code: def onnx_resize_backward(
      inputs,
      scales=(),
      sizes=(),
      mode=None,
      coordinate_transformation_mode=None,
      cubic_coeff_a=None,
      exclude_outside=None,
      extrapolation_value=None,
      nearest_mode=None,
  ):
      """
      Args:
        inputs (list of nn.Variable): Incomming grads/inputs to/of the forward function.
        kwargs (dict of arguments): Dictionary of the corresponding function arguments.
  
      Return:
        list of Variable: Return the gradients wrt inputs of the corresponding function.
      """
      dy = inputs[0]
      x0 = inputs[1]
      raise NotImplementedError(
          "onnx_resize_backward is not implemented."
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: onnx_resize_backward(inputs, scales, sizes, mode, coordinate_transformation_mode, cubic_coeff_a, exclude_outside, extrapolation_value, nearest_mode) without return types