This repository contains the experimental results for our paper "On Neural Network Equivalence Checking using SMT solvers"
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Install docker from https://docs.docker.com/get-docker/. Please choose the docker version based on the OS and specifications of your machine.
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Make sure that docker is working correctly and is enabled/running. In macOS and Windows, this can be done simply by double clicking on the Docker app. In Linux, the user might need to run from the terminal e.g.
service docker start
- Download or Clone current repository. In case you have Git installed you can run from terminal:
git clone https://github.com/hariselef/NNequiv_Experiments.git
or
git clone git@github.com:hariselef/NNequiv_Experiments.git
- Once you have downloaded the source code (from the repository), you need to open a terminal (console, command window, command prompt) and move to the directory you have placed the code, e.g.
cd NNequiv Experiments
- he next step is to create (build) the docker container. This step depends heavily on the computer resources and the internet speed. It might vary from 10 minutes up to 1 hour. Run in the terminal:
docker image build -t nnequiv .
In the previous section, we downloaded and setup the docker container. The commands to run the code as displayed below.
- Run the docker via
docker run -it nnequiv
- Setup the anaconda environment that contains the necessary python libraries/dependencies with
conda activate nnequiv
- Run individual scripts which contain the results reported in the paper. Each script corresponds to a Table. You can type
python src/<Table name>.py
e.g. python src/Table_1.py
Available Table names: Table_1, Table_2, Table_3, Table_4, Table_5, Table_6, Table_7 & Table_9
@InProceedings{10.1007/978-3-031-15839-1_14,
author="Eleftheriadis, Charis
and Kekatos, Nikolaos
and Katsaros, Panagiotis
and Tripakis, Stavros",
title="On Neural Network Equivalence Checking Using SMT Solvers",
booktitle="Formal Modeling and Analysis of Timed Systems",
year="2022",
publisher="Springer International Publishing",
address="Cham",
pages="237--257",
isbn="978-3-031-15839-1"
}