code: def _are_pipeline_tansformations_empty(
      pipeline: ForecastingPipeline,
  ) -> bool:
      """Returns whether the pipeline has transformations for either the target
      or exogenous variables or whether there are no transformatons for either.
  
      Reminder: The pipeline structure is as follows:
      ForecastingPipeline
          - TransformerPipeline(exogenous_steps) [Optional]
          - TransformedTargetForecaster
              - TransformerPipeline(target_steps) [Optional]
              - model
  
      Parameters
      ----------
      pipeline : ForecastingPipeline
          PyCaret's internal Pipeline
  
      Returns
      -------
      bool
          True if there are no transformations, False otherwise
      """
      transform_X_present = _transformations_present_X(pipeline)
      transform_y_present = _transformations_present_y(pipeline)
      return (transform_X_present is False) and (
          transform_y_present is False
      )
  
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 4 for calling a global function with example usage: _are_pipeline_tansformations_empty(pipeline) and returns: unknown