class_docstr: Find the list of OnnxFunction of the PyTorch operator in onnx registry.
class_docstr_tok: ["Find","the","list","of","OnnxFunction","of","the","PyTorch","operator","in","onnx","registry","."]
docstr: Returns the formatted default message of this Rule.
  
  Message template: 'Checking if the FX node: {node} is supported in onnx registry.'
docstr_tok: ["Returns","the","formatted","default","message","of","this","Rule",".","Message","template",":","'Checking","if","the","FX","node",":","{","node","}","is","supported","in","onnx","registry",".","'"]
code: def format_message(self, node) -> str:  # type: ignore[override]
      """Returns the formatted default message of this Rule.
  
      Message template: 'Checking if the FX node: {node} is supported in onnx registry.'
      """
      return self.message_default_template.format(node=node)
  
imports: import dataclasses
  from typing import Tuple
  from torch.onnx._internal.diagnostics import infra
label_desc: Use image node_id 1 for calling the _FindOperatorOverloadsInOnnxRegistry obj's underlying member method code with example usage: obj.format_message(node) and returns: self