class_docstr: Handles parameter management for estimators composed of named estimators.
  
  Partly adapted from sklearn utils.metaestimator.py.
docstr: Return list of estimator tuples, from a list or tuple.
  
  Parameters
  ----------
  estimators : list of estimators, or list of (str, estimator tuples)
  clone_ests : bool, optional, default=False.
      whether estimators of the return are cloned (True) or references (False)
  
  Returns
  -------
  est_tuples : list of (str, estimator) tuples
      if estimators was a list of (str, estimator) tuples, then identical/cloned
      if was a list of estimators, then str are generated via _get_estimator_names
docstr_tok: ["Return","list","of","estimator","tuples",",","from","a","list","or","tuple",".","Parameters","--","--","--","--","--","estimators",":","list","of","estimators",",","or","list","of","(","str",",","estimator","tuples",")","clone_ests",":","bool",",","optional",",","default=False",".","whether","estimators","of","the","return","are","cloned","(","True",")","or","references","(","False",")","Returns","--","--","--","-","est_tuples",":","list","of","(","str",",","estimator",")","tuples","if","estimators","was","a","list","of","(","str",",","estimator",")","tuples",",","then","identical\/cloned","if","was","a","list","of","estimators",",","then","str","are","generated","via","_get_estimator_names"]
code: def _get_estimator_tuples(self, estimators, clone_ests=False):
      """Return list of estimator tuples, from a list or tuple.
  
      Parameters
      ----------
      estimators : list of estimators, or list of (str, estimator tuples)
      clone_ests : bool, optional, default=False.
          whether estimators of the return are cloned (True) or references (False)
  
      Returns
      -------
      est_tuples : list of (str, estimator) tuples
          if estimators was a list of (str, estimator) tuples, then identical/cloned
          if was a list of estimators, then str are generated via _get_estimator_names
      """
      ests = self._get_estimator_list(estimators)
      if clone_ests:
          ests = [e.clone() for e in ests]
      unique_names = self._get_estimator_names(
          estimators, make_unique=True
      )
      est_tuples = list(zip(unique_names, ests))
      return est_tuples
  
imports: from inspect import isclass
  import numpy
  import pandas
  from sktime.base import BaseEstimator
label_desc: Use image node_id 15 for calling the _HeterogenousMetaEstimator obj's underlying member method code with example usage: obj._get_estimator_tuples(estimators, clone_ests) and returns: est_tuples