This video walks through the instructions for setting up the compute environment for the FSDL 2022 labs. These instructions assume that you have a Linux machine with a GPU available that you can SSH into. If that's not you, then we recommend that you stick with Colab. So check out that video for your instructions.
Couple of side notes. If you have a Windows machine with a GPU and you have Windows Subsystem Linux 2, you're welcome to try out these instructions, but we can't guarantee they'll work. Cuz Windows Subsystem Linux with GPU support is a very fresh technology with sharp edges. You can read more about it there.
If you have a Mac with an Apple Silicon GPU, don't even try to install a deep learning stack on it. A lot of good engineers have spent a lot of hours Trying to get libraries to compile and run on that hardware, just run things on Colab.
So the instructions for local development can be found on GitHub here. in order to use them, the first step is to check that repo out. So I'm doing this on a fresh Ubuntu machine.
And once we've cloned the repo, we can go inside, take a look at it.
The next step is to set up the Python environment using Anaconda, which is our system package and Python environment manager.
So to install it, you can follow the instructions at that link to install a Python 3.7 version of miniconda. If you install another version, it's okay. You'll just have multiple versions of Python on your machine.
If you only have terminal access to your machine, then you'll need to use something like wget to get the installer for miniconda. Otherwise the instructions will direct you how to do it via your graphical user interface.
You can run the installer from the command line. You just need to type bash and then the name of the installer file that you downloaded.
You can accept the default options