code: def __getattribute__(self, name: str) -> Any:
      if name == "__dict__":
          return super().__getattribute__(name)
      if "_module_dict" in self.__dict__:
          modules = self.__dict__["_module_dict"]
          if name in modules:
              return modules[name]
      if "_buffers" in self.__dict__:
          buffers = self.__dict__["_buffers"]
          if name in buffers:
              return buffers[name]
      if "_v" in self.__dict__:
          v = self.__dict__["_v"]
          if name in v:
              return v[name]
      # Adding this attribute mapping s.t if someone tries
      # to retrieve self._modules/self._parameters, we
      # can handle that here
      if "_attr_mapping" in self.__dict__:
          mapping = self.__dict__["_attr_mapping"]
          if name in mapping:
              return super().__getattribute__(mapping[name])
      return super().__getattribute__(name)
  
imports: import ivy
  from collections import OrderedDict
  from typing import Any, Dict, Iterator, List, Optional, Set, Tuple
  from ivy.functional.frontends.torch.nn.parameter import Parameter
  from ivy.functional.frontends.torch.tensor import Tensor
label_desc: Use image node_id 24 for calling the Module obj's underlying member method code with example usage: obj.__getattribute__(name) and returns: super, super, modules, buffers, v, super