class_docstr: Handles parameter management for estimators composed of named estimators.
  
  Partly adapted from sklearn utils.metaestimator.py.
docstr: Return whether any estimator in list has tag `tag_name` of value `value`.
  
  Parameters
  ----------
  tag_name : str, name of the tag to check
  value : value of the tag to check for
  estimators : list of (str, estimator) pairs to query for the tag/value
  
  Return
  ------
  bool : True iff at least one estimator in the list has value in tag tag_name
docstr_tok: ["Return","whether","any","estimator","in","list","has","tag","`","tag_name","`","of","value","`","value","`",".","Parameters","--","--","--","--","--","tag_name",":","str",",","name","of","the","tag","to","check","value",":","value","of","the","tag","to","check","for","estimators",":","list","of","(","str",",","estimator",")","pairs","to","query","for","the","tag\/value","Return","--","--","--","bool",":","True","iff","at","least","one","estimator","in","the","list","has","value","in","tag","tag_name"]
code: def _anytagis(self, tag_name, value, estimators):
      """Return whether any estimator in list has tag `tag_name` of value `value`.
  
      Parameters
      ----------
      tag_name : str, name of the tag to check
      value : value of the tag to check for
      estimators : list of (str, estimator) pairs to query for the tag/value
  
      Return
      ------
      bool : True iff at least one estimator in the list has value in tag tag_name
      """
      tagis = [
          est.get_tag(tag_name, value) == value for _, est in estimators
      ]
      return any(tagis)
  
imports: from inspect import isclass
  import numpy
  import pandas
  from sktime.base import BaseEstimator
label_desc: Use image node_id 18 for calling the _HeterogenousMetaEstimator obj's underlying member method code with example usage: obj._anytagis(tag_name, value, estimators) and returns: any