code: def adjust_ask(asked, keys):
      config = {}
      for i in range(len(asked)):
          config[keys[i]] = asked[i]
      config["hidden_size"] = adjust_value(
          config["hidden_size"], config["n_heads"], min_val=64
      )
  
      config["n_local"] = np.floor(
          config["n_heads"] * config["n_local"]
      )
      if config["n_local"] == 0:
          config["local_window"] = 0
      return config
  
file_path: life2vec/analysis/optimization/pretrain_l2v.py
imports: import numpy
  from skopt import Optimizer
  from skopt.learning import GaussianProcessRegressor
  from skopt.learning.gaussian_process.kernels import Matern
  from skopt.space import Real, Integer
  import pandas
  import glob
  import pickle
  import os
label_desc: Use image node_id 3 for calling a global function with example usage: adjust_ask(asked, keys) and returns: config