The HELA (Homomorphic Encryption Learnable Approximations) is an open-source library to accelerate the design of homomorphic encryption compliant neural networks. This is possible by:
- substituting the neural network's modules.
- customizing the behaviour of approximated modules.
- organizing network training in a customizable pipeline, eventually with more than one approximation steps.
- saving training pipeline logs and checkpoints in a single tidy experiment folder.
The package can be installed, for local development, with:
pip install -e .[dev,rdkit]To avoid the installation of the RDKit dependency:
pip install -e .[dev]Eventually, the RDKit dependency can be installed via Conda or Pypi:
# Install RDKit from Conda
conda install -c conda-forge rdkit
# Install RDKit from Pypi
pip install rdkit
# for Python<3.7
# pip install rdkit-pypi