class_docstr: Node is missing ONNX shape inference.
class_docstr_tok: ["Node","is","missing","ONNX","shape","inference","."]
docstr: Returns the formatted default message of this Rule.
  
  Message template: 'The shape inference of {op_name} type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function.'
docstr_tok: ["Returns","the","formatted","default","message","of","this","Rule",".","Message","template",":","'The","shape","inference","of","{","op_name","}","type","is","missing",",","so","it","may","result","in","wrong","shape","inference","for","the","exported","graph",".","Please","consider","adding","it","in","symbolic","function",".","'"]
code: def format_message(self, op_name) -> str:  # type: ignore[override]
      """Returns the formatted default message of this Rule.
  
      Message template: 'The shape inference of {op_name} type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function.'
      """
      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 _NodeMissingOnnxShapeInference obj's underlying member method code with example usage: obj.format_message(op_name) and returns: self