How to Install

Installing Avalanche has Never Been so Simple

Avalanche has been designed for extreme portability and usability. Indeed, it can be run on every OS and native python environment. 💻🍎🐧

📦 Install Avalanche with Pip

you can install Avalanche with pip:

pip install avalanche-lib

This will install the core version of Avalanche, without extra packages (e.g., object detection support, reinforcement learning support). To install all the extra packages run:

pip install avalanche-lib[all]

You can install also specific extra packages by specifying the appropriate code name within the square brackets. This is the complete list of options:

pip install avalanche-lib[extra] # supports for specific functionalities (e.g. specific strategies)
pip install avalanche-lib[rl] # reinforcement learning support
pip install avalanche-lib[detection] # object detection support

Avalanche will raise an error if you need one extra package and will suggest the appropriate package to install.

Note that in some alternatives to bash like zsh you may need to enclose `avalanche-lib[code]` into quotation marks ( " " ), since square brackets are used as special characters.

Warning: by installing the [all] and [extra] versions, the PyTorch version may be limited to <2.* due to the dependencies of those additional packages.

📥 Install the Master Branch Using Pip

If you want, you can install Avalanche directly from the master branch (latest version) in a single command. Make sure to have pytorch already installed in your environment, then execute

pip install git+https://github.com/ContinualAI/avalanche.git

To update avalanche to the latest version, uninstall the package with pip uninstall avalanche-lib and then execute again the pip install command.

💻 Developer Mode Install

To help us to expand and improve Avalanche, you can install Avalanche in a fresh environment with the command

pip install -e ".[dev]"

This will install in editable mode, so that you can develop and modify the installed Avalanche package. It will also install the "extra" dev dependencies necessary to run tests and build the documentation.

🤝 Run it on Google Colab

You can run this chapter and play with it on Google Colaboratory: