that theyāre already installed. However, I still just get the same NameError. Not sure if Iām missing something.
Hmm, this is very strange indeed @agrahame since all of these dependencies are pre-installed. Perhaps youāve modified your notebook? I was unable to replicate this issue just now.
I suggest creating a fresh new notebook using the Papersapce + Fast.AI container found under our Recommended containers ā then once launched open a terminal and cd into fastbook and pull down the latest version via git pull. These are the steps I followed and was able to start lesson 1 without issues.
@tomg I think Iāve identified the issue. In the instructions found here https://course.fast.ai/start_gradient#step-3--update-the-fastai-library it says to run āpip install fastai fastcore --upgradeā after starting the machine. However, this seems to be whatās leading to the errors I was seeing. I just created a notebook from scratch and didnāt run that pip install and now Iām not seeing the error. Thanks for your help.
I had the same error message (āIN_NOTEBOOK is not definedā) with the first cell (āfrom utils import *, from fastai.vision.widgets import *ā) when trying to run the original 02_production notebook (fresh new notebook as Tom suggested, followed the gradient instructions including the āpip install fastai fast core --upgradeā). Tried it without the āpip installā command and it ran without errors. Thanks for the help
To solve the problem, run
pip install nbdev --upgrade
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Thanks worked for the IN_NOTEBOOK error
Iām having trouble getting through errors in Lesson 1.
Iām using the free trial, and Iāve gone through the instructions to update things in terminal,
ie:
pip install fastai fastcore --upgrade
cd fastbook
git pull
Running the first cell from utils import * had a hitch, this was fixed with pip install nbdev --upgrade, but now for āRunning my First Notebookā I get the following error:
<ipython-input-2-3244ec10e8a7> in <module>
9
10 learn = cnn_learner(dls, resnet34, metrics=error_rate)
---> 11 learn.fine_tune(1)
/opt/conda/envs/fastai/lib/python3.8/site-packages/fastcore/utils.py in _f(*args, **kwargs)
471 init_args.update(log)
472 setattr(inst, 'init_args', init_args)
--> 473 return inst if to_return else f(*args, **kwargs)
474 return _f
475
/opt/conda/envs/fastai/lib/python3.8/site-packages/fastai/callback/schedule.py in fine_tune(self, epochs, base_lr, freeze_epochs, lr_mult, pct_start, div, **kwargs)
159 "Fine tune with `freeze` for `freeze_epochs` then with `unfreeze` from `epochs` using 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()
/opt/conda/envs/fastai/lib/python3.8/site-packages/fastcore/utils.py in _f(*args, **kwargs)
471 init_args.update(log)
472 setattr(inst, 'init_args', init_args)
--> 473 return inst if to_return else f(*args, **kwargs)
474 return _f
475
/opt/conda/envs/fastai/lib/python3.8/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 # Cell
/opt/conda/envs/fastai/lib/python3.8/site-packages/fastcore/utils.py in _f(*args, **kwargs)
471 init_args.update(log)
472 setattr(inst, 'init_args', init_args)
--> 473 return inst if to_return else f(*args, **kwargs)
474 return _f
475
/opt/conda/envs/fastai/lib/python3.8/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,self.loss = n_epoch,tensor(0.)
--> 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,None
/opt/conda/envs/fastai/lib/python3.8/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()
/opt/conda/envs/fastai/lib/python3.8/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')
/opt/conda/envs/fastai/lib/python3.8/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()
/opt/conda/envs/fastai/lib/python3.8/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()
193
/opt/conda/envs/fastai/lib/python3.8/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):
/opt/conda/envs/fastai/lib/python3.8/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()
/opt/conda/envs/fastai/lib/python3.8/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):
/opt/conda/envs/fastai/lib/python3.8/site-packages/fastai/learner.py in one_batch(self, i, b)
177 self.iter = i
178 self._split(b)
--> 179 self._with_events(self._do_one_batch, 'batch', CancelBatchException)
180
181 def _do_epoch_train(self):
/opt/conda/envs/fastai/lib/python3.8/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()
/opt/conda/envs/fastai/lib/python3.8/site-packages/fastai/learner.py in _do_one_batch(self)
162
163 def _do_one_batch(self):
--> 164 self.pred = self.model(*self.xb)
165 self('after_pred')
166 if len(self.yb): self.loss = self.loss_func(self.pred, *self.yb)
/opt/conda/envs/fastai/lib/python3.8/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
720 result = self._slow_forward(*input, **kwargs)
721 else:
--> 722 result = self.forward(*input, **kwargs)
723 for hook in itertools.chain(
724 _global_forward_hooks.values(),
/opt/conda/envs/fastai/lib/python3.8/site-packages/torch/nn/modules/container.py in forward(self, input)
115 def forward(self, input):
116 for module in self:
--> 117 input = module(input)
118 return input
119
/opt/conda/envs/fastai/lib/python3.8/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
720 result = self._slow_forward(*input, **kwargs)
721 else:
--> 722 result = self.forward(*input, **kwargs)
723 for hook in itertools.chain(
724 _global_forward_hooks.values(),
/opt/conda/envs/fastai/lib/python3.8/site-packages/torch/nn/modules/container.py in forward(self, input)
115 def forward(self, input):
116 for module in self:
--> 117 input = module(input)
118 return input
119
/opt/conda/envs/fastai/lib/python3.8/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
720 result = self._slow_forward(*input, **kwargs)
721 else:
--> 722 result = self.forward(*input, **kwargs)
723 for hook in itertools.chain(
724 _global_forward_hooks.values(),
/opt/conda/envs/fastai/lib/python3.8/site-packages/torch/nn/modules/container.py in forward(self, input)
115 def forward(self, input):
116 for module in self:
--> 117 input = module(input)
118 return input
119
/opt/conda/envs/fastai/lib/python3.8/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
720 result = self._slow_forward(*input, **kwargs)
721 else:
--> 722 result = self.forward(*input, **kwargs)
723 for hook in itertools.chain(
724 _global_forward_hooks.values(),
/opt/conda/envs/fastai/lib/python3.8/site-packages/torchvision/models/resnet.py in forward(self, x)
61 out = self.relu(out)
62
---> 63 out = self.conv2(out)
64 out = self.bn2(out)
65
/opt/conda/envs/fastai/lib/python3.8/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
720 result = self._slow_forward(*input, **kwargs)
721 else:
--> 722 result = self.forward(*input, **kwargs)
723 for hook in itertools.chain(
724 _global_forward_hooks.values(),
/opt/conda/envs/fastai/lib/python3.8/site-packages/torch/nn/modules/conv.py in forward(self, input)
417
418 def forward(self, input: Tensor) -> Tensor:
--> 419 return self._conv_forward(input, self.weight)
420
421 class Conv3d(_ConvNd):
/opt/conda/envs/fastai/lib/python3.8/site-packages/torch/nn/modules/conv.py in _conv_forward(self, input, weight)
413 weight, self.bias, self.stride,
414 _pair(0), self.dilation, self.groups)
--> 415 return F.conv2d(input, weight, self.bias, self.stride,
416 self.padding, self.dilation, self.groups)
417
/opt/conda/envs/fastai/lib/python3.8/site-packages/torch/utils/data/_utils/signal_handling.py in handler(signum, frame)
64 # This following call uses `waitid` with WNOHANG from C side. Therefore,
65 # Python can still get and update the process status successfully.
---> 66 _error_if_any_worker_fails()
67 if previous_handler is not None:
68 previous_handler(signum, frame)
RuntimeError: DataLoader worker (pid 1862) is killed by signal: Killed.
How do I fix this? Whyād I get this problem so early on in the first place? Thanks!
UPDATE:
I deleted and remade the notebook, following the above steps (before the runtime error) and now everything is working as intended. Not sure what happened in the first place, but this was my fix.
1 Like
Hello, I want to use tex fonts for my matplotlib plots on Gradient. How can I install them on the server? Now I am just getting an error that latex is not found when i try to plot with tex fonts
Iām on a paid Paperspace plan and using the fastaiv2 notebooks.
Following the 10_nlp.ipynb, when running
learn.save('1epoch') I get a āFile system is read-onlyā error.
It seems that learn.path is Path('/storage/data/imdb'), which is read-only.
I can easily set learn.path to something else (e.g., Path(ā/storage/models/imdbā)) to solve this immediate issue.
However, I am concerned that doing so might have other implications (for example, will that cause problems with loading data?).
What is the recommended approach to solve this issue?
Thanks
Thanks for the tip re wandb, was running into this problem myself. I hope itāll be implemented soon, but itās been many months since your comment and still no tensorboard.
1 Like
Trying the same, and doesnāt work 
Just double checked after a full restart of the Notebook and it works : /voila/render/ instead of /notebook/
1 Like
You could change the file access modifiers for the relevant folders and files with chmod +w /storage/readonlyfile or just save to another location.
Thanks. But, the filesystem is read-only, so I cannot just change the protections using chmod.
Are we supposed to run the first cell in 01_intro notebook?
#hide
!pip install -Uqq fastbook
import fastbook
fastbook.setup_book()
ERROR: After October 2020 you may experience errors when installing or updating packages. This is because pip will change the way that it resolves dependency conflicts.
We recommend you use --use-feature=2020-resolver to test your packages with the new resolver before it becomes the default.
fastai 2.0.18 requires fastcore<1.3,>=1.1, but you'll have fastcore 1.3.0 which is incompatible.
Hey; trying out Paperspace Gradient using the fast.ai Deep Learning for Coders course and almost immediately hit an issue where the free instance types donāt seem to be available for me. Is it something I did wrong in navigating the user interface, or is it simply that the pool of free instances is currently exhausted and I need to wait? Just trying to understand what my options are.
Happy to provide more screenshots of what Iām seeing if what Iām seeing is unusual. Seems entirely likely that someone out there will know exactly whatās going on, except I didnāt see anything in the forums already. 