High-level interface to TensorFlow Probability. Do not use for anything serious.

What works?

• Build most models you could build with PyMC3
• Sample using NUTS, all in TF, fully vectorized across chains (multiple chains basically become free)
• Automatic transforms of model to the real line
• Prior and posterior predictive sampling
• Deterministic variables
• Trace that can be passed to ArviZ

However, expect things to break or change without warning.

See here for an example: https://github.com/pymc-devs/pymc4/blob/master/notebooks/radon_hierarchical.ipynb See here for the design document: https://github.com/pymc-devs/pymc4/blob/master/notebooks/pymc4_design_guide.ipynb