class_docstr: Find the OnnxFunction that matches the input/attribute dtypes by comparing them with their opschemas.
class_docstr_tok: ["Find","the","OnnxFunction","that","matches","the","input\/attribute","dtypes","by","comparing","them","with","their","opschemas","."]
docstr: Returns a tuple of (Rule, Level, message) for this Rule.
  
  Message template: 'The OnnxFunction: {symbolic_fn} is the nearest match of the node {node}.'
docstr_tok: ["Returns","a","tuple","of","(","Rule",",","Level",",","message",")","for","this","Rule",".","Message","template",":","'The","OnnxFunction",":","{","symbolic_fn","}","is","the","nearest","match","of","the","node","{","node","}",".","'"]
code: def format(  # type: ignore[override]
      self, level: infra.Level, symbolic_fn, node
  ) -> Tuple[infra.Rule, infra.Level, str]:
      """Returns a tuple of (Rule, Level, message) for this Rule.
  
      Message template: 'The OnnxFunction: {symbolic_fn} is the nearest match of the node {node}.'
      """
      return (
          self,
          level,
          self.format_message(symbolic_fn=symbolic_fn, node=node),
      )
  
imports: import dataclasses
  from typing import Tuple
  from torch.onnx._internal.diagnostics import infra
label_desc: Use image node_id 2 for calling the _FindOpschemaMatchedSymbolicFunction obj's underlying member method code with example usage: obj.format(level, symbolic_fn, node) and returns: self,  level,  self