code: def _patched_gp_base_estimator(dimensions, random_state, noise):
      """Returns a GP non-y-normalizing GP estimator."""
      import numpy as np
      from sklearn.utils import check_random_state
      from guild._skopt.utils import normalize_dimensions
  
      space = normalize_dimensions(dimensions)
      rng = check_random_state(random_state)
  
      estimator = skopt.utils.cook_estimator(
          "GP",
          space=space,
          random_state=rng.randint(0, np.iinfo(np.int32).max),
          noise=noise,
      )
      # The point of this function - setting normalize_y to False
      estimator.normalize_y = False
      return estimator
  
imports: import logging
  import os
  import typing
  import warnings
  from guild import _skopt
  from guild import batch_util
  from guild import flag_util
  from guild import op_util
  from guild import query
label_desc: Use image node_id 36 for calling a global function with example usage: _patched_gp_base_estimator(dimensions, random_state, noise) and returns: estimator