docstr: Returns an iterator over the module's priors, yielding the name of the prior,
  the prior, the associated parameter names, and the transformation callable.
  
  Yields:
      (string, Module, Prior, tuple((Parameter, callable)), callable): Tuple containing:
          - the name of the prior
          - the parent module of the prior
          - the prior
          - a tuple of tuples (param, transform), one for each of the parameters associated with the prior
          - the prior's transform to be called on the parameters
code: def named_priors(self, memo=None, prefix=""):
      """Returns an iterator over the module's priors, yielding the name of the prior,
      the prior, the associated parameter names, and the transformation callable.
  
      Yields:
          (string, Module, Prior, tuple((Parameter, callable)), callable): Tuple containing:
              - the name of the prior
              - the parent module of the prior
              - the prior
              - a tuple of tuples (param, transform), one for each of the parameters associated with the prior
              - the prior's transform to be called on the parameters
      """
      return _extract_named_priors(module=self, 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 13 for calling the Module obj's underlying member method code with example usage: obj.named_priors(memo, prefix) and returns: _extract_named_priors