class_docstr: Fits a GP by tuning the kernel hyper-params. 
class_docstr_tok: ["Fits","a","GP","by","tuning","the","kernel","hyper-params","."]
docstr: Constructor. 
code: def __init__(self, X, Y, options=None, reporter=None):
      """Constructor."""
      self.dim = len(X[0])
      reporter = get_reporter(reporter)
      options = load_options(euclidean_gp_args, partial_options=options)
      super(EuclideanGPFitter, self).__init__(X, Y, options, reporter)
  
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 1 to create a new EuclideanGPFitter object from inherited base classes: gp_core with example: obj = EuclideanGPFitter(X, Y, options, reporter)