class_docstr: Backend is the entity that will take an ONNX model with inputs,
  perform a computation, and then return the output.
  
  For one-off execution, users can use run_node and run_model to obtain results quickly.
  
  For repeated execution, users should use prepare, in which the Backend
  does all of the preparation work for executing the model repeatedly
  (e.g., loading initializers), and returns a BackendRep handle.
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code: def is_compatible(
      cls, model: ModelProto, device: str = "CPU", **kwargs: Any
  ) -> bool:
      # Return whether the model is compatible with the backend.
      return True
  
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 Backend obj's underlying member method code with example usage: obj.is_compatible(cls, model, device) and returns: True