class_docstr: A fitter for GPs in multi-fidelity optimisation. 
class_docstr_tok: ["A","fitter","for","GPs","in","multi-fidelity","optimisation","."]
docstr: Sets up the domain kernel as a Poly kernel. 
code: def _domain_poly_kernel_setup(self):
      """Sets up the domain kernel as a Poly kernel."""
      self.domain_scaling_log_bounds = self._get_poly_kernel_bounds(
          self.ZZ, self.XX, self.options.domain_use_same_scalings
      )
      self.cts_hp_bounds.extend(self.domain_scaling_log_bounds)
  
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 12 for calling the EuclideanMFGPFitter obj's underlying member method code with example usage: obj._domain_poly_kernel_setup() without return types