class_docstr: BackendRep is the handle that a Backend returns after preparing to execute
  a model repeatedly. Users will then pass inputs to the run function of
  BackendRep to retrieve the corresponding results.
class_docstr_tok: ["BackendRep","is","the","handle","that","a","Backend","returns","after","preparing","to","execute","a","model","repeatedly",".","Users","will","then","pass","inputs","to","the","run","function","of","BackendRep","to","retrieve","the","corresponding","results","."]
docstr: Abstract function.
docstr_tok: ["Abstract","function","."]
code: def run(self, inputs: Any, **kwargs: Any) -> Tuple[Any, ...]:
      """Abstract function."""
      return (None,)
  
file_path: onnx/onnx/backend/base.py
imports: from collections import namedtuple
  from typing import Any, Dict, NewType, Optional, Sequence, Tuple, Type
  import numpy
  import onnx.checker
  import onnx.onnx_cpp2py_export.checker
  from onnx import IR_VERSION, ModelProto, NodeProto
label_desc: Use image node_id 1 for calling the BackendRep obj's underlying member method code with example usage: obj.run(inputs) and returns: None