Metadata-Version: 1.1
Name: Theano
Version: 1.0.1
Summary: Optimizing compiler for evaluating mathematical expressions on CPUs and GPUs.
Home-page: http://deeplearning.net/software/theano/
Author: LISA laboratory, University of Montreal
Author-email: theano-dev@googlegroups.com
License: BSD
Description-Content-Type: UNKNOWN
Description: Theano is a Python library that allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays. It is built on top of NumPy_. Theano features:
        
         * **tight integration with NumPy:** a similar interface to NumPy's. numpy.ndarrays are also used internally in Theano-compiled functions.
         * **transparent use of a GPU:** perform data-intensive computations up to 140x faster than on a CPU (support for float32 only).
         * **efficient symbolic differentiation:** Theano can compute derivatives for functions of one or many inputs.
         * **speed and stability optimizations:** avoid nasty bugs when computing expressions such as log(1 + exp(x)) for large values of x.
         * **dynamic C code generation:** evaluate expressions faster.
         * **extensive unit-testing and self-verification:** includes tools for detecting and diagnosing bugs and/or potential problems.
        
        Theano has been powering large-scale computationally intensive scientific
        research since 2007, but it is also approachable enough to be used in the
        classroom (IFT6266 at the University of Montreal).
        
        .. _NumPy: http://numpy.scipy.org/
        
        
        =============
        Release Notes
        =============
        
        
        Theano 1.0.1 (6th of December, 2017)
        ====================================
        
        This is a maintenance release of Theano, version ``1.0.1``, with no new features, but some important bug fixes.
        
        We recommend that everybody update to this version.
        
        Highlights (since 1.0.0):
        
         - Fixed compilation and improved float16 support for topK on GPU
        
           - **NB**: topK support on GPU is experimental and may not work for large input sizes on certain GPUs
        
         - Fixed cuDNN reductions when axes to reduce have size ``1``
         - Attempted to prevent re-initialization of the GPU in a child process
         - Fixed support for temporary paths with spaces in Theano initialization
         - Spell check pass on the documentation
        
        A total of 6 people contributed to this release since ``1.0.0``:
        
         - Frederic Bastien
         - Steven Bocco
         - Arnaud Bergeron
         - Sam Johnson
         - Edward Betts
         - Simon Lefrancois
        
Keywords: theano math numerical symbolic blas numpy gpu autodiff differentiation
Platform: Windows
Platform: Linux
Platform: Solaris
Platform: Mac OS-X
Platform: Unix
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development :: Code Generators
Classifier: Topic :: Software Development :: Compilers
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
