pymc-devs/pymc

AI Summary: Implement a pre-sampling check in PyMC to verify consistency between model coordinates and variable shapes, raising an error before sampling begins if inconsistencies are detected. This involves testing the conversion of the model's initial point (or a single prior draw) to an InferenceData object.

AI Summary: The task involves extending PyMC's dimensionality support for distributions. This includes implementing existing univariate and multivariate distributions to handle multiple dimensions, and addressing the complexities of distribution factories like `Mixture`, `Truncated`, and `Censored` by creating an `extend_dist_dims` function.