Table Of Contents

Next topic

Release Notes

This Page

Welcome

Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Theano features:

  • tight integration with numpy – Use numpy.ndarray in Theano-compiled functions.
  • transparent use of a GPU – Perform data-intensive calculations up to 140x faster than with CPU.(float32 only)
  • symbolic differentiation – Let Theano do your derivatives.
  • speed and stability optimizations – Get the right answer for log(1+x) even when x is really tiny.
  • dynamic C code generation – Evaluate expressions faster.
  • extensive unit-testing and self-verification – Detect and diagnose many types of mistake.

Theano has been powering large-scale computationally intensive scientific investigations since 2007. But it is also approachable enough to be used in the classroom (IFT6266 at the University of Montreal).

Download

We recommend the latest development version, available via:

hg clone http://hg.assembla.com/theano Theano

The theano subfolder should be on your $PYTHONPATH. For more information about installation and configuration, see installing Theano.

Documentation

Roughly in order of what you’ll want to check out:

You can download the latest PDF documentation, rather than reading it online.

Check out how Theano can be used for Machine Learning: Deep Learning Tutorials.

A Scipy conference paper that describe Theano.

Community

  • Register and post to theano-users if you want to talk to all Theano users.
  • Register and post to theano-dev if you want to talk to the developers.
  • Register and post to theano-announce if you want to be keep informed on important change on theano(low volume).
  • Register and post to theano-buildbot if you want to receive our daily buildbot email.
  • We try to stay organized with Theano’s Trac
  • Come visit us in Montreal! Most of the developers are students in the LISA group at the University of Montreal.