7. Setup

This chapter describes common setup steps that are needed to run applications in different ML frameworks.

7.1. Working with a Python virtual environment

It is good practice to work in a different Python virtual environment for each framework or even for each application. This section describes how you can create, activate and deactivate a Python virtual environment.

  1. Create a Python virtual environment.

$ virtualenv -p python3 ~/graphcore/[venv_name]

where [venv_name] is the name of the virtual environment.

  1. Activate the virtual environment so you can use it.

$ source ~/graphcore/[venv_name]/bin/activate

Now all subsequent installations will be local to that virtual environment.

  1. Deactivate the virtual environment with:

$ deactivate