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Description:
jaxcodex 0.0.1
CoDeX
CoDeX contains learned data compression tools for JAX.
You can use this library to build your own ML models with end-to-end optimized
data compression built in. It's useful to find storage-efficient representations
of your data (images, features, examples, etc.) while only sacrificing a small
fraction of model performance.
For a more in-depth introduction from a classical data compression perspective,
consider our paper on nonlinear transform
coding, or watch @jonycgn's talk on learned
image compression. For an
introduction to lossy data compression from a machine learning perspective, take
a look at @yiboyang's review paper.
Documentation & getting help
Please post all questions or comments on
Discussions. Only file
Issues for actual bugs or feature
requests. On Discussions, you may get a faster answer, and you help other people
find the question or answer more easily later.
Installation
To install CoDeX via pip, run the following command:
pip install jax-codex
To test that the installation works correctly, you can run the unit tests with:
python -m codex.all_tests
Once the command finishes, you should see a message 13 passed in 2.76s or
similar in the last line.
Usage
We recommend importing the library from your Python code as follows:
import codex as cdx
Citation
If you use this library for research purposes, please cite:
@software{codex_github,
author = "Ballé, Johannes and Hwang, Sung Jin and Agustsson, Eirikur",
title = "{CoDeX}: Learned Data Compression in {JAX}",
url = "http://github.com/google/codex",
version = "0.0.1",
year = "2022",
}
In the above BibTeX entry, names are top contributors sorted by number of
commits. Please adjust version number and year according to the version that was
actually used.
Note that this is not an officially supported Google product.
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
Customer Reviews
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