Theano is a numerical computation library for Python. Computations are expressed using a Numpy-like syntax and compiled to run efficiently on either CPU or GPU architectures. Theano uses a mathematical computational graph and optimized the graph to speed up the computations using optimized C code. As of release 1.0, Theano will no longer be actively developed.
Theano is a Python library for performing tensor calculations with a numpy-like syntax. Theano can be used to define, optimize, and evaluate mathematical expressions involving tensors (also see tensorflow). Some of the principal features of Theano that set it apart from other libraries have become commonplace in neural network and tensor math libraries:
- Integrates with Numpy and provides Numpy-like syntax to express models using mathematical syntax
- Represents calculations as computation graphs and optimizes graphs for better performance and memory utilization
- Utilizes GPU hardware for data-intensive calculations
- Performs high-order differentiation automatically (symbolically)
- Compiles computation graphs into C code for faster execution
Theano enables rapid building of large-scale computational codes with less cognitive overhead and more expressive syntax. However, it is easy enough to learn that it is used in several deep learning courses (including at the University of Montreal, where it was originally developed).
Several projects build on top of Theano, including keras and lasagne.
As of Theano 1.0, Theano will no longer be under active development. See announcement on mailing list.
- Theano project home page
- github.com/Theano/Theano - Theano source code repository
- Theano Google Group - where developers provide most feedback/support
- Theano software wikipedia page
- Related projects - projects building on top of Theano functionality
Theano is named after a high priestess of Athena in the city of Troy, from Homer's Iliad.