Theano: A Python framework for fast computation of mathematical expressions

TL;DR

Theano is a Python library for efficient mathematical expression computation, widely used in machine learning for its performance and flexibility, supporting CPU and GPU acceleration since 2008.

Contribution

This paper provides a comprehensive overview of Theano's features, community, recent improvements, and performance comparisons with other frameworks.

Findings

Theano offers significant performance improvements over previous tools.

It has been adopted in numerous state-of-the-art machine learning models.

Theano's GPU support enhances computational efficiency.

Abstract

Theano is a Python library that allows to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Since its introduction, it has been one of the most used CPU and GPU mathematical compilers - especially in the machine learning community - and has shown steady performance improvements. Theano is being actively and continuously developed since 2008, multiple frameworks have been built on top of it and it has been used to produce many state-of-the-art machine learning models. The present article is structured as follows. Section I provides an overview of the Theano software and its community. Section II presents the principal features of Theano and how to use them, and compares them with other similar projects. Section III focuses on recently-introduced functionalities and improvements. Section IV compares the performance of Theano against Torch7 and TensorFlow on several machine learning models. Section V discusses current limitations of Theano and potential ways of improving it.