Optimizing compiler for evaluating mathematical expressions on CPUs and GPUs.
Project 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).
Release Notes
Theano 0.10.0beta3 (20th of September, 2017)
This release contains new features, improvements and bug fixes to prepare the upcoming release candidate.
We recommend that every developer updates to this version.
- Highlights:
conda packages now available and updated in our own conda channel mila-udem. To install it: conda install -c mila-udem/label/pre theano pygpu
Improved elemwise operations
Speed-up elemwise ops based on SciPy
Fixed memory leak related to elemwise ops on GPU
Improved pickling and tests in debug mode
Fixed pygpu detection
Bug fixes, crash fixes, warning improvements and documentation updates
A total of 69 people contributed to this release since 0.9.0, see list below.
- Interface changes:
Removed op ExtractDiag from theano.tensor.nlinalg, now only in theano.tensor.basic
- Convolution updates:
Added dilated causal convolutions for 2D
- New features:
Added unravel_index and ravel_multi_index functions on CPU
Implemented max() and min() functions for booleans and unsigned integers types
- Others:
Added R_op() for ZeroGrad
Added description for rnnblock
- Commiters since 0.9.0:
Frederic Bastien
João Victor Tozatti Risso
Arnaud Bergeron
Steven Bocco
Mohammed Affan
amrithasuresh
Pascal Lamblin
Reyhane Askari
Alexander Matyasko
Simon Lefrancois
Shawn Tan
Vikram
Gijs van Tulder
Thomas George
Andrei Costinescu
Faruk Ahmed
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
erakra
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
wyjw
Aarni Koskela
Adam Becker
Adam Geitgey
Adrian Keet
Adrian Seyboldt
Anmol Sahoo
Chong Wu
Holger Kohr
Jayanth Koushik
Lilian Besson
Lv Tao
Michael Manukyan
Murugesh Marvel
NALEPA
Zotov Yuriy
dareneiri
lrast
morrme
naitonium
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