ezkl-testbench

Code for collecting ezkl performance metrics on Zero-Knowledge Proof generation over inference tasks for multiple deep neural network models following a previously-introduced methodology¹.

Usage

The entrypoint main.py provides a command-line interface powered by Hydra, which exposes configuration options that can be listed using the --help flag:

$ python src/main.py --help

Details on important settings are provided below.

model

Controls which neural network model is used for proof generation and verification. It accepts a list of strings, corresponding to the names of the models to be used. For a list of supported models, see model.py. If left unspecified (default), all models will be used.

Footnotes

1. Cerioli, L.: A survey on Zero Knowledge proofs and their applications on machine learning. Master’s thesis, Politecnico di Milano, Scuola di Ingegneria Industriale e dell’Informazione (5 2023), https://hdl.handle.net/10589/209893 ↩