|Developer(s)||Montreal Institute for Learning Algorithms (MILA), University of Montreal|
1.0.5 / 27 July 2020
|Written in||Python, CUDA|
|Platform||Linux, macOS, Windows|
|Type||Machine learning library|
|License||The 3-Clause BSD License|
Theano is a Python library and optimizing compiler for manipulating and evaluating mathematical expressions, especially matrix-valued ones. In Theano, computations are expressed using a NumPy-esque syntax and compiled to run efficiently on either CPU or GPU architectures.
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. Theano 1.0.0 was then released on 15 November 2017.
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.
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)
- "Theano Release". Retrieved 16 August 2020.
- 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.
- "Github Repository".
- Lamblin, Pascal (28 September 2017). "MILA and the future of Theano". theano-users (Mailing list). Retrieved 28 September 2017.
- "Release Notes – Theano 1.0.0 documentation".
- Developers, PyMC (1 June 2019). "Theano, TensorFlow and the Future of PyMC". Medium. Retrieved 27 August 2019.
- "Theano Documentation Release 1.0.0" (PDF). LISA lab, University of Montreal. 21 November 2017. p. 22. Retrieved 31 August 2018.
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