The title says it all, however I have run into multiple problems using the Gradient Instance so far and I wanted to see if the problems were unique to me. I chose the Gradient Instance initially as I read that FastAI would work more smoothly on it compared to a Collab notebook.
So far I have two major issues: the first is the initial model training
Where the output I get is an issue with DataLoader: RuntimeError: DataLoader worker (pid 1220) is killed by signal: Killed.
A previous post covered that issue by suggesting using the argument num_workers=0, however running with that simply made my kernel shutdown which is why I am wondering if this is unique to Gradient on Paperspace.
Secondly, I chose Collab largely because I heard it didn’t support widgets. That being said when I tried to run the code cell for a simple upload button: uploader = widgets.FileUpload() uploader
I got a response that “widgets could not be found”. As someone who recently started with FastAI should I switch over to another notebook provider? Should I just skip ahead? Looking forward to any comments.
That’s a weird error indeed. Are you sure your instance has enough RAM and GPU RAM to run the code? Otherwise it’s possible that the kernel is dying because of lack of resources. Which instance are you using?
About Colab - you should check the Colab thread in the forum, I believe people have already found workarounds for the widgets.
Hi @robmel – Tom from Paperspace here. Are you launching your notebook on a GPU backed instance? The fastai course requires a GPU so if you’re utilizing our free option that means you must choose either a Free-GPU or Free-P5000 but no the Free-CPU instance.
@tomg I set up a free GPU instance and used it for a little while only to find it then changed to a CPU-only instance. This has happened twice now. The only solution I’ve found is to delete the CPU instance and start from scratch with a new free-GPU instance, losing any of my previous changes.
Is this expected behaviour or is something going wrong?
Hey Tom, sorry for the late reply I got absolutely swamped with work and only found time recently to get back into it. Yes it indeed seems that Free-CPU seems to be the problem, however like @thawkins mentioned, I originally set up a Free-P5000 so it seems strange about the switch, will delete and swap over and report what I find.
Hi @Fahimeh – this is not possible. Even with our free notebooks you always launch on the instance type you select. Sometimes the free tier fills up due to GPU demand and when this does happen you won’t be able to select a GPU but our launcher will never launch on CPU when a GPU is selected.
Hope this helps – should you experience abnormal behavior to the above please file a support ticket so that we may look deeper into this.
No the wierd thing is it’s not available in the list, whereas when I create a new notebook I get all sorts of machines available. I have reported it to Paperspace. They have reproduced it and working on helping me. Thanks.
You can save your work on /storage, so you can use it from multiple instances.
I have set up a free GPU notebook for training and a free CPU notebook when I know, I will only do inference, or try things with python and numpy. Both gradient notebooks have access to the same jupyter notebooks in my /storage folder. I hope this helps.
Another solution would be to use a git repository to save your changes to github or gitlab, or whatever you use.