Metadata-Version: 2.1
Name: Theano
Version: 1.0.5
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
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
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Provides-Extra: test
Provides-Extra: doc
License-File: LICENSE.txt

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 1.0.5 (27th of July 2020)
================================

This is a maintenance release of Theano, version ``1.0.5``, with no
new features, but some deprecation fixes.

We recommend that everybody update to this version.

Highlights (since 1.0.4):

 - Theano is now compatible with Python 3.9
 - Fixed many deprecation warnings

A total of 13 people contributed to this release since ``1.0.4``:

 - 1fish2
 - Frederic Bastien
 - Rebecca Palmer
 - Miro Hrončok
 - Dan Foreman-Mackey
 - Adrian Seyboldt
 - abergeron
 - Tim Gates
 - Tim Odonnell
 - Robert P. Goldman
 - Duc Nguyen
 - Igor Varfolomeev
 - Thomas Wiecki


