class_docstr: Fits a GP by tuning the kernel hyper-params. 
class_docstr_tok: ["Fits","a","GP","by","tuning","the","kernel","hyper-params","."]
docstr: Wrapper to pack the kernel hyper-parameters into a dictionary. 
code: def _prep_init_kernel_hyperparams(self, kernel_type):
      """Wrapper to pack the kernel hyper-parameters into a dictionary."""
      return prep_euclidean_integral_kernel_hyperparams(
          kernel_type, self.options, self.dim
      )
  
imports: from __future__ import division
  from argparse import Namespace
  import numpy
  from .None import gp_core, mf_gp
  from .None import kernel
  from ..utils.ancillary_utils import get_list_of_floats_as_str
  from ..utils.general_utils import get_sublist_from_indices, map_to_bounds
  from ..utils.option_handler import get_option_specs, load_options
  from ..utils.oper_utils import random_sample_from_discrete_domain
  from ..utils.reporters import get_reporter
label_desc: Use image node_id 7 for calling the EuclideanGPFitter obj's underlying member method code with example usage: obj._prep_init_kernel_hyperparams(kernel_type) and returns: prep_euclidean_integral_kernel_hyperparams