The fastai library v1 is now available on Kernels!
1. learn.save gives error
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
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
- 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.
Lesson-Wise Notebook Links:
- Lesson-1 Pets
- Lesson 2 Download
- Lesson 2 SGD
- Lesson 3 Camvid-tiramisu
Lesson 3 Camvid
Note: Known issue, notebook needs more fine-tuning since its slightly compute demanding
- Lesson 3 Head-Pose
Lesson 3 Planet
Note: Learn.export error is a known issue.
- Lesson 3 Tabular
- Lesson 4 Collab
- Lesson 4 Tabular
- Lesson 5 SGD-MNIST
- Lesson 6 Pets-more
- Rossmann data clean
- Lesson 6 Rossmann
- Lesson 7 Human-numbers
- Lesson 7 Resnet MNIST