code: def named_hyperparameters(self):
      from .variational._variational_distribution import (
          _VariationalDistribution,
      )
  
      for module_prefix, module in self.named_modules():
          if not isinstance(module, _VariationalDistribution):
              for elem in module.named_parameters(
                  prefix=module_prefix, recurse=False
              ):
                  yield elem
  
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 12 for calling the Module obj's underlying member method code with example usage: obj.named_hyperparameters() without return types