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","."]
code: def from_name_parts(
      cls, namespace: str, op_name: str, overload: Optional[str] = None
  ) -> OpName:
      # NOTE: in PyTorch, the overload could be unprovided to indicate the
      # default overload
      # TODO: This is slightly unsafe that dev could accidentally create illegal
      # OpName by using initializer directly
      # https://github.com/pytorch/pytorch/pull/103943#discussion_r1256511069
      if overload is None or overload == "":
          overload = "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 1 for calling the OpName obj's underlying member method code with example usage: obj.from_name_parts(cls, namespace, op_name, overload) and returns: cls