Welcome#

PyTensor is a Python library that allows you to define, optimize/rewrite, and evaluate mathematical expressions involving multi-dimensional arrays efficiently.

Some of PyTensor’s features are:

  • Tight integration with NumPy - Use numpy.ndarray in PyTensor-compiled functions

  • Efficient symbolic differentiation - PyTensor efficiently computes your derivatives for functions with one or many inputs

  • Speed and stability optimizations - Get the right answer for log(1 + x) even when x is near zero

  • Dynamic C/JAX/Numba code generation - Evaluate expressions faster

PyTensor is based on Theano, which has been powering large-scale computationally intensive scientific investigations since 2007.

Warning

Much of the documentation hasn’t been updated and is simply the old Theano documentation.

Download#

PyTensor is available on PyPI, and can be installed via pip install PyTensor.

Those interested in bleeding-edge features should obtain the latest development version, available via:

git clone git://github.com/pymc-devs/pytensor.git

You can then place the checkout directory on your $PYTHONPATH or use python setup.py develop to install a .pth into your site-packages directory, so that when you pull updates via Git, they will be automatically reflected the “installed” version. For more information about installation and configuration, see installing PyTensor.

Documentation#

Roughly in order of what you’ll want to check out:

Community#