Installation#
This page describes how to install APPFL on a machine independent of operating systems.
Conda environment#
We highly recommend to create new conda environment and install the required packages for APPFL.
conda create -n APPFL python=3.8
conda activate APPFL
User installation#
For most users, including data scientists, this simple installation is sufficient for running the package.
pip install pip --upgrade
pip install "appfl[analytics,examples]"
If you want to even minimize the installation of package dependencies, you can use:
pip install appfl
Note
torch
may need to be updated manually to supprt CUDA. Please check GPU support in PyTorch.
Developer installation#
Code developers and contributors may want to work on the local repository. To set up the development environment,
git clone https://github.com/APPFL/APPFL.git
cd APPFL
pip install -e ".[dev,examples,analytics]"
On Ubuntu, if the installation process failed, you can try:
sudo apt install libopenmpi-dev,libopenmpi-bin,libopenmpi-doc