A package for optimization based neural network verification.
Project description
verifiNN
This project implements the training of deep linear networks from the ground up. We also intend to use it in investigating the loss landscape of deep linear networks and comparing it with other learning models, e.g. linear rigression. We hope to publish the results of our learing in the forrm of blog posts.
Prerequisites:
- python 3
- virtualenv
- pip
Instructions:
- set up the python virtual enviroment by running
setup.sh
- add the following entry to the
~/.bash_profile
fileexport PYTHONPATH="<path/to/parent/repo>:$PYTHONPATH"
- start up the python environment by
. ./venv/bin/activate
References:
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
No source distribution files available for this release.See tutorial on generating distribution archives.
Built Distribution
Close
Hashes for verifiNN-0.0.0.dev1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5917fde8dbba270f6abec8dfe4ae25fe653196bb519d830c4f4eb23f822804a6 |
|
MD5 | 0fe25fead5310cb45481801bb09d7204 |
|
BLAKE2b-256 | 889f6e06483a253ab1c12456fba05a6935eb76f0c49bc874d8bb8d95683bf73a |