class_docstr: A class representing an operator name in internal ONNX converter.
class_docstr_tok: ["A","class","representing","an","operator","name","in","internal","ONNX","converter","."]
docstr: From a builtin function, e.g. operator.add, math.ceil, etc, get the OpName.
  
  FX graph uses built-in functions to caculate sympy expression. This function
  is used to get the OpName from a builtin function.
  
  Args:
      builtin_function (types.BuiltinFunctionType): operator.add, math.ceil, etc.
  
  Returns:
      OpName: _description_
docstr_tok: ["From","a","builtin","function",",","e.g",".","operator.add",",","math.ceil",",","etc",",","get","the","OpName",".","FX","graph","uses","built-in","functions","to","caculate","sympy","expression",".","This","function","is","used","to","get","the","OpName","from","a","builtin","function",".","Args",":","builtin_function","(","types.BuiltinFunctionType",")",":","operator.add",",","math.ceil",",","etc",".","Returns",":","OpName",":","_description_"]
code: def from_builtin_function(
      cls, builtin_function: types.BuiltinFunctionType
  ) -> OpName:
      """From a builtin function, e.g. operator.add, math.ceil, etc, get the OpName.
  
      FX graph uses built-in functions to caculate sympy expression. This function
      is used to get the OpName from a builtin function.
  
      Args:
          builtin_function (types.BuiltinFunctionType): operator.add, math.ceil, etc.
  
      Returns:
          OpName: _description_
      """
      op = builtin_function.__name__  # add, sub, etc.
      module = builtin_function.__module__  # _operators or math
      return cls.from_qualified_name(module + "::" + op)
  
file_path: pytorch/torch/onnx/_internal/fx/registration.py
imports: from __future__ import annotations
  import dataclasses
  import types
  from typing import Optional, TYPE_CHECKING, Union
  import torch._ops
  from torch.onnx._internal import _beartype
label_desc: Use image node_id 4 for calling the OpName obj's underlying member method code with example usage: obj.from_builtin_function(cls, builtin_function) and returns: cls