Using Chainer on a Mac is not supported, and I decided to use Docker because of the hassle of porting it when I want to run it on a server after Iā€™ve created something.

$ brew install docker $ brew cask install docker $ docker run -p 8888:8888 --name ml -it asashiho/ml-jupyter-python3

If you want to access data files, results files, etc. from the outside, Bind mounts instead of Volumes seems to be the way to go.

$ docker run -p 8888:8888 --name ml -it --mount type=bind,source=/Users/nishio,target=/notebooks/home asashiho/ml-jupyter-python3

memo

  • Chainer is not included.
  • pip is old
    • You should consider upgrading via the ā€˜pip install ā€”upgrade pipā€™ command.
    • pip install ā€”upgrade pip

  • Iā€™ll be about 30% slower.

This page is auto-translated from [/nishio/Docker for Mac](https://scrapbox.io/nishio/Docker for Mac) using DeepL. If you looks something interesting but the auto-translated English is not good enough to understand it, feel free to let me know at @nishio_en. Iā€™m very happy to spread my thought to non-Japanese readers.