code: def get_multi_obj_exp_and_opt_config():
      multi_obj_exp = get_branin_experiment_with_multi_objective(
          with_batch=True
      )
      # pyre-fixme[16]: Optional type has no attribute `objective`.
      metrics = multi_obj_exp.optimization_config.objective.metrics
      multi_objective_thresholds = [
          ObjectiveThreshold(
              metric=metrics[0],
              bound=5.0,
              relative=False,
              op=ComparisonOp.LEQ,
          ),
          ObjectiveThreshold(
              metric=metrics[1],
              bound=10.0,
              relative=False,
              op=ComparisonOp.LEQ,
          ),
      ]
      # pyre-fixme[16]: Optional type has no attribute `clone_with_args`.
      optimization_config = (
          multi_obj_exp.optimization_config.clone_with_args(
              objective_thresholds=multi_objective_thresholds
          )
      )
      return multi_obj_exp, optimization_config
  
imports: from unittest import mock
  import pandas
  import torch
  from ax.core.data import Data
  from ax.core.metric import Metric
  from ax.core.objective import MultiObjective, Objective
  from ax.core.observation import ObservationFeatures
  from ax.core.optimization_config import MultiObjectiveOptimizationConfig
  from ax.core.outcome_constraint import ComparisonOp, ObjectiveThreshold
  from ax.core.parameter import RangeParameter
  from ax.modelbridge.discrete import DiscreteModelBridge
  from ax.modelbridge.factory import get_botorch, get_empirical_bayes_thompson, get_factorial, get_GPEI, get_GPKG, get_GPMES, get_MOO_EHVI, get_MOO_NEHVI, get_MOO_PAREGO, get_MOO_RS, get_MTGP_LEGACY, get_MTGP_NEHVI, get_MTGP_PAREGO, get_sobol, get_thompson, get_uniform
  from ax.modelbridge.random import RandomModelBridge
  from ax.modelbridge.torch import TorchModelBridge
  from ax.models.discrete.eb_thompson import EmpiricalBayesThompsonSampler
  from ax.models.discrete.thompson import ThompsonSampler
  from ax.models.winsorization_config import WinsorizationConfig
  from ax.utils.common.testutils import TestCase
  from ax.utils.testing.core_stubs import get_branin_experiment, get_branin_experiment_with_multi_objective, get_branin_optimization_config, get_factorial_experiment, get_multi_type_experiment, get_multi_type_experiment_with_multi_objective
  from ax.utils.testing.mock import fast_botorch_optimize
  from botorch.models.multitask import MultiTaskGP
label_desc: Use image node_id 1 for calling a global function with example usage: get_multi_obj_exp_and_opt_config() and returns: multi_obj_exp,  optimization_config