github pymc-devs/pymc v5.0.0

latest releases: v5.18.0, v5.17.0, v5.16.2...
23 months ago

What's Changed

In this major release we are switching our graph computation backend from Aesara to PyTensor, which is a fork of Aesara under PyMC governance.
Read the full announcement here: PyMC is Forking Aesara to PyTensor.

The switch itself should be rather seamless and you can probably just update your imports:

import aesara.tensor as at       # old (pymc >=4,< 5)
import pytensor.tensor as pt     # new (pymc >=5)

If you encounter problems updating please check the latest Discussions and don't hesitate to get in touch.

Major Changes 🛠

  • ⚠ Switched the graph backend from Aesara to PyTensor
  • Merged AePPL into a new logprob submodule. Dispatch methods can be found in logprob.abstract
  • ⚠ The log_likelihood, needed for arviz.compare is no longer computed by default. It can be added with idata = pm.compute_log_likelihood(idata) or using pm.sample(idata_kwargs=dict(log_likelihood=True)) by @ricardoV94 in #6374
  • Changed Minibatch API by @ferrine in #6304
  • Fix ordering transformation for batched dimensions, and deprecate in favor of univariate_ordered and multivariate_ordered by @TimOliverMaier in #6255 and @ricardoV94 in #6375

New Features & Bugfixes 🎉

  • Support logp derivation in DensityDist when random function returns a PyTensor variable by @ricardoV94 in #6361
  • Added alternative parametrization for AsymmetricLaplace by @aloctavodia in #6337

Docs & Maintenance 🔧

New Contributors

Full Changelog: v4.4.0...v5.0.0

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