class_docstr: Missing symbolic function for custom PyTorch operator, cannot translate node to ONNX.
class_docstr_tok: ["Missing","symbolic","function","for","custom","PyTorch","operator",",","can","not","translate","node","to","ONNX","."]
docstr: Returns the formatted default message of this Rule.
  
  Message template: 'ONNX export failed on an operator with unrecognized namespace {op_name}. If you are trying to export a custom operator, make sure you registered it with the right domain and version.'
docstr_tok: ["Returns","the","formatted","default","message","of","this","Rule",".","Message","template",":","'ONNX","export","failed","on","an","operator","with","unrecognized","namespace","{","op_name","}",".","If","you","are","trying","to","export","a","custom","operator",",","make","sure","you","registered","it","with","the","right","domain","and","version",".","'"]
code: def format_message(self, op_name) -> str:  # type: ignore[override]
      """Returns the formatted default message of this Rule.
  
      Message template: 'ONNX export failed on an operator with unrecognized namespace {op_name}. If you are trying to export a custom operator, make sure you registered it with the right domain and version.'
      """
      return self.message_default_template.format(op_name=op_name)
  
imports: import dataclasses
  from typing import Tuple
  from torch.onnx._internal.diagnostics import infra
label_desc: Use image node_id 1 for calling the _MissingCustomSymbolicFunction obj's underlying member method code with example usage: obj.format_message(op_name) and returns: self