code: def test_mes(self) -> None:
      user_options = {"foo": "bar", "num_restarts": 83}
      generic_options = _argparse_base(
          None, optimizer_options=user_options
      )
      for acqf in (qMaxValueEntropy, qMultiFidelityMaxValueEntropy):
          with self.subTest(acqf=acqf):
              options = optimizer_argparse(
                  acqf,
                  optimizer_options=user_options,
              )
              self.assertEqual(options["sequential"], True)
              self.assertEqual(options, generic_options)
  
imports: from __future__ import annotations
  from importlib import reload
  from unittest.mock import patch
  from ax.models.torch.botorch_modular import optimizer_argparse
  from ax.models.torch.botorch_modular.optimizer_argparse import _argparse_base, MaybeType, optimizer_argparse
  from ax.utils.common.constants import Keys
  from ax.utils.common.testutils import TestCase
  from botorch.acquisition.acquisition import AcquisitionFunction
  from botorch.acquisition.knowledge_gradient import qKnowledgeGradient, qMultiFidelityKnowledgeGradient
  from botorch.acquisition.max_value_entropy_search import qMaxValueEntropy, qMultiFidelityMaxValueEntropy
  from botorch.acquisition.multi_objective.monte_carlo import qExpectedHypervolumeImprovement, qNoisyExpectedHypervolumeImprovement
label_desc: Use image node_id 7 for calling the OptimizerArgparseTest obj's underlying member method code with example usage: obj.test_mes() without return types