Log Message:
py-pymc3: updated to 3.11.6

PyMC 3.11.5 (14 March 2022)
Backports
+ The `pm.logp(rv, x)` syntax is now available and recommended to make your \ 
model code `v4`-ready. Note that this backport is just an alias and much less \ 
capable than what's available with `pymc >=4`
+ The `pm.Distribution(testval=...)` kwarg was deprecated and will be replaced \ 
by `pm.Distribution(initval=...)`in `pymc >=4`
+ The `pm.sample(start=...)` kwarg was deprecated and will be replaced by \ 
`pm.sample(initvals=...)`in `pymc >=4`
+ `pm.Lognormal` is now available as an alias for `pm.Lognormal`

Bugfixes
+ The upper limit for the SciPy version is `<1.8.0` and will most probably \ 
remain for all future `3.x.x` releases. For compatibility with newer SciPy \ 
versions please update to `pymc>=4.0.0`.
+ A hotfix is applied on import to remain compatible with NumPy 1.22

PyMC3 3.11.4 (20 August 2021)

New Features
+ Generalized BART, bounded distributions like Binomial and Poisson can now be \ 
used as likelihoods
+ `plot_gp_dist` is now available at the package level: `pm.plot_gp_dist`
+ The experimental JAX sampling was removed. It will be included in the upcoming \ 
`v4` release
+ `pm.intX` no longer downcasts integers unnecessarily

Maintenance
+ A deprecation warning from the `semver` package we use for checking backend \ 
compatibility was dealt with
+ `theano.printing.pydotprint` is now hotfixed upon import
+ Fix bug in the computation of the log pseudolikelihood values (SMC-ABC).
+ Fix `LKJCorr.random` method to work with `pm.sample_prior_predictive`.
+ Enable documentation generation via ReadTheDocs for upcoming v3 releases.
+ Remove `float128` dtype support
+ Use `to_tuple` function in `pm.fast_sample_posterior_predictive` to pass shape \ 
assertions