class_docstr: Change the relative flag of the given relative optimization configuration
  to False. This is needed in order for the new opt config to pass ModelBridge
  that requires non-relativized opt config.
  
  Also transforms absolute data and opt configs to relative.
  
  Requires a modelbridge with a status quo set to work.
  
  Abstract property control_as_constant is set to True/False in its subclasses
  Relativize and RelativizeWithConstantControl respectively to account for
  appropriate transform/untransform differently.
docstr: Change the relative flag of the given relative optimization configuration
  to False. This is needed in order for the new opt config to pass ModelBridge
  that requires non-relativized opt config.
  
  Args:
      opt_config: Optimization configuration relative to status quo.
  
  Returns:
      Optimization configuration relative to status quo with relative flag
      equal to false.
docstr_tok: ["Change","the","relative","flag","of","the","given","relative","optimization","configuration","to","False",".","This","is","needed","in","order","for","the","new","opt","config","to","pass","ModelBridge","that","requires","non-relativized","opt","config",".","Args",":","opt_config",":","Optimization","configuration","relative","to","status","quo",".","Returns",":","Optimization","configuration","relative","to","status","quo","with","relative","flag","equal","to","false","."]
code: def transform_optimization_config(
      self,
      optimization_config: OptimizationConfig,
      modelbridge: Optional[modelbridge_module.base.ModelBridge] = None,
      fixed_features: Optional[ObservationFeatures] = None,
  ) -> OptimizationConfig:
      r"""
      Change the relative flag of the given relative optimization configuration
      to False. This is needed in order for the new opt config to pass ModelBridge
      that requires non-relativized opt config.
  
      Args:
          opt_config: Optimization configuration relative to status quo.
  
      Returns:
          Optimization configuration relative to status quo with relative flag
          equal to false.
  
      """
      # Getting constraints
      constraints = [
          constraint.clone()
          for constraint in optimization_config.outcome_constraints
      ]
      if not all(
          constraint.relative
          for constraint in optimization_config.outcome_constraints
      ):
          raise ValueError(
              "All constraints must be relative to use the Relativize transform."
          )
      for constraint in constraints:
          constraint.relative = False
  
      if isinstance(
          optimization_config, MultiObjectiveOptimizationConfig
      ):
          # Getting objective thresholds
          obj_thresholds = [
              obj_threshold.clone()
              for obj_threshold in optimization_config.objective_thresholds
          ]
          for obj_threshold in obj_thresholds:
              if not obj_threshold.relative:
                  raise ValueError(
                      "All objective thresholds must be relative to use "
                      "the Relativize transform."
                  )
              obj_threshold.relative = False
  
          new_optimization_config = MultiObjectiveOptimizationConfig(
              objective=optimization_config.objective,
              outcome_constraints=constraints,
              objective_thresholds=obj_thresholds,
          )
      else:
          new_optimization_config = OptimizationConfig(
              objective=optimization_config.objective,
              outcome_constraints=constraints,
          )
  
      return new_optimization_config
  
imports: from __future__ import annotations
  from abc import ABC, abstractmethod
  from math import sqrt
  from typing import Callable, Dict, List, Optional, Tuple, TYPE_CHECKING
  import numpy
  from ax.core.observation import Observation, ObservationData, ObservationFeatures
  from ax.core.optimization_config import MultiObjectiveOptimizationConfig, OptimizationConfig
  from ax.core.outcome_constraint import OutcomeConstraint
  from ax.core.search_space import SearchSpace
  from ax.modelbridge import ModelBridge
  from ax.modelbridge.transforms.base import Transform
  from ax.models.types import TConfig
  from ax.utils.common.typeutils import not_none
  from ax.utils.stats.statstools import relativize, unrelativize
label_desc: Use image node_id 3 for calling the BaseRelativize obj's underlying member method code with example usage: obj.transform_optimization_config(optimization_config, modelbridge, fixed_features) and returns: new_optimization_config