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: When the name is <namespace>::<op_name>[.<overload>]
docstr_tok: ["When","the","name","is","<","namespace",">",":",":","<","op_name",">","[",".","<","overload",">","]"]
code: def from_qualified_name(cls, qualified_name: str) -> OpName:
      """When the name is <namespace>::<op_name>[.<overload>]"""
      namespace, opname_overload = qualified_name.split("::")
      op_name, *overload = opname_overload.split(".", 1)
      overload = overload[0] if overload else "default"
      return cls(namespace, op_name, overload)
  
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 2 for calling the OpName obj's underlying member method code with example usage: obj.from_qualified_name(cls, qualified_name) and returns: cls