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. ๐Ÿ’ป๐ŸŽ๐Ÿง

๐Ÿ“ฆ 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.

โฌ†๏ธ 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.

๐Ÿ Install the Master Branch Using Anaconda

We suggest you to use the pip package, but if you need some recent features you may want to install directly from the master branch. In general, the master branch is well tested and safe to use. However, the API of new features may change more frequently or break backward compatibility. Reproducibility is also easier if you use the pip package.
# choose your python version
python="3.8"
โ€‹
# Step 1
git clone https://github.com/ContinualAI/avalanche.git
cd avalanche
conda create -n avalanche-env python=$python -c conda-forge
conda activate avalanche-env
โ€‹
# Step 2
# Istall Pytorch with Conda (instructions here: https://pytorch.org/)
โ€‹
# Step 3
conda env update --file environment.yml
On Linux, alternatively, you can simply run the install_environment.sh in the Avalanche home directory. The script takes 2 arguments: --python and --cuda_version. Check --help for details.
You can test your installation by running the examples/test_install.py script. Make sure to include avalanche into your $PYTHONPATH if you are running examples with the command line interface.

๐Ÿ’ป Developer Mode Install

If you want to expand Avalanche and help us improve it (see the "From Zero to Hero" Tutorial). In this case we suggest to create an environment in developer-mode as follows (just a couple of more dependencies will be installed).
Assuming you have Anaconda (or Miniconda) installed on your system, you can follow these simple steps:
  1. 1.
    Install the avalanche-dev-env environment and activate it.
  2. 2.
    โ€‹Install Pytorch + TorchVision (follow the instructions on the website to use conda).
  3. 3.
    Update the Conda Environment.
These three steps can be accomplished with the following lines of code:
# choose you python version
python="3.8"
โ€‹
# Step 1
git clone https://github.com/ContinualAI/avalanche.git
cd avalanche
conda create -n avalanche-dev-env python=$python -c conda-forge
conda activate avalanche-dev-env
โ€‹
# Step 2
# Istall Pytorch with Conda (instructions here: https://pytorch.org/)
โ€‹
# Step 3
conda env update --file environment-dev.yml
On Linux, alternatively, you can simply run the install_environment_dev.sh in the Avalanche home directory. The script takes 2 arguments: --python and --cuda_version. Check --help for details.
You can test your installation by running the examples/test_install.py script. Make sure to include avalanche into your $PYTHONPATH if you are running examples with the command line interface.
That's it. now we have Avalanche up and running and we can start contribute to it!

๐Ÿค Run it on Google Colab

You can run this chapter and play with it on Google Colaboratory:
Google Colaboratory
Run the "How to Install" Chapter on Google Colab
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Outline
๐Ÿ“ฆ Install Avalanche with Pip
โฌ†๏ธ Install the Master Branch Using Pip
๐Ÿ Install the Master Branch Using Anaconda
๐Ÿ’ป Developer Mode Install
๐Ÿค Run it on Google Colab