This chapter describes common setup steps that are needed to run applications in different ML frameworks.
4.1. 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.
Create a Python virtual environment.
$ virtualenv -p python3 ~/graphcore/[venv_name]
[venv_name]is the name of the virtual environment.
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.
Deactivate the virtual environment with:
4.2. Running an application
You are now ready to run an application. Refer to the appropriate guide for the framework you are using: