pymc.Group.set_size_and_deterministic#
- Group.set_size_and_deterministic(node, s, d, more_replacements=None)[source]#
Dev - after node is sampled via
symbolic_sample_over_posterior()
orsymbolic_single_sample()
new random generator can be allocated and applied to node.- Parameters:
- node
PyTensor node(s) with symbolically applied VI replacements
- s: scalar
desired number of samples
- d: bool or int
whether sampling is done deterministically
- more_replacements: dict
more replacements to apply
- Returns:
Variable
orlist
with
applied
replacements
,ready
to
use