def METHOD_NAME(model, benchmark_nums, max_seq_length):
    session = onnxruntime.InferenceSession(model.SerializeToString(), None,
        providers=onnxruntime.get_available_providers())
    shapes = []
    lows = []
    highs = []
    for i in range(len(session.get_inputs())):
        input_name = session.get_inputs()[i].name
        input_shapes = session.get_inputs()[i].shape
        shape = [benchmark_nums]
        shape.append(max_seq_length)
        if input_name == "input_ids":
            low = 0.0
            high = 1000.0
        else:
            low = 0.0
            high = 2.0
        shapes.append(tuple(shape))
        lows.append(low)
        highs.append(high)
    return shapes, lows, highs