code: def sklearn_to_sktime(estimator):
      """Coerces an sklearn estimator to the sktime pipeline interface.
  
      Creates a pipeline of two elements, the identity transformer and the estimator.
      The identity transformer acts as adapter and holds sktime base class logic.
  
      Developer note:
      Type dispatch logic is in the transformer base class, in the `__mul__` dunder.
  
      Parameters
      ----------
      estimator : sklearn compatible estimator
          can be classifier, regressor, transformer, clusterer
  
      Returns
      -------
      pipe : sktime estimator of corresponding time series type
          classifiers, regressors, clusterers are converted to time series counterparts
          by flattening time series. Assumes equal length time series.
          transformers are converted to time series transformer by application per series
      """
      from sktime.transformations.compose import Id
  
      return make_pipeline(Id(), estimator)
  
label_desc: Use image node_id 1 for calling a global function with example usage: sklearn_to_sktime(estimator) and returns: make_pipeline