code: def generate_stub_file() -> str:
      import inspect
  
      import torch
      import torch.nn as nn
  
      _NO_WRAP_CLASSES = [
          # not an nn.Module
          "Parameter",
          "ParameterList",
          "UninitializedBuffer",
          "UninitializedParameter",
          # arguments are special
          "Module",
          "Sequential",
          # utilities
          "Container",
          "DataParallel",
      ]
  
      _WRAP_WITHOUT_TAG_CLASSES = [
          # special support on graph engine
          "ModuleList",
          "ModuleDict",
      ]
  
      code = [
          "# Copyright (c) Microsoft Corporation.",
          "# Licensed under the MIT license.",
          "# This file is auto-generated to make auto-completion work.",
          "# When pytorch version does not match, it will get automatically updated.",
          "# pylint: skip-file",
          "# pyright: reportGeneralTypeIssues=false",
          f"# _torch_version = {torch.__version__}",
          f"# _torch_nn_cache_version = 10",  # backward compatibility
          f"# _torch_nn_cache_sha1 = {cache_version}",
          "import typing",
          "import torch.nn as nn",
          "from .base import ParametrizedModule",
      ]
  
      # Add modules, classes, functions in torch.nn into this module.
      for name, obj in inspect.getmembers(torch.nn):
          if inspect.isclass(obj):
              if name in _NO_WRAP_CLASSES:
                  code.append(f"{name} = nn.{name}")
              elif not issubclass(obj, nn.Module):
                  # It should never go here
                  # We did it to play safe
                  warnings.warn(
                      f"{obj} is found to be not a nn.Module, which is unexpected. "
                      "It means your PyTorch version might not be supported.",
                      RuntimeWarning,
                  )
                  code.append(f"{name} = nn.{name}")
              elif name in _WRAP_WITHOUT_TAG_CLASSES:
                  # for graph model space
                  code.append(
                      f"class {name}(ParametrizedModule, nn.{name}, wraps=nn.{name}, copy_wrapped=True):\n    _nni_basic_unit = False"
                  )  # pylint: disable=line-too-long
              else:
                  code.append(
                      f"class Mutable{name}(ParametrizedModule, nn.{name}, wraps=nn.{name}): pass"
                  )
                  # for graph model space
                  code.append(
                      f"class {name}(ParametrizedModule, nn.{name}, wraps=nn.{name}, copy_wrapped=True): pass"
                  )
  
          elif inspect.isfunction(obj) or inspect.ismodule(obj):
              code.append(f"{name} = nn.{name}")  # no modification
  
      return "\n".join(code)
  
file_path: nni/nni/nas/nn/pytorch/layers.py
imports: import hashlib
  import os
  import warnings
  from pathlib import Path
label_desc: Use image node_id 2 for calling a global function with example usage: generate_stub_file() and returns: str