code: def to_random_module(self):
      random_module_cls = type(
          "_Random" + self.__class__.__name__,
          (RandomModuleMixin, self.__class__),
          {},
      )
      if not isinstance(self, random_module_cls):
          new_module = copy.deepcopy(self)
          new_module.__class__ = random_module_cls  # hack
      else:
          # Unclear if this branch would ever get used in practice, but it semantically makes sense to have.
          new_module = copy.deepcopy(self)
  
      for mname, child in new_module.named_children():
          if isinstance(child, Module):
              setattr(new_module, mname, child.to_random_module())
  
      return new_module
  
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 28 for calling the Module obj's underlying member method code with example usage: obj.to_random_module() and returns: new_module