This repo is used for fastai development. fastai v2 is being developed in the dev
folder. Docs are at http://dev.fast.ai .
You can get all the necessary dependencies by simply installing fastai v1: conda install -c fastai -c pytorch fastai
. Or alternatively you can automatically install the dependencies into a new environment:
cd fastai_dev
conda env create -f environment.yml
Then, you can install fastai v2 with pip: pip install git+https://github.com/fastai/fastai_dev
. Or clone this repo, cd to its directory, and pip install -e .
for an editable install (which is probably the best approach at the moment, since fastai v2 is under heavy development).
To use fastai2.medical.imaging
you'll also need to:
conda install pyarrow
pip install pydicom kornia opencv-python
To run the tests in parallel, do something like this:
for i in {0,1,2}*.ipynb; do sleep 1; python run_notebook.py --fn $i & done
After you clone this repository, please run tools/run-after-git-clone
in your terminal. This sets up git hooks, which clean up the notebooks to remove the extraneous stuff stored in the notebooks (e.g. which cells you ran) which causes unnecessary merge conflicts.
Before submitting a PR, check that the local library and notebooks match. The script diff_nb_script.py
can let you know if there is a difference between the local library and the notebooks.
- If you made a change to the notebooks in one of the exported cells, you can export it to the library with
notebook2script.py
. - If you made a change to the library, you can export it back to the notebooks with
script2notebook.py
.