The fastai library v1 is now available on Kernels!
Edit: Kernels were last updated on 24/2/2019
Note: The kernels are being maintained by @init_27
If anyone would like to contribute to the kernels, please ping @wdhorton or @init_27.
Kernels load datasets from ../input/ this is read only storage. If we create a learner from here and try learn.save() , the function tries to save in the same folder as the dataset. Hence the error.
Fix: Set the path in learn.save() accordingly.
2. I don’t see my kernel output files
To see the outputs, you need to “commit” the kernel, which will run the nb from end to end. Thus creating your output files.
3. Uploading custom datasets
You will need to create custom dataset by uploading it to kaggle datasets and then linking it to your kernel. Follow the kaggle kernels tutorial to understand this.
Hope these solve the pain points.
Please let me know if I’ve missed anything.
4. HTTP or Connection Errors
Ensure that Internet connection is enabled in your kernel, this might require you to complete filling your kaggle profile.
Once you’ve enabled it, you’ll have to restart your kernel
5. Bus errors
Try setting num_workers=0
Other Pitfalls:
Ensure GPU is enabled on your kernel
If you get strange errors/‘not defined errors’, its possible that the kernel hasn’t been updated to the latest, ping @init_27 for such a case.
thanks! i would be interested to access the kernels, as my attempt to run what’s your pet notebook in kernels resulted in 'RuntimeError: DataLoader worker (pid 114) is killed by signal: Bus error.
my kaggle username is: miwojc. thanks again!
Horton please add me to your kernel access list also I have a running lesson 1 notebook with the new fastai sw: https://www.kaggle.com/allanjackson/fastai-lesson-1-new-sw it is set to private for now and I will add you to my kernel access list. I was originally having the “bus error” but you have to set up the lesson 1 kernel from scratch -feel free to fork.
Kaggle name is Ajaxon6255 and I used your old fastai 0.7 kernels many times - thanks!
I will add @miwojc and @init_27 also.
I am in the process of running my Fastdotai Lesson 1 (new sw) Kernel from start to finish now on Kaggle. It has not shown the bus error. Martijn, did you have the buss error when running on the 17th or 18th of this month?
Google cloud servers had some issues on those days, but it may be entirely unrelated to bus errors you saw. I will add you to my lesson 1 kernel access (view and edit) and encourage you to fork it and run it in your Kaggle console. You will note that I have added a couple lines to help you check the fastai version and the torch version (both should be greater than 1). @init_27 and @wdhorton have all the other lessons that have an extra few bits of code that stop the bus error in the kernels they now have. (Oddly the few people on Kaggle that I gave access to my kernel - don’t seem to have access anymore according to my console). Access to my kernel (and theirs) is not public and will not be until the MOOC is publicly released. If you still get the bus error with my lesson 1 kernel after forking/committing/running in Kaggle please contact me and we will try to insure a proper execution for you (and the many others that will be using the kernels soon).
1). Good to hear about your pets file.
2). I can’t help with the solution file. (I haven’t written one yet).
3). Thank You for telling me about the error you were having with my lesson 7 NB. Sadly it was running great 24 days ago. I was getting errors today with larger batch sizes in cell #2. It ran 7/8 of the way through with batch size of 12. Then error with “Runtime Error: The size of tensor a (45) must match the size of tensor b (15) at non-singleton dimension 0”. I won’t put anyone on access for this version till I get it working again.
4). Yes today Kaggle version for fastai = 1.0.39
Thanks again for the Heads-up!
Access to my kernel (and theirs) is not public and will not be until the MOOC is publicly released. If you still get the bus error with my lesson 1 kernel after forking/committing/running in Kaggle please contact me and we will try to insure a proper execution for you (and the many others that will be using the kernels soon).