class_docstr: TSPipeline is an E2E solution for time series analysis (only forecasting task for now).
  You can use TSPipeline to:
  
  1. Further development on the prototype. (predict, evaluate, incremental fit)
  
  2. Deploy the model to their scenario. (save, load)
code: def _tsdataset_unscale(self, y):
      if self._scaler:
          from zoo.chronos.data.utils.scale import (
              unscale_timeseries_numpy,
          )
  
          y = unscale_timeseries_numpy(
              y, self._scaler, self._scaler_index
          )
      return y
  
file_path: analytics-zoo/pyzoo/zoo/chronos/autots/tspipeline.py
imports: import os
  from zoo.chronos.data import TSDataset
  from zoo.orca.automl.metrics import Evaluator
label_desc: Use image node_id 10 for calling the TSPipeline obj's underlying member method code with example usage: obj._tsdataset_unscale(y) and returns: y