docstr: For each parameter in this Module and submodule that have defined priors, sample a value for that parameter
  from its corresponding prior with a pyro.sample primitive and load the resulting value in to the parameter.
  
  This method can be used in a Pyro model to conveniently define pyro sample sites for all
  parameters of the model that have GPyTorch priors registered to them.
code: def pyro_sample_from_prior(self):
      """
      For each parameter in this Module and submodule that have defined priors, sample a value for that parameter
      from its corresponding prior with a pyro.sample primitive and load the resulting value in to the parameter.
  
      This method can be used in a Pyro model to conveniently define pyro sample sites for all
      parameters of the model that have GPyTorch priors registered to them.
      """
      new_module = self.to_pyro_random_module()
      return _pyro_sample_from_prior(
          module=new_module, memo=None, prefix=""
      )
  
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 29 for calling the Module obj's underlying member method code with example usage: obj.pyro_sample_from_prior() and returns: _pyro_sample_from_prior