code: def load_from_file(
      file_name, math_engine, input_layouts=None, output_layouts=None
  ):
      """Loads ONNX model from the given file
      Returns NeoML net and dictionary with additional info (input/output names, metadata, etc.)
  
      :param file_name: name of file to load from
      :type file_name: str
  
      :param math_engine: math engine to use in model
      :type math_engine: neoml.MathEngine.MathEngine
  
      :param input_layouts: custom layouts of ONNX model inputs. For more details see ONNX.ipynb tutorial.
      :type input_layouts: dict(str: list[str]) or None
  
      :param output_layouts: custom layouts of ONNX model outputs. For more details see ONNX.ipynb tutorial.
      :type output_layouts: dict(str: list[str]) or None
  
      :return: tuple(neoml.Dnn.Dnn, dict)
      """
      _validate_layouts(input_layouts)
      _validate_layouts(output_layouts)
      dnn = neoml.Dnn.Dnn(math_engine)
      model_info = PythonWrapper.load_onnx_from_file(
          file_name, dnn, input_layouts, output_layouts
      )
      return dnn, model_info
  
imports: import neoml.PythonWrapper
  import neoml.Dnn
label_desc: Use image node_id 2 for calling a global function with example usage: load_from_file(file_name, math_engine, input_layouts, output_layouts) and returns: dnn,  model_info