code: def _param_for_white_kernel_in_Sum(kernel, kernel_str=""):
      """
      Check if a WhiteKernel exists in a Sum Kernel
      and if it does return the corresponding key in
      `kernel.get_params()`
      """
      if kernel_str != "":
          kernel_str = kernel_str + "__"
  
      if isinstance(kernel, Sum):
          for param, child in kernel.get_params(deep=False).items():
              if isinstance(child, WhiteKernel):
                  return True, kernel_str + param
              else:
                  present, child_str = _param_for_white_kernel_in_Sum(
                      child, kernel_str + param
                  )
                  if present:
                      return True, child_str
  
      return False, "_"
  
file_path: scikit-optimize/skopt/learning/gaussian_process/gpr.py
imports: import numpy
  import warnings
  from scipy.linalg import cho_solve
  from scipy.linalg import solve_triangular
  import sklearn
  from sklearn.gaussian_process import GaussianProcessRegressor
  from sklearn.utils import check_array
  from .kernels import ConstantKernel
  from .kernels import Sum
  from .kernels import RBF
  from .kernels import WhiteKernel
label_desc: Use image node_id 1 for calling a global function with example usage: _param_for_white_kernel_in_Sum(kernel, kernel_str) and returns: False,  str, True,  unknown, True,  child_str