code: def _get_pipeline_estimator_label(
      pipeline: ForecastingPipeline,
  ) -> str:
      """Returns the name of the Transformed Target Forecaster in the pipeline along
      with the name of the final model step in the pipeline.
  
      These names can be used to adjust the search space while tuning the pipeline in
      tune_models (defined search space is only for the models, but we pass the entire
      pipeline for tuning. Hence the model search space has to be adjusted appropriately
      by adding the step names in front).
  
      Parameters
      ----------
      pipeline : ForecastingPipeline
          The pipeline used for modeling
  
      Returns
      -------
      str
          Name of the TransformedTargetForecaster in the pipeline and the name of
          the final model inside the TransformedTargetForecaster. Returns a single
          string appended with "__".
      """
      name_ttf, transformed_target_forecaster = pipeline.steps_[-1]
      name_model, _ = transformed_target_forecaster.steps_[-1]
      return name_ttf + "__" + name_model
  
file_path: pycaret/pycaret/utils/time_series/forecasting/pipeline.py
imports: from copy import deepcopy
  from typing import Optional, Tuple
  import pandas
  from sktime.forecasting.base import BaseForecaster
  from sktime.forecasting.compose import ForecastingPipeline
  from sktime.transformations.compose import TransformerPipeline
  from sktime.transformations.series.impute import Imputer
label_desc: Use image node_id 6 for calling a global function with example usage: _get_pipeline_estimator_label(pipeline) and returns: unknown