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.
• 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:

• Installing Theano – How to install Theano.
• Theano at a Glance – What is Theano?
• Tutorial – Learn the basics.
• Library Documentation – Theano’s functionality, module by module.
• Optimizations – Guide to Theano’s graph optimizations.
• Extending Theano – Learn to add a Type, Op, or graph optimization.
• Internal Documentation – How to maintaining Theano, LISA-specific tips, and more...
• API – The automatically-generated API

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.

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.
• 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.