code: def test_model_options():
      unstructured_options: t.Dict[str, t.Any] = {
          "task": "sentiment-analysis",
          "tf": (),
          "pt": (),
          "default": {},
          "type": None,
          "kwargs": {},
      }
  
      structured_options = ModelOptions(task="sentiment-analysis")
      assert structured_options.to_dict() == unstructured_options
  
      structured_options = ModelOptions(**unstructured_options)
      assert structured_options is not None
      assert structured_options.tf == ()
      assert structured_options.pt == ()
      assert structured_options.default == {}
      assert structured_options.type is None
      assert structured_options.kwargs == {}
  
imports: from __future__ import annotations
  import logging
  import os
  import typing
  import pytest
  import transformers
  from transformers.models.auto.modeling_auto import AutoModelForAudioClassification
  from transformers.models.auto.modeling_auto import AutoModelForCausalLM
  from transformers.models.auto.modeling_auto import AutoModelForSequenceClassification
  from transformers.pipelines import check_task
  from transformers.pipelines import pipeline
  from transformers.pipelines.audio_classification import AudioClassificationPipeline
  from transformers.trainer_utils import set_seed
  import bentoml
  from bentoml.exceptions import BentoMLException
  from bentoml.transformers import ModelOptions
label_desc: Use image node_id 9 for calling a global function with example usage: test_model_options() without return types