arrays. It can use GPUs and perform efficient symbolic differentiation.
This is a fork of the `original Theano library <https://github.com/Theano/Theano>`__ that is being
maintained by the `PyMC team <https://github.com/pymc-devs>`__.
arrays.
Features
========
- A hackable, pure-Python codebase
- Extensible graph framework suitable for rapid development of custom symbolic optimizations
- Extensible graph framework suitable for rapid development of custom operators and symbolic optimizations
- Implements an extensible graph transpilation framework that currently provides
compilation to C and JAX JITed Python functions
- Built on top of one of the most widely-used Python tensor libraries: Theano
compilation via C, `JAX <https://github.com/google/jax>`__, and `Numba <https://github.com/numba/numba>`__
- Based on one of the most widely-used Python tensor libraries: `Theano <https://github.com/Theano/Theano>`__
Getting started
===============
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@@ -119,7 +116,7 @@ For platform-specific installation information see the legacy documentation `her
Support
=======
The PyMC group operates under the NumFOCUS umbrella. If you want to support us financially, you can donate `here <https://numfocus.salsalabs.org/donate-to-pymc3/index.html>`__.
The PyMC group operates under the NumFOCUS umbrella. If you want to support us financially, donate `here <https://numfocus.salsalabs.org/donate-to-pymc3/index.html>`__.
