Ma, Eric and Kummer, Arkadij (2020) Reimplementing Unirep in JAX. Reimplementing Unirep in JAX.

Abstract

UniRep is a recurrent neural network model
trained on 24 million protein sequences,
and has shown utility in protein engineering.
The original model, however, has rough spots in its implementation,
and a convenient API is not available for certain tasks.
To rectify this, we reimplemented the model in JAX/NumPy,
achieving near-100X speedups in forward pass performance,
and implemented a convenient API for specialized tasks.
In this article, we wish to document our model reimplementation process
with the goal of educating others interested in learning
how to dissect a deep learning model,
and engineer it for robustness and ease of use.

Item Type:	Article
Keywords:	jax, unirep, protein engineering, deep learning, machine learning
Date Deposited:	30 Sep 2020 00:45
Last Modified:	30 Sep 2020 00:45
URI:	https://oak.novartis.com/id/eprint/42299