class_docstr: Meta information about the module call stack.
  
  This class is used to represent the module call stack information in a more
  structured way. It parses raw module stack information from `node.meta["nn_module_stack"]`.
  
  Example of raw module stack information:
  
      If produced by dynamo:
  
          {
              'L__self___h_1': (
                  "L['self'].h[1]",
                  <class 'transformers.models.gpt2.modeling_gpt2.GPT2Block'>
              ),
              'L__self___h_1_attn': (
                  "L['self'].h[1].attn",
                  <class 'transformers.models.gpt2.modeling_gpt2.GPT2Attention'>
              )
          }
  
      If produced by fx.symbolic_trace:
  
          {
              'h.1': <class 'transformers.models.gpt2.modeling_gpt2.GPT2Block'>,
              'h.1.attn': <class 'transformers.models.gpt2.modeling_gpt2.GPT2Attention'>
          }
class_docstr_tok: ["Meta","information","about","the","module","call","stack",".","This","class","is","used","to","represent","the","module","call","stack","information","in","a","more","structured","way",".","It","parses","raw","module","stack","information","from","`","node.meta","[","``","nn_module_stack","''","]","`",".","Example","of","raw","module","stack","information",":","If","produced","by","dynamo",":","{","'L__self___h_1","'",":","(","``","L","[","'self","'","]",".h","[","1","]","''",",","<","class","'transformers.models.gpt2.modeling_gpt2.GPT2Block","'",">",")",",","'L__self___h_1_attn","'",":","(","``","L","[","'self","'","]",".h","[","1","]",".attn","''",",","<","class","'transformers.models.gpt2.modeling_gpt2.GPT2Attention","'",">",")","}","If","produced","by","fx.symbolic_trace",":","{","'","h.1","'",":","<","class","'transformers.models.gpt2.modeling_gpt2.GPT2Block","'",">",",","'","h.1.attn","'",":","<","class","'transformers.models.gpt2.modeling_gpt2.GPT2Attention","'",">","}"]
code: def __getitem__(self, index: int) -> _ModuleMeta:
      return self._module_stack[index]
  
imports: from __future__ import annotations
  import abc
  import collections
  import copy
  import operator
  from typing import Any, Dict, Final, Generator, Iterator, List, Optional, Sequence, Set, Tuple, Union
  import torch
  import torch.fx
  from torch.onnx._internal import _beartype
  from torch.onnx._internal.fx import _pass
  from torch.utils import _pytree
label_desc: Use image node_id 3 for calling the _ModuleStackMeta obj's underlying member method code with example usage: obj.__getitem__(index) and returns: self