Theano (software)

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Theano
Theano logo.svg
Developer(s)Montreal Institute for Learning Algorithms (MILA), University of Montreal
Initial release2007; 11 years ago (2007)
Stable release
1.0.3[1] / 17 September 2018; 2 months ago (2018-09-17)
Repositorygithub.com/Theano/Theano
Written inPython, CUDA
PlatformLinux, macOS, Windows
TypeMachine learning library
LicenseThe 3-Clause BSD License
Websitewww.deeplearning.net/software/theano/

Theano is a Python library and optimizing compiler for manipulating and evaluating mathematical expressions, especially matrix-valued ones.[2] In Theano, computations are expressed using a NumPy-esque syntax and compiled to run efficiently on either CPU or GPU architectures.

Theano is an open source project[3] primarily developed by a Montreal Institute for Learning Algorithms (MILA) at the Université de Montréal.[4]

On 28 September 2017, Pascal Lamblin posted a message from Yoshua Bengio, Head of MILA: major development would cease after the 1.0 release due to competing offerings by strong industrial players.[5] Theano 1.0.0 was then released on 15 November 2017.[6]

Sample code[edit]

The following code is the original Theano's example. It defines a computational graph with 2 scalars a and b of type double and an operation between them (addition) and then creates a python function f that does the actual computation.[7]

import theano
from theano import tensor

# declare two symbolic floating-point scalars
a = tensor.dscalar()
b = tensor.dscalar()

# create a simple expression
c = a + b

# convert the expression into a callable object that takes (a,b)
# values as input and computes a value for c
f = theano.function([a,b], c)

# bind 1.5 to 'a', 2.5 to 'b', and evaluate 'c'
assert 4.0 == f(1.5, 2.5)

[7]

See also[edit]

References[edit]

  1. ^ "Theano Release". Retrieved 17 September 2018.
  2. ^ Bergstra, J.; O. Breuleux; F. Bastien; P. Lamblin; R. Pascanu; G. Desjardins; J. Turian; D. Warde-Farley; Y. Bengio (30 June 2010). "Theano: A CPU and GPU Math Expression Compiler" (PDF). Proceedings of the Python for Scientific Computing Conference (SciPy) 2010.
  3. ^ "Github Repository".
  4. ^ "deeplearning.net".
  5. ^ Lamblin, Pascal (28 September 2017). "MILA and the future of Theano". theano-users (Mailing list). Retrieved 28 September 2017.
  6. ^ "Release Notes – Theano 1.0.0 documentation".
  7. ^ a b "Theano Documentation Release 1.0.0" (PDF). LISA lab, University of Montreal. 21 November 2017. p. 22. Retrieved 31 August 2018.

External links[edit]