class_docstr: Check functionality of optimization loop.
code: def test_annotate_exception(self, _):
      strategy0 = GenerationStrategy(
          name="Sobol",
          steps=[GenerationStep(model=Models.SOBOL, num_trials=-1)],
      )
      loop = OptimizationLoop.with_evaluation_function(
          parameters=[
              {
                  "name": "x1",
                  "type": "range",
                  "bounds": [-5.0, 10.0],
                  "value_type": "float",
                  "log_scale": False,
              },
              {"name": "x2", "type": "range", "bounds": [0.0, 10.0]},
          ],
          experiment_name="test",
          objective_name="branin",
          minimize=True,
          evaluation_function=_branin_evaluation_function,
          total_trials=6,
          generation_strategy=strategy0,
      )
      with self.assertRaisesRegex(
          expected_exception=RuntimeError,
          expected_regex="Cholesky errors typically occur",
      ):
          loop.run_trial()
  
imports: from typing import Dict, Tuple, Union
  from unittest.mock import Mock, patch
  import numpy
  from ax.exceptions.core import UserInputError
  from ax.metrics.branin import branin
  from ax.modelbridge.generation_strategy import GenerationStep, GenerationStrategy
  from ax.modelbridge.registry import Models
  from ax.service.managed_loop import OptimizationLoop, optimize
  from ax.utils.common.testutils import TestCase
  from ax.utils.testing.mock import fast_botorch_optimize
  from numpy import ndarray
label_desc: Use image node_id 14 for calling the TestManagedLoop obj's underlying member method code with example usage: obj.test_annotate_exception(_) without return types