class_docstr: A fitter for GPs in multi-fidelity optimisation. 
class_docstr_tok: ["A","fitter","for","GPs","in","multi-fidelity","optimisation","."]
docstr: Gets bandwidths for the SE kernel. 
code: def _get_bandwidth_log_bounds(
      cls, dim, single_bw_bounds, use_same_bandwidth
  ):
      """Gets bandwidths for the SE kernel."""
      if isinstance(single_bw_bounds, float) or isinstance(
          single_bw_bounds, int
      ):
          single_bw_bounds = [
              0.01 * single_bw_bounds,
              10 * single_bw_bounds,
          ]
      single_bandwidth_log_bounds = [
          np.log(x) for x in single_bw_bounds
      ]
      bandwidth_log_bounds = (
          [single_bandwidth_log_bounds]
          if use_same_bandwidth
          else [single_bandwidth_log_bounds] * dim
      )
      return bandwidth_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 14 for calling the EuclideanMFGPFitter obj's underlying member method code with example usage: obj._get_bandwidth_log_bounds(cls, dim, single_bw_bounds, use_same_bandwidth) and returns: bandwidth_log_bounds