gituser/production/: theano-1.0.4 metadata and description

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Optimizing compiler for evaluating mathematical expressions on CPUs and GPUs.

author LISA laboratory, University of Montreal
author_email theano-dev@googlegroups.com
classifiers
  • Development Status :: 4 - Beta
  • Intended Audience :: Education
  • Intended Audience :: Science/Research
  • Intended Audience :: Developers
  • License :: OSI Approved :: BSD License
  • Programming Language :: Python
  • Topic :: Software Development :: Code Generators
  • Topic :: Software Development :: Compilers
  • Topic :: Scientific/Engineering :: Mathematics
  • Operating System :: Microsoft :: Windows
  • Operating System :: POSIX
  • Operating System :: Unix
  • Operating System :: MacOS
  • Programming Language :: Python :: 2
  • Programming Language :: Python :: 2.7
  • Programming Language :: Python :: 3
  • Programming Language :: Python :: 3.4
  • Programming Language :: Python :: 3.5
  • Programming Language :: Python :: 3.6
keywords theano math numerical symbolic blas numpy gpu autodiff differentiation
license BSD
provides_extras test
requires_dist
  • numpy (>=1.9.1)
  • scipy (>=0.14)
  • six (>=1.9.0)
  • Sphinx (>=0.5.1) ; extra == 'doc'
  • pygments ; extra == 'doc'
  • nose (>=1.3.0) ; extra == 'test'
  • parameterized ; extra == 'test'
  • flake8 ; extra == 'test'
File Tox results History
Theano-1.0.4-py2-none-any.whl
Size
3 MB
Type
Python Wheel
Python
2
Theano-1.0.4-py3-none-any.whl
Size
3 MB
Type
Python Wheel
Python
3

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).

Release Notes

Theano 1.0.4 (16th of January 2019)

This is a maintenance release of Theano, version 1.0.4, with no new features, but some important bug fixes.

We recommend that everybody update to this version.

Highlights (since 1.0.3):

  • Theano is now compatible with NumPy 1.16.

A total of 10 people contributed to this release since 1.0.3:

  • wonghang

  • Frederic Bastien

  • Arnaud Bergeron

  • Duc Nguyen

  • Andrew Nelson

  • Björn Linse

  • Luis Mario Domenzain

  • Rebecca N. Palmer

  • Luciano Paz

  • Dan Foreman-Mackey