code: def transform(self, X):
          
          self._check_method("transform")
          X = self._check_array(X)
  
          if isinstance(X, da.Array):
              return X.map_blocks(_transform, estimator=self._postfit_estimator)
          elif isinstance(X, dd._Frame):
              return X.map_partitions(_transform, estimator=self._postfit_estimator)
          else:
              return _transform(X, estimator=self._postfit_estimator)
docs: Transform block or partition-wise for dask inputs.
  
          For dask inputs, a dask array or dataframe is returned. For other
          inputs (NumPy array, pandas dataframe, scipy sparse matrix), the
          regular return value is returned.
  
          If the underlying estimator does not have a ``transform`` method, then
          an ``AttributeError`` is raised.
  
          Parameters
          ----------
          X : array-like
  
          Returns
          -------
          transformed : array-like