Metadata-Version: 1.1
Name: Theano
Version: 1.0.0rc1
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 1.0.0rc1 (30th of October, 2017)
        =======================================
        
        This release contains new features, improvements and bug fixes to prepare the upcoming release.
        
        We recommend that every developer updates to this version.
        
        Highlights:
         - Make sure MKL uses GNU OpenMP
        
           - **NB**: Matrix dot product (``gemm``) with ``mkl`` from conda
             could return wrong results in some cases. We have reported the problem upstream
             and we have a work around that raises an error with information about how to fix it.
        
         - Optimized ``SUM(x^2)``, ``SUM(ABS(X))`` and ``MAX(ABS(X))`` operations with cuDNN reductions
         - Added Python scripts to help test cuDNN convolutions
         - Fixed invalid casts and index overflows in ``theano.tensor.signal.pool``
        
        A total of 71 people contributed to this release since 0.9.0, see list below.
        
        Commiters since 0.9.0:
         - Frederic Bastien
         - Steven Bocco
         - João Victor Tozatti Risso
         - Arnaud Bergeron
         - Mohammed Affan
         - amrithasuresh
         - Pascal Lamblin
         - Reyhane Askari
         - Alexander Matyasko
         - Shawn Tan
         - Simon Lefrancois
         - Adam Becker
         - Vikram
         - Gijs van Tulder
         - Faruk Ahmed
         - Thomas George
         - erakra
         - Andrei Costinescu
         - Boris Fomitchev
         - Zhouhan LIN
         - Aleksandar Botev
         - jhelie
         - xiaoqie
         - Tegan Maharaj
         - Matt Graham
         - Cesar Laurent
         - Gabe Schwartz
         - Juan Camilo Gamboa Higuera
         - Tim Cooijmans
         - Anirudh Goyal
         - Saizheng Zhang
         - Yikang Shen
         - vipulraheja
         - Florian Bordes
         - Sina Honari
         - Chiheb Trabelsi
         - Shubh Vachher
         - Daren Eiri
         - Joseph Paul Cohen
         - Laurent Dinh
         - Mohamed Ishmael Diwan Belghazi
         - Jeff Donahue
         - Ramana Subramanyam
         - Bogdan Budescu
         - Dzmitry Bahdanau
         - Ghislain Antony Vaillant
         - Jan Schlüter
         - Nan Jiang
         - Xavier Bouthillier
         - fo40225
         - mrTsjolder
         - wyjw
         - Aarni Koskela
         - Adam Geitgey
         - Adrian Keet
         - Adrian Seyboldt
         - Anmol Sahoo
         - Chong Wu
         - Holger Kohr
         - Jayanth Koushik
         - Lilian Besson
         - Lv Tao
         - Michael Manukyan
         - Murugesh Marvel
         - NALEPA
         - Rebecca N. Palmer
         - Zotov Yuriy
         - dareneiri
         - lrast
         - morrme
         - naitonium
        
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
