class_docstr: Ensemble consisting of a single model.
  
  Parameters
  ----------
  task_type: int
      An identifier indicating which task is being performed.
  
  metrics: Sequence[Scorer] | Scorer
      The metrics used to evaluate the models.
  
  backend : Backend
      Gives access to the backend of Auto-sklearn. Not used.
  
  random_state: int | RandomState | None = None
      Not used.
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docstr: Return identifier of models in the ensemble.
  
  This includes models which have a weight of zero!
  
  Returns
  -------
  list
docstr_tok: ["Return","identifier","of","models","in","the","ensemble",".","This","includes","models","which","have","a","weight","of","zero","!","Returns","--","--","--","-","list"]
code: def get_selected_model_identifiers(
      self,
  ) -> list[tuple[int, int, float]]:
      """Return identifier of models in the ensemble.
  
      This includes models which have a weight of zero!
  
      Returns
      -------
      list
      """
      return self.identifiers_
  
imports: from __future__ import annotations
  from typing import Sequence
  import os
  import numpy
  from smac.runhistory.runhistory import RunHistory
  from autosklearn.automl_common.common.utils.backend import Backend
  from autosklearn.data.validation import SUPPORTED_FEAT_TYPES
  from autosklearn.ensemble_building.run import Run
  from autosklearn.ensembles.abstract_ensemble import AbstractEnsemble
  from autosklearn.metrics import Scorer, calculate_losses
  from autosklearn.pipeline.base import BasePipeline
label_desc: Use image node_id 7 for calling the AbstractSingleModelEnsemble obj's underlying member method code with example usage: obj.get_selected_model_identifiers() and returns: self