Setting up Windows 10 for fast.ai part1v2
This is what worked for me (windows 10 box, with gtx 1070). It could be used as a tentative guideline for windows users.
a) Create a new anaconda env with python 3.6 and some additional packages:
>conda create -n fastai python=3.6 numpy cython statsmodels opencv
b) Install pytorch for cuda. If you already have a keras/TF setup which works only with cuda 8.0, and want to avoid headaches, you would rather install the cuda 8.0 version:
>conda install -c peterjc123 pytorch cuda80
However, keep us posted should you manage a successful installation of the cuda9 version alongside TF and cuda8
>pip install fastai
be patient, that will install a lot of stuff.
d) Now you are done, but you may want to install the ipython kernel in order to use lessons’ notebooks and do your own experiments. In my case:
>python -m ipykernel install --user --name fastai --display-name "fastAI custom"
That would be all.
Now, one may want to log in into such workstation remotely. In that case, there are various options, for example:
- Using remote desktop (mind that it’s slow if you have a slow or high-latency connection)
- Just leaving the notebook server on (unpractical: you would not be able to run administration tasks)
- Using “linux on windows” with tmux (install LoW from windows store)
Hope this helps.
Some users report various issues, which I will try to address as I hear of them.
bcolz: Shuld you get an error related to package
bcolz, it’s because it was installed via pip when you installed
fastai library, and the pip version doesn’t quite match. Remove it by
pip uninstall bcolz, then install it by
conda install bcolz. Quick test:
python -c "import bcolz"
torchvision: Should you get import errors related to
torchvision, install it with pip:
pip install torchvision.