Theano: A CPU and GPU Math Compiler in Python

TLDR

Theano is a Python compiler that translates high‑level, NumPy‑style mathematical expressions into optimized native code, enabling symbolic differentiation and delivering faster machine‑learning performance on CPUs and GPUs compared to traditional libraries. The paper demonstrates Theano’s usage, defines its scope, benchmarks its CPU and GPU performance, and explains its overall design. Theano optimizes expressions, translates them into C++ or CUDA, and compiles them into dynamically loaded Python modules before execution.

Abstract

Theano is a compiler for mathematical expressions in Python that combines the convenience of NumPy's syntax with the speed of optimized native machine language. The user composes mathematical expressions in a high-level description that mimics NumPy's syntax and semantics, while being statically typed and functional (as opposed to imperative). These expressions allow Theano to provide symbolic differentiation. Before performing computation, Theano optimizes the choice of expressions, translates them into C++ (or CUDA for GPU), compiles them into dynamically loaded Python modules, all automatically. Common machine learning algorithms implemented with Theano are from to faster than competitive alternatives (including those implemented with C/C++, NumPy/SciPy and MATLAB) when compiled for the CPU and between and faster when compiled for the GPU. This paper illustrates how to use Theano, outlines the scope of the compiler, provides benchmarks on both CPU and GPU processors, and explains its overall design.