XAIN is an open source framework for federated learning.
The XAIN project is building a GDPR-compliance layer for machine learning. The approach relies on federated machine learning (FedML) as enabling technology that removes compliance-related adoption barriers of AI applications used in production.
At present, the source code in this project demonstrates the effectiveness of our FedML implementation on well known benchmarks using a realistic deep learning model structure. We will soon add a link to details on those experiments.
In the future, we will open source here a first minimal viable product for this layer. And we will add links to articles and papers that describe our approaches to networking, architecture, and privacy-preserving technology. We will also provide references to legal opinions about how and why our compliance layer for machine learning meets the demands of GDPR.
POLITE NOTE: We want to point out that running the benchmarks as described below is consuming considerable resources. XAIN cannot take any responsibilities for costs that arise for you when you execute these demanding machine-learning benchmarks.
XAIN requires Python 3.6+. To install the
xain-fl package just run:
$ python -m pip install xain-fl
XAIN can also be installed with GPU support through the
gpu extra feature. To
xain-fl package with support for GPUs just run:
$ python -m pip install xain-fl[gpu]
Running training sessions and benchmarks
Install from source
For development we require some extra system dependencies:
- clang-format 8+
sudo apt install clang-format
brew install clang-format
Clone Repository & Install XAIN in development mode
To clone this repository and to install the XAIN project, please execute the following commands:
$ git clone https://github.com/xainag/xain-fl.git $ cd xain-fl $ python -m pip install -e .[dev]
You can verify the installation by running the tests
Building the Documentation
The project documentation resides under
docs/. To build the documentation
$ cd docs/ $ make docs
The generated documentation will be under
docs/_build/html/. You can open the
root of the documentation by opening
docs/_build/html/index.html on your
Related Papers and Articles
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