def METHOD_NAME() -> 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)