docstr: Sample parameter values from prior. Modifies the module's parameters in-place.
code: def sample_from_prior(self, prior_name):
      """Sample parameter values from prior. Modifies the module's parameters in-place."""
      if prior_name not in self._priors:
          raise RuntimeError(
              "Unknown prior name '{}'".format(prior_name)
          )
      prior, _, setting_closure = self._priors[prior_name]
      if setting_closure is None:
          raise RuntimeError(
              "Must provide inverse transform to be able to sample from prior."
          )
      setting_closure(self, prior.sample())
  
imports: import copy
  import inspect
  import itertools
  import operator
  from collections import OrderedDict
  from typing import Union
  import torch
  from linear_operator.operators import LinearOperator
  from torch import nn, Tensor
  from torch.distributions import Distribution
  from .constraints import Interval
label_desc: Use image node_id 26 for calling the Module obj's underlying member method code with example usage: obj.sample_from_prior(prior_name) without return types