code: def register_dataclass(cls: Type[Any]) -> None:
      """
      Registers a dataclass as a valid input/output type for :func:`torch.export.export`.
  
      Args:
          cls: the dataclass type to register
  
      Example::
  
          @dataclass
          class InputDataClass:
              feature: torch.Tensor
              bias: int
  
          class OutputDataClass:
              res: torch.Tensor
  
          torch.export.register_dataclass(InputDataClass)
          torch.export.register_dataclass(OutputDataClass)
  
          def fn(o: InputDataClass) -> torch.Tensor:
              res = res=o.feature + o.bias
              return OutputDataClass(res=res)
  
          ep = torch.export.export(fn, (InputDataClass(torch.ones(2, 2), 1), ))
          print(ep)
  
      """
  
      from torch._export.utils import register_dataclass_as_pytree_node
  
      return register_dataclass_as_pytree_node(cls)
  
imports: import builtins
  import copy
  import dataclasses
  import inspect
  import io
  import os
  import sys
  import typing
  import warnings
  from enum import auto, Enum
  from typing import Any, Callable, Dict, Iterator, List, Optional, Tuple, Type, TYPE_CHECKING, Union
  import torch
  import torch.fx._pytree
  import torch.utils._pytree
  from torch.fx._compatibility import compatibility
  from torch.fx.passes.infra.pass_base import PassResult
  from torch.fx.passes.infra.pass_manager import PassManager
  from torch.utils._pytree import FlattenFunc, FromDumpableContextFn, ToDumpableContextFn, UnflattenFunc
  from .dynamic_shapes import Constraint, Dim, dims, dynamic_dim
  from .exported_program import ExportedProgram, ModuleCallEntry, ModuleCallSignature
  from .graph_signature import ExportBackwardSignature, ExportGraphSignature
  from .unflatten import FlatArgsAdapter, unflatten, UnflattenedModule
label_desc: Use image node_id 4 for calling a global function with example usage: register_dataclass(cls) and returns: register_dataclass_as_pytree_node