code: def derelativize_optimization_config_with_raw_status_quo(
      optimization_config: OptimizationConfig,
      modelbridge: "modelbridge_module.base.ModelBridge",
      observations: Optional[List[Observation]],
  ) -> OptimizationConfig:
      """Derelativize optimization_config using raw status-quo values"""
      tf = Derelativize(
          search_space=modelbridge.model_space.clone(),
          observations=observations,
          config={"use_raw_status_quo": True},
      )
      return tf.transform_optimization_config(
          optimization_config=optimization_config.clone(),
          modelbridge=modelbridge,
          fixed_features=ObservationFeatures(parameters={}),
      )
  
imports: from __future__ import annotations
  from collections import defaultdict
  from math import isnan
  from numbers import Number
  from typing import Any, Callable, Dict, List, Optional, Tuple, TYPE_CHECKING, Union
  import numpy
  from ax.core.observation import Observation, ObservationData, ObservationFeatures
  from ax.core.optimization_config import OptimizationConfig
  from ax.core.parameter import Parameter
  from ax.core.parameter_constraint import ParameterConstraint
  from ax.core.search_space import RobustSearchSpace, SearchSpace
  from ax.modelbridge.transforms.derelativize import Derelativize
  from scipy.stats import norm
label_desc: Use image node_id 4 for calling a global function with example usage: derelativize_optimization_config_with_raw_status_quo(optimization_config, modelbridge, observations) and returns: tf