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Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.
Python Cuda C C++ Shell HTML
Latest commit 09605e7 lamblin Merge pull request #3683 from laurent-dinh/conv_infer_shape …
Factoring inference of convolution output shape (continuation)
To install the package, see this page: http://deeplearning.net/software/theano/install.html For the documentation, see the project website: http://deeplearning.net/software/theano/ Related Projects: https://github.com/Theano/Theano/wiki/Related-projects We recommend you look at the documentation on the website, since it will be more current than the documentation included with the package. If you really wish to build the documentation yourself, you will need epydoc and sphinx. Issue the following command: python ./doc/scripts/docgen.py Documentation is built into html/ The PDF of the documentation is html/theano.pdf DIRECTORY LAYOUT Theano (current directory) is the distribution directory. * Theano/theano contains the package * Theano/theano has several submodules: * gof + compile are the core * scalar depends upon core * tensor depends upon scalar * sparse depends upon tensor * sandbox can depend on everything else * Theano/examples are copies of the example on the wiki * Theano/benchmark and Theano/examples are in the distribution, but not in the Python package * Theano/bin contains executable scripts that are copied to the bin folder when the Python package is installed * Tests are distributed and are part of the package, i.e. fall in the appropriate submodules * Theano/doc contains files and scripts used to generate the documentation * Theano/html is the place where the documentation will be generated