Numerical computation library for Python
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.
History
Theano is an open source project[3] primarily developed by the Montreal Institute for Learning Algorithms (MILA) at the Université de Montréal.[4]
The name of the software references the ancient philosopher Theano, long associated with the development of the golden mean.
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]
On 17 May 2018, Chris Fonnesbeck wrote on behalf of the PyMC development team[7] that the PyMC developers will officially assume control of Theano maintenance once they step down. On 29 January 2021, they started using the name Aesara for their fork of Theano.[8]
On 29 Nov 2022, the PyMC development team[9] that the PyMC developers will fork the Aesara project under the name PyTensor.
Sample code
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.[10]
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)
