Welcome¶
Theano is a Python library that allows your to define, optimize, and evaluate mathematical expressions involving multi-dime Nsional arrays efficiently. Theano Features:
- tight integration with NumPy –use numpy.ndarray in theano-compiled functions.
- Transparent use of the A GPU –perform data-intensive calculations up to 140x faster than with CPU. (float32 only)
- Efficient symbolic differentiation –theano Does your derivatives for function with one or many input S.
- 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 was also approachable enough to being used in the classroom (IFT6266 at the University of Montreal).
News¶
- We Support CuDNN If it's installed by the user.
- Open machine Learning Workshop presentation.
- Colin Raffel tutorial on Theano.
- Ian Goodfellow did a 12h class with exercises on Theano.
- Theano 0.6 was released. Everybody is encouraged to update.
- New Technical Report on Theano:Theano:new features and speed improvements.
- HPCs Tutorial. We included a few fixes discovered while doing the Tutorial.
You can watch a quick (minute) Introduction to Theano given as a talk at SciPy via streaming (or downloaded) video :
Transparent GPU Computing with Theano. James Bergstra, SciPy, June 30, 2010.
Download¶
Theano is now available on PyPI, and can be installed via easy_install Theano, pip install T Heano or by downloading and unpacking the tarball and typing python setup.py install.
Those interested in Bleeding-edge features should obtain the latest development version, available via:
git clone git://github.com/theano/theano.git
You can and place the checkout directory on your $PYTHONPATH or use python setup.py develop to the install a . PTH into your site-packages directory, so, if you pull updates via Git, they Would be automatically reflected the "installed" version. For more information about installation and configuration, see Installing Theano.
Status¶citing theano¶
If you use Theano for academic in the highly encouraged (though not required) to cite the following:
- F. Bastien, P. Lamblin, R. Pascanu, J. Bergstra, I. Goodfellow, A. Bergeron, N. Bouchard, D. Warde-farley and Y. Bengio. "Theano:new Features and speed improvements". NIPS Deep Learning Workshop. (BibTex)
- J. Bergstra, O. Breuleux, F. Bastien, p. Lamblin, R. Pascanu, G. Desjardins, J. Turian, D. Warde-farley and Y. Bengio. "Theano:a CPU and GPU Math Expression Compiler". Proceedings of the Python for scientific Computing Conference (SciPy) 2010. June 30-july 3, Austin, TX (BibTeX)
Theano is primarily developed by academics, and so citations matter a lot to us. As an added benefit, you increase Theano ' s exposure and potential user (and developer) base, which are to the benefit of AL L Users of Theano. Thanks in advance!
See our Theano citation Policy for details.
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.
- Frequently asked Questions –a set of commonly asked Questions.
- optimizations –guide to Theano ' s graph optimizations.
- extending Theano –learn to add a Type, Op, or graph optimization.
- Developer Start guide –how to contribute code to Theano.
- Theano Design and implementation documentation –primarily of interest to developers of Theano
- Internal Documentation –how to maintain Theano, lisa-specific tips, and more ...
- Release –how our release should work.
- Acknowledgements –what We took from the other projects.
- Related Projects–link to other Projects, implement new functionalities on top of Theano
You can download the latest PDF documentation, rather than reading it online.
Check out how Theano can is used for machine learning:deep learning tutorials.
Theano is featured at SciPy 2010.
Community¶
"Thank you to correcting it so quickly. I wish all packages I worked with would has such an active maintenance-this is as good as it gets:-) "
(Theano-users, 2, 2010)
- Register to Theano-announce if your want to is kept informed on important change on Theano (low volume).
- Register and post to the theano-users if you want to the all Theano users.
- Register and post to Theano-dev if you want to the developers.
- Register to Theano-github if your want to receive a email for all changes to the GitHub repository.
- Register to Theano-buildbot if your want to receive our daily Buildbot email.
- Ask/view questions/answers at Metaoptimize/qa/tags/theano (it's like stack Overflow for machine learning)
- We Use the Github tickets to keep track of issues (however, some old tickets can still is found on Assembla).
- Come Visit us in montreal! Most developers is students in the LISA group at the University of Montreal.
Theano is a Python library:a CPU and GPU math expression compiler
