code: def _return_results(
      dtw_dist,
      cost_mat,
      acc_cost_mat,
      return_cost=False,
      return_accumulated=False,
      return_path=False,
  ):
      """Return the results according to the parameters."""
      res = (dtw_dist,)
      if return_cost:
          res += (cost_mat,)
      if return_accumulated:
          res += (acc_cost_mat,)
      if return_path:
          path = _return_path(acc_cost_mat)
          res += (path,)
      if len(res) == 1:
          return res[0]
      else:
          return res
  
imports: import numpy
  from math import ceil, log2, sqrt
  from numba import njit, prange
  from sklearn.utils import check_array
label_desc: Use image node_id 14 for calling a global function with example usage: _return_results(dtw_dist, cost_mat, acc_cost_mat, return_cost, return_accumulated, return_path) and returns: res, res