pymc.model.core.Model.logp_dlogp_function#

Model.logp_dlogp_function(grad_vars=None, tempered=False, initial_point=None, ravel_inputs=None, **kwargs)[source]#

Compile a PyTensor function that computes logp and gradient.

Parameters:

grad_varslist of random variables, optional: Compute the gradient with respect to those variables. If None, use all free random variables of this model.
temperedbool: Compute the tempered logp free_logp + alpha * observed_logp. alpha can be changed using ValueGradFunction.set_weights([alpha]).