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Reimplementing Unirep in JAX

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


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


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